R-universe search: signal

r-forge

signal:Signal Processing

A set of signal processing functions originally written for 'Matlab' and 'Octave'. Includes filter generation utilities, filtering functions, resampling routines, and visualization of filter models. It also includes interpolation functions.

Maintained by Uwe Ligges. Last updated 1 years ago.

fortran

71.8 match 8.78 score 828 scripts 151 dependents

gjmvanboxtel

gsignal:Signal Processing

R implementation of the 'Octave' package 'signal', containing a variety of signal processing tools, such as signal generation and measurement, correlation and convolution, filtering, filter design, filter analysis and conversion, power spectrum analysis, system identification, decimation and sample rate change, and windowing.

Maintained by Geert van Boxtel. Last updated 2 months ago.

signal-processing signals cpp

42.8 match 24 stars 10.03 score 133 scripts 34 dependents

mlverse

torch:Tensors and Neural Networks with 'GPU' Acceleration

Provides functionality to define and train neural networks similar to 'PyTorch' by Paszke et al (2019) <doi:10.48550/arXiv.1912.01703> but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.

Maintained by Daniel Falbel. Last updated 6 days ago.

autograd deep-learning torch cpp

23.0 match 520 stars 16.52 score 1.4k scripts 38 dependents

marce10

warbleR:Streamline Bioacoustic Analysis

Functions aiming to facilitate the analysis of the structure of animal acoustic signals in 'R'. 'warbleR' makes use of the basic sound analysis tools from the packages 'tuneR' and 'seewave', and offers new tools for explore and quantify acoustic signal structure. The package allows to organize and manipulate multiple sound files, create spectrograms of complete recordings or individual signals in different formats, run several measures of acoustic structure, and characterize different structural levels in acoustic signals.

Maintained by Marcelo Araya-Salas. Last updated 2 months ago.

animal-acoustic-signals audio-processing bioacoustics spectrogram streamline-analysis cpp

22.7 match 54 stars 11.01 score 270 scripts 4 dependents

coffeemuggler

eseis:Environmental Seismology Toolbox

Environmental seismology is a scientific field that studies the seismic signals, emitted by Earth surface processes. This package provides all relevant functions to read/write seismic data files, prepare, analyse and visualise seismic data, and generate reports of the processing history.

Maintained by Michael Dietze. Last updated 4 months ago.

cpp

56.2 match 9 stars 4.42 score 58 scripts

tidymodels

recipes:Preprocessing and Feature Engineering Steps for Modeling

A recipe prepares your data for modeling. We provide an extensible framework for pipeable sequences of feature engineering steps provides preprocessing tools to be applied to data. Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting processed output can then be used as inputs for statistical or machine learning models.

Maintained by Max Kuhn. Last updated 6 days ago.

12.8 match 584 stars 18.71 score 7.2k scripts 380 dependents

bioc

matter:Out-of-core statistical computing and signal processing

Toolbox for larger-than-memory scientific computing and visualization, providing efficient out-of-core data structures using files or shared memory, for dense and sparse vectors, matrices, and arrays, with applications to nonuniformly sampled signals and images.

Maintained by Kylie A. Bemis. Last updated 3 months ago.

infrastructure datarepresentation dataimport dimensionreduction preprocessing cpp

22.1 match 57 stars 9.52 score 64 scripts 2 dependents

martin3141

spant:MR Spectroscopy Analysis Tools

Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data. The package includes methods for spectral fitting: Wilson (2021) <DOI:10.1002/mrm.28385> and spectral alignment: Wilson (2018) <DOI:10.1002/mrm.27605>.

Maintained by Martin Wilson. Last updated 30 days ago.

brain mri mrs mrshub spectroscopy fortran

23.0 match 25 stars 8.52 score 81 scripts

l-ramirez-lopez

prospectr:Miscellaneous Functions for Processing and Sample Selection of Spectroscopic Data

Functions to preprocess spectroscopic data and conduct (representative) sample selection/calibration sampling.

Maintained by Leonardo Ramirez-Lopez. Last updated 11 days ago.

chemometrics derivatives infrared near-infrared nir pedometrics preprocessing resample sampling signal soil-spectroscopy spectroscopy openblas cpp openmp

17.3 match 42 stars 10.00 score 326 scripts 4 dependents

chr1swallace

coloc:Colocalisation Tests of Two Genetic Traits

Performs the colocalisation tests described in Giambartolomei et al (2013) <doi:10.1371/journal.pgen.1004383>, Wallace (2020) <doi:10.1371/journal.pgen.1008720>, Wallace (2021) <doi:10.1371/journal.pgen.1009440>.

Maintained by Chris Wallace. Last updated 4 months ago.

12.7 match 162 stars 12.23 score 916 scripts 3 dependents

r-forge

Rwave:Time-Frequency analysis of 1-D signals

Rwave is a library of R functions which provide an environment for the Time-Frequency analysis of 1-D signals (and especially for the wavelet and Gabor transforms of noisy signals). It was originally written for Splus by Rene Carmona, Bruno Torresani, and Wen L. Hwang, first at the University of California at Irvine and then at Princeton University. Credit should also be given to Andrea Wang whose functions on the dyadic wavelet transform are included. Rwave is based on the book: "Practical Time-Frequency Analysis: Gabor and Wavelet Transforms with an Implementation in S", by Rene Carmona, Wen L. Hwang and Bruno Torresani, Academic Press, 1998. This package is no longer actively maintained. A C++ rewrite of core functionality is in progress. If you'd like to participate, please contact Christian Gunning.

Maintained by Brandon Whitcher. Last updated 13 years ago.

30.7 match 4.82 score 88 scripts 5 dependents

r-lib

rlang:Functions for Base Types and Core R and 'Tidyverse' Features

A toolbox for working with base types, core R features like the condition system, and core 'Tidyverse' features like tidy evaluation.

Maintained by Lionel Henry. Last updated 20 days ago.

7.2 match 517 stars 20.53 score 9.8k scripts 15k dependents

bioc

OmnipathR:OmniPath web service client and more

A client for the OmniPath web service (https://www.omnipathdb.org) and many other resources. It also includes functions to transform and pretty print some of the downloaded data, functions to access a number of other resources such as BioPlex, ConsensusPathDB, EVEX, Gene Ontology, Guide to Pharmacology (IUPHAR/BPS), Harmonizome, HTRIdb, Human Phenotype Ontology, InWeb InBioMap, KEGG Pathway, Pathway Commons, Ramilowski et al. 2015, RegNetwork, ReMap, TF census, TRRUST and Vinayagam et al. 2011. Furthermore, OmnipathR features a close integration with the NicheNet method for ligand activity prediction from transcriptomics data, and its R implementation `nichenetr` (available only on github).

Maintained by Denes Turei. Last updated 19 days ago.

graphandnetwork network pathways software thirdpartyclient dataimport datarepresentation genesignaling generegulation systemsbiology transcriptomics singlecell annotation kegg complexes enzyme-ptm networks networks-biology omnipath proteins quarto

14.7 match 126 stars 9.90 score 226 scripts 2 dependents

fkeck

phylosignal:Exploring the Phylogenetic Signal in Continuous Traits

A collection of tools to explore the phylogenetic signal in univariate and multivariate data. The package provides functions to plot traits data against a phylogenetic tree, different measures and tests for the phylogenetic signal, methods to describe where the signal is located and a phylogenetic clustering method.

Maintained by Francois Keck. Last updated 1 years ago.

openblas cpp

19.9 match 16 stars 7.22 score 104 scripts

bioc

dominoSignal:Cell Communication Analysis for Single Cell RNA Sequencing

dominoSignal is a package developed to analyze cell signaling through ligand - receptor - transcription factor networks in scRNAseq data. It takes as input information transcriptomic data, requiring counts, z-scored counts, and cluster labels, as well as information on transcription factor activation (such as from SCENIC) and a database of ligand and receptor pairings (such as from CellPhoneDB). This package creates an object storing ligand - receptor - transcription factor linkages by cluster and provides several methods for exploring, summarizing, and visualizing the analysis.

Maintained by Jacob T Mitchell. Last updated 5 months ago.

systemsbiology singlecell transcriptomics network

21.0 match 5 stars 6.50 score 5 scripts

geomorphr

geomorph:Geometric Morphometric Analyses of 2D and 3D Landmark Data

Read, manipulate, and digitize landmark data, generate shape variables via Procrustes analysis for points, curves and surfaces, perform shape analyses, and provide graphical depictions of shapes and patterns of shape variation.

Maintained by Dean Adams. Last updated 1 months ago.

10.4 match 76 stars 12.05 score 700 scripts 6 dependents

murrayefford

secr:Spatially Explicit Capture-Recapture

Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.

Maintained by Murray Efford. Last updated 2 hours ago.

cpp

12.1 match 3 stars 10.14 score 410 scripts 5 dependents

paternogbc

sensiPhy:Sensitivity Analysis for Comparative Methods

An implementation of sensitivity analysis for phylogenetic comparative methods. The package is an umbrella of statistical and graphical methods that estimate and report different types of uncertainty in PCM: (i) Species Sampling uncertainty (sample size; influential species and clades). (ii) Phylogenetic uncertainty (different topologies and/or branch lengths). (iii) Data uncertainty (intraspecific variation and measurement error).

Maintained by Gustavo Paterno. Last updated 5 years ago.

comparative-methods ecology evolution phylogenetics sensitivity-analysis

19.1 match 13 stars 6.38 score 61 scripts

shah-in-boots

EGM:Evaluating Cardiac Electrophysiology Signals

A system for importing electrophysiological signal, based on the 'Waveform Database (WFDB)' software package, written by Moody et al 2022 <doi:10.13026/gjvw-1m31>. A wrapper for utilizing 'WFDB' functions for reading and writing signal data, as well as functions for visualization and analysis are provided. A stable and broadly compatible class for working with signal data, supporting the reading in of cardiac electrophysiogical files such as intracardiac electrograms, is introduced.

Maintained by Anish S. Shah. Last updated 20 days ago.

cardiology electrophysiology signal-processing cpp

22.8 match 5.32 score 9 scripts

bioc

sesame:SEnsible Step-wise Analysis of DNA MEthylation BeadChips

Tools For analyzing Illumina Infinium DNA methylation arrays. SeSAMe provides utilities to support analyses of multiple generations of Infinium DNA methylation BeadChips, including preprocessing, quality control, visualization and inference. SeSAMe features accurate detection calling, intelligent inference of ethnicity, sex and advanced quality control routines.

Maintained by Wanding Zhou. Last updated 2 months ago.

dnamethylation methylationarray preprocessing qualitycontrol bioinformatics dna-methylation microarray

13.2 match 69 stars 9.08 score 258 scripts 1 dependents

eu-ecdc

EpiSignalDetection:Signal Detection Analysis

Exploring time series for signal detection. It is specifically designed to detect possible outbreaks using infectious disease surveillance data at the European Union / European Economic Area or country level. Automatic detection tools used are presented in the paper "Monitoring count time series in R: aberration detection in public health surveillance", by Salmon et al. (2016) <doi:10.18637/jss.v070.i10>. The package includes: - Signal Detection tool, an interactive 'shiny' application in which the user can import external data and perform basic signal detection analyses; - An automated report in HTML format, presenting the results of the time series analysis in tables and graphs. This report can also be stratified by population characteristics (see 'Population' variable). This project was funded by the European Centre for Disease Prevention and Control.

Maintained by Joana Gomes Dias. Last updated 6 years ago.

21.7 match 16 stars 5.43 score 17 scripts

craddm

eegUtils:Utilities for Electroencephalographic (EEG) Analysis

Electroencephalography data processing and visualization tools. Includes import functions for 'BioSemi' (.BDF), 'Neuroscan' (.CNT), 'Brain Vision Analyzer' (.VHDR), 'EEGLAB' (.set) and 'Fieldtrip' (.mat). Many preprocessing functions such as referencing, epoching, filtering, and ICA are available. There are a variety of visualizations possible, including timecourse and topographical plotting.

Maintained by Matt Craddock. Last updated 5 months ago.

eeg eeg-analysis eeg-data eeg-signals eeg-signals-processing openblas cpp openmp

17.8 match 106 stars 6.54 score 82 scripts

capnrefsmmat

covidcast:Client for Delphi's 'COVIDcast Epidata' API

Tools for Delphi's 'COVIDcast Epidata' API: data access, maps and time series plotting, and basic signal processing. The API includes a collection of numerous indicators relevant to the COVID-19 pandemic in the United States, including official reports, de-identified aggregated medical claims data, large-scale surveys of symptoms and public behavior, and mobility data, typically updated daily and at the county level. All data sources are documented at <https://cmu-delphi.github.io/delphi-epidata/api/covidcast.html>.

Maintained by Alex Reinhart. Last updated 2 years ago.

23.9 match 4.86 score 293 scripts

r-lib

ps:List, Query, Manipulate System Processes

List, query and manipulate all system processes, on 'Windows', 'Linux' and 'macOS'.

Maintained by Gábor Csárdi. Last updated 17 days ago.

7.0 match 79 stars 15.09 score 108 scripts 1.5k dependents

bioc

EnrichedHeatmap:Making Enriched Heatmaps

Enriched heatmap is a special type of heatmap which visualizes the enrichment of genomic signals on specific target regions. Here we implement enriched heatmap by ComplexHeatmap package. Since this type of heatmap is just a normal heatmap but with some special settings, with the functionality of ComplexHeatmap, it would be much easier to customize the heatmap as well as concatenating to a list of heatmaps to show correspondance between different data sources.

Maintained by Zuguang Gu. Last updated 5 months ago.

software visualization sequencing genomeannotation coverage cpp

9.6 match 190 stars 10.87 score 330 scripts 1 dependents

bioc

cosmosR:COSMOS (Causal Oriented Search of Multi-Omic Space)

COSMOS (Causal Oriented Search of Multi-Omic Space) is a method that integrates phosphoproteomics, transcriptomics, and metabolomics data sets based on prior knowledge of signaling, metabolic, and gene regulatory networks. It estimated the activities of transcrption factors and kinases and finds a network-level causal reasoning. Thereby, COSMOS provides mechanistic hypotheses for experimental observations across mulit-omics datasets.

Maintained by Attila Gabor. Last updated 5 months ago.

cellbiology pathways network proteomics metabolomics transcriptomics genesignaling data-integration metabolomic-data network-modelling phosphoproteomics

14.4 match 59 stars 7.22 score 35 scripts

spatial-ews

spatialwarnings:Spatial Early Warning Signals of Ecosystem Degradation

Tools to compute and assess significance of early-warnings signals (EWS) of ecosystem degradation on raster data sets. EWS are spatial metrics derived from raster data -- e.g. spatial autocorrelation -- that increase before an ecosystem undergoes a non-linear transition (Genin et al. (2018) <doi:10.1111/2041-210X.13058>).

Maintained by Alexandre Genin. Last updated 6 months ago.

catastrophic critical ecology indicators points shifts space transitions cpp

19.3 match 15 stars 5.32 score 46 scripts

bioc

BindingSiteFinder:Binding site defintion based on iCLIP data

Precise knowledge on the binding sites of an RNA-binding protein (RBP) is key to understand (post-) transcriptional regulatory processes. Here we present a workflow that describes how exact binding sites can be defined from iCLIP data. The package provides functions for binding site definition and result visualization. For details please see the vignette.

Maintained by Mirko Brüggemann. Last updated 4 months ago.

sequencing geneexpression generegulation functionalgenomics coverage dataimport binding-site-classification binding-sites bioconductor-package iclip rna-binding-proteins

17.8 match 6 stars 5.65 score 3 scripts

ropensci

baRulho:Quantifying (Animal) Sound Degradation

Intended to facilitate acoustic analysis of (animal) sound propagation experiments, which typically aim to quantify changes in signal structure when transmitted in a given habitat by broadcasting and re-recording animal sounds at increasing distances. The package offers a workflow with functions to prepare the data set for analysis as well as to calculate and visualize several degradation metrics, including blur ratio, signal-to-noise ratio, excess attenuation and envelope correlation among others (Dabelsteen et al 1993 <doi:10.1121/1.406682>).

Maintained by Marcelo Araya-Salas. Last updated 24 days ago.

acoustic-signals animal behavior bioacoustics

14.5 match 7 stars 6.72 score 18 scripts

bioc

InTAD:Search for correlation between epigenetic signals and gene expression in TADs

The package is focused on the detection of correlation between expressed genes and selected epigenomic signals (i.e. enhancers obtained from ChIP-seq data) either within topologically associated domains (TADs) or between chromatin contact loop anchors. Various parameters can be controlled to investigate the influence of external factors and visualization plots are available for each analysis step.

Maintained by Konstantin Okonechnikov. Last updated 5 months ago.

epigenetics sequencing chipseq rnaseq hic geneexpression immunooncology

22.3 match 4.30 score 6 scripts

bioc

GreyListChIP:Grey Lists -- Mask Artefact Regions Based on ChIP Inputs

Identify regions of ChIP experiments with high signal in the input, that lead to spurious peaks during peak calling. Remove reads aligning to these regions prior to peak calling, for cleaner ChIP analysis.

Maintained by Matt Eldridge. Last updated 5 months ago.

chipseq alignment preprocessing differentialpeakcalling sequencing genomeannotation coverage

18.9 match 4.93 score 10 scripts 4 dependents

bioc

minfi:Analyze Illumina Infinium DNA methylation arrays

Tools to analyze & visualize Illumina Infinium methylation arrays.

Maintained by Kasper Daniel Hansen. Last updated 4 months ago.

immunooncology dnamethylation differentialmethylation epigenetics microarray methylationarray multichannel twochannel dataimport normalization preprocessing qualitycontrol

7.1 match 60 stars 12.83 score 996 scripts 26 dependents

skembel

picante:Integrating Phylogenies and Ecology

Functions for phylocom integration, community analyses, null-models, traits and evolution. Implements numerous ecophylogenetic approaches including measures of community phylogenetic and trait diversity, phylogenetic signal, estimation of trait values for unobserved taxa, null models for community and phylogeny randomizations, and utility functions for data input/output and phylogeny plotting. A full description of package functionality and methods are provided by Kembel et al. (2010) <doi:10.1093/bioinformatics/btq166>.

Maintained by Steven W. Kembel. Last updated 2 years ago.

7.9 match 34 stars 11.42 score 1.1k scripts 16 dependents

mhealthgroup

MIMSunit:Algorithm to Compute Monitor Independent Movement Summary Unit (MIMS-Unit)

The MIMS-unit algorithm is developed to compute Monitor Independent Movement Summary Unit, a measurement to summarize raw accelerometer data while ensuring harmonized results across different devices. It also includes scripts to reproduce results in the related publication (John, D., Tang. Q., Albinali, F. and Intille, S. (2019) <doi:10.1123/jmpb.2018-0068>).

Maintained by Qu Tang. Last updated 3 years ago.

22.4 match 12 stars 3.98 score 16 scripts

fabnavarro

rwavelet:Wavelet Analysis

Perform wavelet analysis (orthogonal,translation invariant, tensorial, 1-2-3d transforms, thresholding, block thresholding, linear,...) with applications to data compression, denoising/regression or clustering. The core of the code is a port of 'MATLAB' Wavelab toolbox written by D. Donoho, A. Maleki and M. Shahram (<https://statweb.stanford.edu/~wavelab/>).

Maintained by Navarro Fabien. Last updated 7 months ago.

machine-learning regression wavelet

17.7 match 5 stars 5.01 score 41 scripts

fabnavarro

gasper:Graph Signal Processing

Provides the standard operations for signal processing on graphs: graph Fourier transform, spectral graph wavelet transform, visualization tools. It also implements a data driven method for graph signal denoising/regression, for details see De Loynes, Navarro, Olivier (2019) <arxiv:1906.01882>. The package also provides an interface to the SuiteSparse Matrix Collection, <https://sparse.tamu.edu/>, a large and widely used set of sparse matrix benchmarks collected from a wide range of applications.

Maintained by Fabien Navarro. Last updated 7 months ago.

data-science graph graph-signal-processing graph-wavelet machine-learning spectral-graph-theory statistics suitesparse wavelet-transform openblas cpp

21.7 match 8 stars 4.03 score 27 scripts

bioc

PepsNMR:Pre-process 1H-NMR FID signals

This package provides R functions for common pre-procssing steps that are applied on 1H-NMR data. It also provides a function to read the FID signals directly in the Bruker format.

Maintained by Manon Martin. Last updated 5 months ago.

software preprocessing visualization metabolomics dataimport

12.9 match 10 stars 6.62 score 23 scripts 1 dependents

eagerai

fastai:Interface to 'fastai'

The 'fastai' <https://docs.fast.ai/index.html> library simplifies training fast and accurate neural networks using modern best practices. It is based on research in to deep learning best practices undertaken at 'fast.ai', including 'out of the box' support for vision, text, tabular, audio, time series, and collaborative filtering models.

Maintained by Turgut Abdullayev. Last updated 11 months ago.

audio collaborative-filtering darknet darknet-image-classification fastai medical object-detection tabular text vision

9.0 match 118 stars 9.40 score 76 scripts

bioc

TOAST:Tools for the analysis of heterogeneous tissues

This package is devoted to analyzing high-throughput data (e.g. gene expression microarray, DNA methylation microarray, RNA-seq) from complex tissues. Current functionalities include 1. detect cell-type specific or cross-cell type differential signals 2. tree-based differential analysis 3. improve variable selection in reference-free deconvolution 4. partial reference-free deconvolution with prior knowledge.

Maintained by Ziyi Li. Last updated 5 months ago.

dnamethylation geneexpression differentialexpression differentialmethylation microarray genetarget epigenetics methylationarray

10.5 match 11 stars 8.01 score 104 scripts 3 dependents

dipterix

ravetools:Signal and Image Processing Toolbox for Analyzing Intracranial Electroencephalography Data

Implemented fast and memory-efficient Notch-filter, Welch-periodogram, discrete wavelet spectrogram for minutes of high-resolution signals, fast 3D convolution, image registration, 3D mesh manipulation; providing fundamental toolbox for intracranial Electroencephalography (iEEG) pipelines. Documentation and examples about 'RAVE' project are provided at <https://rave.wiki>, and the paper by John F. Magnotti, Zhengjia Wang, Michael S. Beauchamp (2020) <doi:10.1016/j.neuroimage.2020.117341>; see 'citation("ravetools")' for details.

Maintained by Zhengjia Wang. Last updated 4 days ago.

fftw3 cpp

16.3 match 3 stars 5.13 score 20 scripts 1 dependents

bioc

GenomicPlot:Plot profiles of next generation sequencing data in genomic features

Visualization of next generation sequencing (NGS) data is essential for interpreting high-throughput genomics experiment results. 'GenomicPlot' facilitates plotting of NGS data in various formats (bam, bed, wig and bigwig); both coverage and enrichment over input can be computed and displayed with respect to genomic features (such as UTR, CDS, enhancer), and user defined genomic loci or regions. Statistical tests on signal intensity within user defined regions of interest can be performed and represented as boxplots or bar graphs. Parallel processing is used to speed up computation on multicore platforms. In addition to genomic plots which is suitable for displaying of coverage of genomic DNA (such as ChIPseq data), metagenomic (without introns) plots can also be made for RNAseq or CLIPseq data as well.

Maintained by Shuye Pu. Last updated 2 months ago.

alternativesplicing chipseq coverage geneexpression rnaseq sequencing software transcription visualization annotation

14.2 match 3 stars 5.62 score 4 scripts

bsnatr

tswge:Time Series for Data Science

Accompanies the texts Time Series for Data Science with R by Woodward, Sadler and Robertson & Applied Time Series Analysis with R, 2nd edition by Woodward, Gray, and Elliott. It is helpful for data analysis and for time series instruction.

Maintained by Bivin Sadler. Last updated 2 years ago.

29.3 match 2.70 score 496 scripts

pievos101

TopKSignal:A Convex Optimization Tool for Signal Reconstruction from Multiple Ranked Lists

A mathematical optimization procedure in combination with statistical bootstrap for the estimation of the latent signals (sometimes called scores) informing the global consensus ranking (often named aggregation ranking). To solve mid/large-scale problems, users should install the 'gurobi' optimiser (available from <https://www.gurobi.com/>).

Maintained by Bastian Pfeifer Maintainer. Last updated 1 years ago.

convex-optimization ranking-data signal-estimation

18.4 match 3 stars 4.18 score 1 scripts

dcourvoisier

doremi:Dynamics of Return to Equilibrium During Multiple Inputs

Provides models to fit the dynamics of a regulated system experiencing exogenous inputs. The underlying models use differential equations and linear mixed-effects regressions to estimate the coefficients of the equation. With them, the functions can provide an estimated signal. The package provides simulation and analysis functions and also print, summary, plot and predict methods, adapted to the function outputs, for easy implementation and presentation of results.

Maintained by Mongin Denis. Last updated 3 years ago.

16.9 match 4.48 score 25 scripts 1 dependents

bioc

bamsignals:Extract read count signals from bam files

This package allows to efficiently obtain count vectors from indexed bam files. It counts the number of reads in given genomic ranges and it computes reads profiles and coverage profiles. It also handles paired-end data.

Maintained by Johannes Helmuth. Last updated 5 months ago.

dataimport sequencing coverage alignment curl bzip2 xz-utils zlib cpp

8.4 match 15 stars 8.95 score 31 scripts 11 dependents

bioc

recountmethylation:Access and analyze public DNA methylation array data compilations

Resources for cross-study analyses of public DNAm array data from NCBI GEO repo, produced using Illumina's Infinium HumanMethylation450K (HM450K) and MethylationEPIC (EPIC) platforms. Provided functions enable download, summary, and filtering of large compilation files. Vignettes detail background about file formats, example analyses, and more. Note the disclaimer on package load and consult the main manuscripts for further info.

Maintained by Sean K Maden. Last updated 5 months ago.

dnamethylation epigenetics microarray methylationarray experimenthub

11.2 match 9 stars 6.28 score 9 scripts

bioc

plotgardener:Coordinate-Based Genomic Visualization Package for R

Coordinate-based genomic visualization package for R. It grants users the ability to programmatically produce complex, multi-paneled figures. Tailored for genomics, plotgardener allows users to visualize large complex genomic datasets and provides exquisite control over how plots are placed and arranged on a page.

Maintained by Nicole Kramer. Last updated 5 months ago.

visualization genomeannotation functionalgenomics genomeassembly hic cpp

6.8 match 308 stars 10.16 score 167 scripts 3 dependents

rstudio

keras3:R Interface to 'Keras'

Interface to 'Keras' <https://keras.io>, a high-level neural networks API. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both CPU and GPU devices.

Maintained by Tomasz Kalinowski. Last updated 4 days ago.

5.1 match 845 stars 13.57 score 264 scripts 2 dependents

bioc

pmp:Peak Matrix Processing and signal batch correction for metabolomics datasets

Methods and tools for (pre-)processing of metabolomics datasets (i.e. peak matrices), including filtering, normalisation, missing value imputation, scaling, and signal drift and batch effect correction methods. Filtering methods are based on: the fraction of missing values (across samples or features); Relative Standard Deviation (RSD) calculated from the Quality Control (QC) samples; the blank samples. Normalisation methods include Probabilistic Quotient Normalisation (PQN) and normalisation to total signal intensity. A unified user interface for several commonly used missing value imputation algorithms is also provided. Supported methods are: k-nearest neighbours (knn), random forests (rf), Bayesian PCA missing value estimator (bpca), mean or median value of the given feature and a constant small value. The generalised logarithm (glog) transformation algorithm is available to stabilise the variance across low and high intensity mass spectral features. Finally, this package provides an implementation of the Quality Control-Robust Spline Correction (QCRSC) algorithm for signal drift and batch effect correction of mass spectrometry-based datasets.

Maintained by Gavin Rhys Lloyd. Last updated 5 months ago.

massspectrometry metabolomics software qualitycontrol batcheffect

15.0 match 4.60 score 33 scripts

stephenslab

mashr:Multivariate Adaptive Shrinkage

Implements the multivariate adaptive shrinkage (mash) method of Urbut et al (2019) <DOI:10.1038/s41588-018-0268-8> for estimating and testing large numbers of effects in many conditions (or many outcomes). Mash takes an empirical Bayes approach to testing and effect estimation; it estimates patterns of similarity among conditions, then exploits these patterns to improve accuracy of the effect estimates. The core linear algebra is implemented in C++ for fast model fitting and posterior computation.

Maintained by Peter Carbonetto. Last updated 4 months ago.

openblas gsl cpp openmp

6.2 match 91 stars 11.04 score 624 scripts 3 dependents

bioc

extraChIPs:Additional functions for working with ChIP-Seq data

This package builds on existing tools and adds some simple but extremely useful capabilities for working wth ChIP-Seq data. The focus is on detecting differential binding windows/regions. One set of functions focusses on set-operations retaining mcols for GRanges objects, whilst another group of functions are to aid visualisation of results. Coercion to tibble objects is also implemented.

Maintained by Stevie Pederson. Last updated 16 days ago.

chipseq hic sequencing coverage

10.3 match 7 stars 6.67 score 25 scripts

bioc

ASpli:Analysis of Alternative Splicing Using RNA-Seq

Integrative pipeline for the analysis of alternative splicing using RNAseq.

Maintained by Ariel Chernomoretz. Last updated 5 months ago.

immunooncology geneexpression transcription alternativesplicing coverage differentialexpression differentialsplicing timecourse rnaseq genomeannotation sequencing alignment

12.5 match 5.33 score 45 scripts 1 dependents

mpierrejean

jointseg:Joint Segmentation of Multivariate (Copy Number) Signals

Methods for fast segmentation of multivariate signals into piecewise constant profiles and for generating realistic copy-number profiles. A typical application is the joint segmentation of total DNA copy numbers and allelic ratios obtained from Single Nucleotide Polymorphism (SNP) microarrays in cancer studies. The methods are described in Pierre-Jean, Rigaill and Neuvial (2015) <doi:10.1093/bib/bbu026>.

Maintained by Morgane Pierre-Jean. Last updated 6 years ago.

cpp

9.9 match 6 stars 6.50 score 44 scripts 2 dependents

bioc

MetaboSignal:MetaboSignal: a network-based approach to overlay and explore metabolic and signaling KEGG pathways

MetaboSignal is an R package that allows merging, analyzing and customizing metabolic and signaling KEGG pathways. It is a network-based approach designed to explore the topological relationship between genes (signaling- or enzymatic-genes) and metabolites, representing a powerful tool to investigate the genetic landscape and regulatory networks of metabolic phenotypes.

Maintained by Andrea Rodriguez-Martinez. Last updated 5 months ago.

graphandnetwork genesignaling genetarget network pathways kegg reactome software

12.9 match 4.90 score 8 scripts

bioc

graph:graph: A package to handle graph data structures

A package that implements some simple graph handling capabilities.

Maintained by Bioconductor Package Maintainer. Last updated 11 days ago.

graphandnetwork

5.3 match 11.78 score 764 scripts 342 dependents

bioc

MSstatsConvert:Import Data from Various Mass Spectrometry Signal Processing Tools to MSstats Format

MSstatsConvert provides tools for importing reports of Mass Spectrometry data processing tools into R format suitable for statistical analysis using the MSstats and MSstatsTMT packages.

Maintained by Mateusz Staniak. Last updated 3 months ago.

massspectrometry proteomics software dataimport qualitycontrol

9.6 match 6.37 score 25 scripts 7 dependents

bioc

seqsetvis:Set Based Visualizations for Next-Gen Sequencing Data

seqsetvis enables the visualization and analysis of sets of genomic sites in next gen sequencing data. Although seqsetvis was designed for the comparison of mulitple ChIP-seq samples, this package is domain-agnostic and allows the processing of multiple genomic coordinate files (bed-like files) and signal files (bigwig files pileups from bam file). seqsetvis has multiple functions for fetching data from regions into a tidy format for analysis in data.table or tidyverse and visualization via ggplot2.

Maintained by Joseph R Boyd. Last updated 3 months ago.

software chipseq multiplecomparison sequencing visualization

10.4 match 5.82 score 82 scripts

hneth

unikn:Graphical Elements of the University of Konstanz's Corporate Design

Define and use graphical elements of corporate design manuals in R. The 'unikn' package provides color functions (by defining dedicated colors and color palettes, and commands for finding, changing, viewing, and using them) and styled text elements (e.g., for marking, underlining, or plotting colored titles). The pre-defined range of colors and text decoration functions is based on the corporate design of the University of Konstanz <https://www.uni-konstanz.de/>, but can be adapted and extended for other purposes or institutions.

Maintained by Hansjoerg Neth. Last updated 3 months ago.

branding color color-palette colorscheme corporate-design palette text-decoration university-colors visual-identity

6.8 match 39 stars 8.82 score 156 scripts 2 dependents

signaturescience

rplanes:Plausibility Analysis of Epidemiological Signals

Provides functionality to prepare data and analyze plausibility of both forecasted and reported epidemiological signals. The functions implement a set of plausibility algorithms that are agnostic to geographic and time resolutions and are calculated independently then presented as a combined score.

Maintained by VP Nagraj. Last updated 8 months ago.

9.8 match 9 stars 6.03 score 7 scripts

r-lib

lifecycle:Manage the Life Cycle of your Package Functions

Manage the life cycle of your exported functions with shared conventions, documentation badges, and user-friendly deprecation warnings.

Maintained by Lionel Henry. Last updated 26 days ago.

3.8 match 95 stars 15.84 score 54 scripts 14k dependents

cran

Sequential:Exact Sequential Analysis for Poisson and Binomial Data

Functions to calculate exact critical values, statistical power, expected time to signal, and required sample sizes for performing exact sequential analysis. All these calculations can be done for either Poisson or binomial data, for continuous or group sequential analyses, and for different types of rejection boundaries. In case of group sequential analyses, the group sizes do not have to be specified in advance and the alpha spending can be arbitrarily settled.

Maintained by Ivair Ramos Silva. Last updated 5 months ago.

18.3 match 2 stars 3.24 score 38 scripts 1 dependents

cran

edfReader:Reading EDF(+) and BDF(+) Files

Reads European Data Format files EDF and EDF+, see <http://www.edfplus.info>, BioSemi Data Format files BDF, see <http://www.biosemi.com/faq/file_format.htm>, and BDF+ files, see <http://www.teuniz.net/edfbrowser/bdfplus%20format%20description.html>. The files are read in two steps: first the header is read and then the signals (using the header object as a parameter).

Maintained by Jan Vis. Last updated 6 years ago.

21.7 match 2.71 score 17 scripts 1 dependents

dankelley

oce:Analysis of Oceanographic Data

Supports the analysis of Oceanographic data, including 'ADCP' measurements, measurements made with 'argo' floats, 'CTD' measurements, sectional data, sea-level time series, coastline and topographic data, etc. Provides specialized functions for calculating seawater properties such as potential temperature in either the 'UNESCO' or 'TEOS-10' equation of state. Produces graphical displays that conform to the conventions of the Oceanographic literature. This package is discussed extensively by Kelley (2018) "Oceanographic Analysis with R" <doi:10.1007/978-1-4939-8844-0>.

Maintained by Dan Kelley. Last updated 2 days ago.

oceanography fortran cpp

3.8 match 146 stars 15.42 score 4.2k scripts 18 dependents

bioc

ChIPpeakAnno:Batch annotation of the peaks identified from either ChIP-seq, ChIP-chip experiments, or any experiments that result in large number of genomic interval data

The package encompasses a range of functions for identifying the closest gene, exon, miRNA, or custom features—such as highly conserved elements and user-supplied transcription factor binding sites. Additionally, users can retrieve sequences around the peaks and obtain enriched Gene Ontology (GO) or Pathway terms. In version 2.0.5 and beyond, new functionalities have been introduced. These include features for identifying peaks associated with bi-directional promoters along with summary statistics (peaksNearBDP), summarizing motif occurrences in peaks (summarizePatternInPeaks), and associating additional identifiers with annotated peaks or enrichedGO (addGeneIDs). The package integrates with various other packages such as biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest, and stat to enhance its analytical capabilities.

Maintained by Jianhong Ou. Last updated 2 months ago.

annotation chipseq chipchip

6.6 match 8.75 score 584 scripts 6 dependents

ips-lmu

wrassp:Interface to the 'ASSP' Library

A wrapper around Michel Scheffers's 'libassp' (<https://libassp.sourceforge.net/>). The 'libassp' (Advanced Speech Signal Processor) library aims at providing functionality for handling speech signal files in most common audio formats and for performing analyses common in phonetic science/speech science. This includes the calculation of formants, fundamental frequency, root mean square, auto correlation, a variety of spectral analyses, zero crossing rate, filtering etc. This wrapper provides R with a large subset of 'libassp's signal processing functions and provides them to the user in a (hopefully) user-friendly manner.

Maintained by Markus Jochim. Last updated 1 years ago.

7.5 match 24 stars 7.43 score 62 scripts 3 dependents

ltorgo

DMwR2:Functions and Data for the Second Edition of "Data Mining with R"

Functions and data accompanying the second edition of the book "Data Mining with R, learning with case studies" by Luis Torgo, published by CRC Press.

Maintained by Luis Torgo. Last updated 8 years ago.

7.5 match 27 stars 7.46 score 380 scripts 2 dependents

sysbiolab

PathwaySpace:Spatial Projection of Network Signals along Geodesic Paths

For a given graph containing vertices, edges, and a signal associated with the vertices, the 'PathwaySpace' package performs a convolution operation, which involves a weighted combination of neighboring vertices and their associated signals. The package then uses a decay function to project these signals, creating geodesic paths on a 2D-image space. 'PathwaySpace' could have various applications, such as visualizing and analyzing network data in a graphical format that highlights the relationships and signal strengths between vertices. It can be particularly useful for understanding the influence of signals through complex networks. By combining graph theory, signal processing, and visualization, the 'PathwaySpace' package provides a novel way of representing and analyzing graph data.

Maintained by Mauro Castro. Last updated 2 months ago.

bioinformatics biological-networks graph

11.5 match 2 stars 4.85 score 5 scripts

helske

KFAS:Kalman Filter and Smoother for Exponential Family State Space Models

State space modelling is an efficient and flexible framework for statistical inference of a broad class of time series and other data. KFAS includes computationally efficient functions for Kalman filtering, smoothing, forecasting, and simulation of multivariate exponential family state space models, with observations from Gaussian, Poisson, binomial, negative binomial, and gamma distributions. See the paper by Helske (2017) <doi:10.18637/jss.v078.i10> for details.

Maintained by Jouni Helske. Last updated 6 months ago.

dynamic-linear-model exponential-family fortran gaussian-models state-space time-series openblas

5.1 match 64 stars 10.97 score 242 scripts 16 dependents

vdakos

earlywarnings:Early Warning Signals for Critical Transitions in Time Series

The Early-Warning-Signals Toolbox provides methods for estimating statistical changes in time series that can be used for identifying nearby critical transitions.

Maintained by Vasilis Dakos. Last updated 2 years ago.

14.2 match 3.88 score 75 scripts

duncanobrien

EWSmethods:Forecasting Tipping Points at the Community Level

Rolling and expanding window approaches to assessing abundance based early warning signals, non-equilibrium resilience measures, and machine learning. See Dakos et al. (2012) <doi:10.1371/journal.pone.0041010>, Deb et al. (2022) <doi:10.1098/rsos.211475>, Drake and Griffen (2010) <doi:10.1038/nature09389>, Ushio et al. (2018) <doi:10.1038/nature25504> and Weinans et al. (2021) <doi:10.1038/s41598-021-87839-y> for methodological details. Graphical presentation of the outputs are also provided for clear and publishable figures. Visit the 'EWSmethods' website for more information, and tutorials.

Maintained by Duncan OBrien. Last updated 7 months ago.

9.9 match 8 stars 5.51 score 20 scripts

bioc

limma:Linear Models for Microarray and Omics Data

Data analysis, linear models and differential expression for omics data.

Maintained by Gordon Smyth. Last updated 6 days ago.

exonarray geneexpression transcription alternativesplicing differentialexpression differentialsplicing genesetenrichment dataimport bayesian clustering regression timecourse microarray micrornaarray mrnamicroarray onechannel proprietaryplatforms twochannel sequencing rnaseq batcheffect multiplecomparison normalization preprocessing qualitycontrol biomedicalinformatics cellbiology cheminformatics epigenetics functionalgenomics genetics immunooncology metabolomics proteomics systemsbiology transcriptomics

3.9 match 13.81 score 16k scripts 585 dependents

lcougnaud

nlcv:Nested Loop Cross Validation

Nested loop cross validation for classification purposes for misclassification error rate estimation. The package supports several methodologies for feature selection: random forest, Student t-test, limma, and provides an interface to the following classification methods in the 'MLInterfaces' package: linear, quadratic discriminant analyses, random forest, bagging, prediction analysis for microarray, generalized linear model, support vector machine (svm and ksvm). Visualizations to assess the quality of the classifier are included: plot of the ranks of the features, scores plot for a specific classification algorithm and number of features, misclassification rate for the different number of features and classification algorithms tested and ROC plot. For further details about the methodology, please check: Markus Ruschhaupt, Wolfgang Huber, Annemarie Poustka, and Ulrich Mansmann (2004) <doi:10.2202/1544-6115.1078>.

Maintained by Laure Cougnaud. Last updated 7 years ago.

26.5 match 2.00 score 8 scripts

tidymodels

embed:Extra Recipes for Encoding Predictors

Predictors can be converted to one or more numeric representations using a variety of methods. Effect encodings using simple generalized linear models <doi:10.48550/arXiv.1611.09477> or nonlinear models <doi:10.48550/arXiv.1604.06737> can be used. There are also functions for dimension reduction and other approaches.

Maintained by Emil Hvitfeldt. Last updated 2 months ago.

5.5 match 142 stars 9.35 score 1.1k scripts

bioc

SPIA:Signaling Pathway Impact Analysis (SPIA) using combined evidence of pathway over-representation and unusual signaling perturbations

This package implements the Signaling Pathway Impact Analysis (SPIA) which uses the information form a list of differentially expressed genes and their log fold changes together with signaling pathways topology, in order to identify the pathways most relevant to the condition under the study.

Maintained by Adi Laurentiu Tarca. Last updated 2 months ago.

microarray graphandnetwork

7.8 match 6.62 score 113 scripts 4 dependents

r-forge

PreProcess:Basic Functions for Pre-Processing Microarrays

Provides classes to pre-process microarray gene expression data as part of the OOMPA collection of packages described at <http://oompa.r-forge.r-project.org/>.

Maintained by Kevin R. Coombes. Last updated 1 months ago.

microarray preprocessing

10.1 match 5.03 score 30 scripts

animaltags

tagtools:Work with Data from High-Resolution Biologging Tags

High-resolution movement-sensor tags typically include accelerometers to measure body posture and sudden movements or changes in speed, magnetometers to measure direction of travel, and pressure sensors to measure dive depth in aquatic or marine animals. The sensors in these tags usually sample many times per second. Some tags include sensors for speed, turning rate (gyroscopes), and sound. This package provides software tools to facilitate calibration, processing, and analysis of such data. Tools are provided for: data import/export; calibration (from raw data to calibrated data in scientific units); visualization (for example, multi-panel time-series plots); data processing (such as event detection, calculation of derived metrics like jerk and dynamic acceleration, dive detection, and dive parameter calculation); and statistical analysis (for example, track reconstruction, a rotation test, and Mahalanobis distance analysis).

Maintained by Stacy DeRuiter. Last updated 9 months ago.

10.9 match 8 stars 4.62 score 26 scripts

r-lum

Luminescence:Comprehensive Luminescence Dating Data Analysis

A collection of various R functions for the purpose of Luminescence dating data analysis. This includes, amongst others, data import, export, application of age models, curve deconvolution, sequence analysis and plotting of equivalent dose distributions.

Maintained by Sebastian Kreutzer. Last updated 1 days ago.

bayesian-statistics data-science geochronology luminescence luminescence-dating open-science osl plotting radiofluorescence tl xsyg cpp

4.6 match 15 stars 10.77 score 178 scripts 8 dependents

eduardoarle

bRacatus:A Method to Estimate the Accuracy and Biogeographical Status of Georeferenced Biological Data

Automated assessment of accuracy and geographical status of georeferenced biological data. The methods rely on reference regions, namely checklists and range maps. Includes functions to obtain data from the Global Biodiversity Information Facility <https://www.gbif.org/> and from the Global Inventory of Floras and Traits <https://gift.uni-goettingen.de/home>. Alternatively, the user can input their own data. Furthermore, provides easy visualisation of the data and the results through the plotting functions. Especially suited for large datasets. The reference for the methodology is: Arlé et al. (under review).

Maintained by Eduardo Arlé. Last updated 11 months ago.

12.0 match 8 stars 4.08 score 4 scripts

stefanocoretta

rticulate:Articulatory Data Processing in R

A tool for processing Articulate Assistant Advanced™ (AAA) ultrasound tongue imaging data and Carstens AG500/1 electro-magnetic articulographic data.

Maintained by Stefano Coretta. Last updated 25 days ago.

phonetics software tongue-image ultrasound ultrasound-tongue-imaging

8.3 match 5 stars 5.88 score 17 scripts

eu-ecdc

epitweetr:Early Detection of Public Health Threats from 'Twitter' Data

It allows you to automatically monitor trends of tweets by time, place and topic aiming at detecting public health threats early through the detection of signals (e.g. an unusual increase in the number of tweets). It was designed to focus on infectious diseases, and it can be extended to all hazards or other fields of study by modifying the topics and keywords. More information is available in the 'epitweetr' peer-review publication (doi:10.2807/1560-7917.ES.2022.27.39.2200177).

Maintained by Laura Espinosa. Last updated 1 years ago.

early-warning-systems epidemic-surveillance lucene machine-learning signal-detection spark twitter

8.0 match 56 stars 5.98 score 86 scripts

bioc

mirIntegrator:Integrating microRNA expression into signaling pathways for pathway analysis

Tools for augmenting signaling pathways to perform pathway analysis of microRNA and mRNA expression levels.

Maintained by Diana Diaz. Last updated 5 months ago.

network microarray graphandnetwork pathways kegg

14.4 match 1 stars 3.30 score 2 scripts

spkaluzny

splusTimeSeries:Time Series from 'S-PLUS'

A collection of classes and methods for working with indexed rectangular data. The index values can be calendar (timeSeries class) or numeric (signalSeries class). Methods are included for aggregation, alignment, merging, and summaries. The code was originally available in 'S-PLUS'.

Maintained by Stephen Kaluzny. Last updated 6 months ago.

data-structures time-series

11.9 match 3.95 score 20 scripts 1 dependents

gmgeorg

ForeCA:Forecastable Component Analysis

Implementation of Forecastable Component Analysis ('ForeCA'), including main algorithms and auxiliary function (summary, plotting, etc.) to apply 'ForeCA' to multivariate time series data. 'ForeCA' is a novel dimension reduction (DR) technique for temporally dependent signals. Contrary to other popular DR methods, such as 'PCA' or 'ICA', 'ForeCA' takes time dependency explicitly into account and searches for the most ''forecastable'' signal. The measure of forecastability is based on the Shannon entropy of the spectral density of the transformed signal.

Maintained by Georg M. Goerg. Last updated 5 years ago.

blind-source-separation dimensionality-reduction forecasting multivariate-timeseries signal-processing spectrum time-series time-series-analysis

8.4 match 15 stars 5.47 score 39 scripts

convexfi

intradayModel:Modeling and Forecasting Financial Intraday Signals

Models, analyzes, and forecasts financial intraday signals. This package currently supports a univariate state-space model for intraday trading volume provided by Chen (2016) <doi:10.2139/ssrn.3101695>.

Maintained by Daniel P. Palomar. Last updated 2 years ago.

8.2 match 14 stars 5.58 score 27 scripts

bioc

gCrisprTools:Suite of Functions for Pooled Crispr Screen QC and Analysis

Set of tools for evaluating pooled high-throughput screening experiments, typically employing CRISPR/Cas9 or shRNA expression cassettes. Contains methods for interrogating library and cassette behavior within an experiment, identifying differentially abundant cassettes, aggregating signals to identify candidate targets for empirical validation, hypothesis testing, and comprehensive reporting. Version 2.0 extends these applications to include a variety of tools for contextualizing and integrating signals across many experiments, incorporates extended signal enrichment methodologies via the "sparrow" package, and streamlines many formal requirements to aid in interpretablity.

Maintained by Russell Bainer. Last updated 5 months ago.

immunooncology crispr pooledscreens experimentaldesign biomedicalinformatics cellbiology functionalgenomics pharmacogenomics pharmacogenetics systemsbiology differentialexpression genesetenrichment genetics multiplecomparison normalization preprocessing qualitycontrol rnaseq regression software visualization

9.5 match 4.78 score 8 scripts

opendendro

dplR:Dendrochronology Program Library in R

Perform tree-ring analyses such as detrending, chronology building, and cross dating. Read and write standard file formats used in dendrochronology.

Maintained by Andy Bunn. Last updated 19 days ago.

fortran

3.9 match 39 stars 11.71 score 546 scripts 26 dependents

bioc

faers:R interface for FDA Adverse Event Reporting System

The FDA Adverse Event Reporting System (FAERS) is a database used for the spontaneous reporting of adverse events and medication errors related to human drugs and therapeutic biological products. faers pacakge serves as the interface between the FAERS database and R. Furthermore, faers pacakge offers a standardized approach for performing pharmacovigilance analysis.

Maintained by Yun Peng. Last updated 5 months ago.

software dataimport biomedicalinformatics pharmacogenomics adverse-events drug-safety faers faers-procedure pharmacovigilance signal-detection

7.5 match 20 stars 5.95 score 5 scripts

gitumino

fitPoly:Genotype Calling for Bi-Allelic Marker Assays

Genotyping assays for bi-allelic markers (e.g. SNPs) produce signal intensities for the two alleles. 'fitPoly' assigns genotypes (allele dosages) to a collection of polyploid samples based on these signal intensities. 'fitPoly' replaces the older package 'fitTetra' that was limited (a.o.) to only tetraploid populations whereas 'fitPoly' accepts any ploidy level. Reference: Voorrips RE, Gort G, Vosman B (2011) <doi:10.1186/1471-2105-12-172>. New functions added on conversion of data from SNP array software formats, drawing of XY-scatterplots with or without genotype colors, checking against expected F1 segregation patterns, comparing results from two different assays (probes) for the same SNP, recovery from a saveMarkerModels() crash.

Maintained by Giorgio Tumino. Last updated 1 months ago.

10.8 match 4.13 score 15 scripts

cogdisreslab

KRSA:KRSA: Kinome Random Sampling Analyzer

The goal of this package is to analyze the PamChip data and identify the changes in the active kinome. The package can preprocess the PamChip data output from BioNavigator and use Random Sampling and Permutation Analysis to identify upstream kinases. Additionally, this package provides a set of useful visualizations for the PamChip data.

Maintained by Ali Sajid Imami. Last updated 11 days ago.

kinase phosphatases pamchip kinome random sampling permutation analysis

10.0 match 4 stars 4.42 score 49 scripts

dsstoffer

astsa:Applied Statistical Time Series Analysis

Contains data sets and scripts for analyzing time series in both the frequency and time domains including state space modeling as well as supporting the texts Time Series Analysis and Its Applications: With R Examples (5th ed), by R.H. Shumway and D.S. Stoffer. Springer Texts in Statistics, 2025, <https://link.springer.com/book/9783031705830>, and Time Series: A Data Analysis Approach Using R. Chapman-Hall, 2019, <DOI:10.1201/9780429273285>.

Maintained by David Stoffer. Last updated 2 months ago.

5.6 match 7 stars 7.88 score 2.2k scripts 8 dependents

hmorlon

RPANDA:Phylogenetic ANalyses of DiversificAtion

Implements macroevolutionary analyses on phylogenetic trees. See Morlon et al. (2010) <DOI:10.1371/journal.pbio.1000493>, Morlon et al. (2011) <DOI:10.1073/pnas.1102543108>, Condamine et al. (2013) <DOI:10.1111/ele.12062>, Morlon et al. (2014) <DOI:10.1111/ele.12251>, Manceau et al. (2015) <DOI:10.1111/ele.12415>, Lewitus & Morlon (2016) <DOI:10.1093/sysbio/syv116>, Drury et al. (2016) <DOI:10.1093/sysbio/syw020>, Manceau et al. (2016) <DOI:10.1093/sysbio/syw115>, Morlon et al. (2016) <DOI:10.1111/2041-210X.12526>, Clavel & Morlon (2017) <DOI:10.1073/pnas.1606868114>, Drury et al. (2017) <DOI:10.1093/sysbio/syx079>, Lewitus & Morlon (2017) <DOI:10.1093/sysbio/syx095>, Drury et al. (2018) <DOI:10.1371/journal.pbio.2003563>, Clavel et al. (2019) <DOI:10.1093/sysbio/syy045>, Maliet et al. (2019) <DOI:10.1038/s41559-019-0908-0>, Billaud et al. (2019) <DOI:10.1093/sysbio/syz057>, Lewitus et al. (2019) <DOI:10.1093/sysbio/syz061>, Aristide & Morlon (2019) <DOI:10.1111/ele.13385>, Maliet et al. (2020) <DOI:10.1111/ele.13592>, Drury et al. (2021) <DOI:10.1371/journal.pbio.3001270>, Perez-Lamarque & Morlon (2022) <DOI:10.1111/mec.16478>, Perez-Lamarque et al. (2022) <DOI:10.1101/2021.08.30.458192>, Mazet et al. (2023) <DOI:10.1111/2041-210X.14195>, Drury et al. (2024) <DOI:10.1016/j.cub.2023.12.055>.

Maintained by Hélène Morlon. Last updated 2 months ago.

5.1 match 24 stars 8.50 score 255 scripts

yelleknek

MBESS:The MBESS R Package

Implements methods that are useful in designing research studies and analyzing data, with particular emphasis on methods that are developed for or used within the behavioral, educational, and social sciences (broadly defined). That being said, many of the methods implemented within MBESS are applicable to a wide variety of disciplines. MBESS has a suite of functions for a variety of related topics, such as effect sizes, confidence intervals for effect sizes (including standardized effect sizes and noncentral effect sizes), sample size planning (from the accuracy in parameter estimation [AIPE], power analytic, equivalence, and minimum-risk point estimation perspectives), mediation analysis, various properties of distributions, and a variety of utility functions. MBESS (pronounced 'em-bes') was originally an acronym for 'Methods for the Behavioral, Educational, and Social Sciences,' but MBESS became more general and now contains methods applicable and used in a wide variety of fields and is an orphan acronym, in the sense that what was an acronym is now literally its name. MBESS has greatly benefited from others, see <https://www3.nd.edu/~kkelley/site/MBESS.html> for a detailed list of those that have contributed and other details.

Maintained by Ken Kelley. Last updated 1 years ago.

5.2 match 2 stars 8.21 score 274 scripts 23 dependents

jaromilfrossard

permuco:Permutation Tests for Regression, (Repeated Measures) ANOVA/ANCOVA and Comparison of Signals

Functions to compute p-values based on permutation tests. Regression, ANOVA and ANCOVA, omnibus F-tests, marginal unilateral and bilateral t-tests are available. Several methods to handle nuisance variables are implemented (Kherad-Pajouh, S., & Renaud, O. (2010) <doi:10.1016/j.csda.2010.02.015> ; Kherad-Pajouh, S., & Renaud, O. (2014) <doi:10.1007/s00362-014-0617-3> ; Winkler, A. M., Ridgway, G. R., Webster, M. A., Smith, S. M., & Nichols, T. E. (2014) <doi:10.1016/j.neuroimage.2014.01.060>). An extension for the comparison of signals issued from experimental conditions (e.g. EEG/ERP signals) is provided. Several corrections for multiple testing are possible, including the cluster-mass statistic (Maris, E., & Oostenveld, R. (2007) <doi:10.1016/j.jneumeth.2007.03.024>) and the threshold-free cluster enhancement (Smith, S. M., & Nichols, T. E. (2009) <doi:10.1016/j.neuroimage.2008.03.061>).

Maintained by Jaromil Frossard. Last updated 7 months ago.

cpp

6.5 match 13 stars 6.57 score 81 scripts

bioc

GeneStructureTools:Tools for spliced gene structure manipulation and analysis

GeneStructureTools can be used to create in silico alternative splicing events, and analyse potential effects this has on functional gene products.

Maintained by Beth Signal. Last updated 5 months ago.

immunooncology software differentialsplicing functionalprediction transcriptomics alternativesplicing rnaseq

9.8 match 4.32 score 21 scripts

wanchanglin

mt:Metabolomics Data Analysis Toolbox

Functions for metabolomics data analysis: data preprocessing, orthogonal signal correction, PCA analysis, PCA-DA analysis, PLS-DA analysis, classification, feature selection, correlation analysis, data visualisation and re-sampling strategies.

Maintained by Wanchang Lin. Last updated 1 years ago.

9.2 match 3 stars 4.57 score 50 scripts

bioc

profileplyr:Visualization and annotation of read signal over genomic ranges with profileplyr

Quick and straightforward visualization of read signal over genomic intervals is key for generating hypotheses from sequencing data sets (e.g. ChIP-seq, ATAC-seq, bisulfite/methyl-seq). Many tools both inside and outside of R and Bioconductor are available to explore these types of data, and they typically start with a bigWig or BAM file and end with some representation of the signal (e.g. heatmap). profileplyr leverages many Bioconductor tools to allow for both flexibility and additional functionality in workflows that end with visualization of the read signal.

Maintained by Tom Carroll. Last updated 5 months ago.

chipseq dataimport sequencing chiponchip coverage

10.2 match 4.03 score 54 scripts

tushiqi

MAnorm2:Tools for Normalizing and Comparing ChIP-seq Samples

Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the premier technology for profiling genome-wide localization of chromatin-binding proteins, including transcription factors and histones with various modifications. This package provides a robust method for normalizing ChIP-seq signals across individual samples or groups of samples. It also designs a self-contained system of statistical models for calling differential ChIP-seq signals between two or more biological conditions as well as for calling hypervariable ChIP-seq signals across samples. Refer to Tu et al. (2021) <doi:10.1101/gr.262675.120> and Chen et al. (2022) <doi:10.1186/s13059-022-02627-9> for associated statistical details.

Maintained by Shiqi Tu. Last updated 2 years ago.

chip-seq differential-analysis empirical-bayes winsorize-values

7.5 match 32 stars 5.48 score 19 scripts

smac-group

wv:Wavelet Variance

Provides a series of tools to compute and plot quantities related to classical and robust wavelet variance for time series and regular lattices. More details can be found, for example, in Serroukh, A., Walden, A.T., & Percival, D.B. (2000) <doi:10.2307/2669537> and Guerrier, S. & Molinari, R. (2016) <arXiv:1607.05858>.

Maintained by Stéphane Guerrier. Last updated 2 years ago.

signal-processing time-series wavelet-variance openblas cpp

7.5 match 17 stars 5.43 score 15 scripts 1 dependents

mlthom

cogirt:Cognitive Testing Using Item Response Theory

Psychometrically analyze latent individual differences related to tasks, interventions, or maturational/aging effects in the context of experimental or longitudinal cognitive research using methods first described by Thomas et al. (2020) <doi:10.1177/0013164420919898>.

Maintained by Michael Thomas. Last updated 1 months ago.

10.0 match 4.00 score 2 scripts

bioc

CellNOptR:Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data

This package does optimisation of boolean logic networks of signalling pathways based on a previous knowledge network and a set of data upon perturbation of the nodes in the network.

Maintained by Attila Gabor. Last updated 5 months ago.

cellbasedassays cellbiology proteomics pathways network timecourse immunooncology

5.9 match 6.72 score 98 scripts 6 dependents

nicholasjclark

mvgam:Multivariate (Dynamic) Generalized Additive Models

Fit Bayesian Dynamic Generalized Additive Models to multivariate observations. Users can build nonlinear State-Space models that can incorporate semiparametric effects in observation and process components, using a wide range of observation families. Estimation is performed using Markov Chain Monte Carlo with Hamiltonian Monte Carlo in the software 'Stan'. References: Clark & Wells (2023) <doi:10.1111/2041-210X.13974>.

Maintained by Nicholas J Clark. Last updated 2 hours ago.

bayesian-statistics dynamic-factor-models ecological-modelling forecasting gaussian-process generalised-additive-models generalized-additive-models joint-species-distribution-modelling multilevel-models multivariate-timeseries stan time-series-analysis timeseries vector-autoregression vectorautoregression cpp

4.0 match 139 stars 9.85 score 117 scripts

dkimstatlab

GSD:Graph Signal Decomposition

Graph signals residing on the vertices of a graph have recently gained prominence in research in various fields. Many methodologies have been proposed to analyze graph signals by adapting classical signal processing tools. Recently, several notable graph signal decomposition methods have been proposed, which include graph Fourier decomposition based on graph Fourier transform, graph empirical mode decomposition, and statistical graph empirical mode decomposition. This package efficiently implements multiscale analysis applicable to various fields, and offers an effective tool for visualizing and decomposing graph signals. For the detailed methodology, see Ortega et al. (2018) <doi:10.1109/JPROC.2018.2820126>, Shuman et al. (2013) <doi:10.1109/MSP.2012.2235192>, Tremblay et al. (2014) <https://www.eurasip.org/Proceedings/Eusipco/Eusipco2014/HTML/papers/1569922141.pdf>, and Cho et al. (2024) "Statistical graph empirical mode decomposition by graph denoising and boundary treatment".

Maintained by Donghoh Kim. Last updated 1 years ago.

14.1 match 2.70 score

welch-lab

cytosignal:What the Package Does (One Line, Title Case)

What the package does (one paragraph).

Maintained by Jialin Liu. Last updated 6 days ago.

openblas cpp

6.3 match 16 stars 5.95 score 6 scripts

adafede

cascade:Contextualizing untargeted Annotation with Semi-quantitative Charged Aerosol Detection for pertinent characterization of natural Extracts

This package provides the infrastructure to perform Automated Composition Assessment of Natural Extracts.

Maintained by Adriano Rutz. Last updated 11 days ago.

metabolite annotation charged aerosol detector semi-quantitative natural products computational metabolomics specialized metabolome

6.5 match 2 stars 5.74 score 40 scripts 1 dependents

bioc

bnem:Training of logical models from indirect measurements of perturbation experiments

bnem combines the use of indirect measurements of Nested Effects Models (package mnem) with the Boolean networks of CellNOptR. Perturbation experiments of signalling nodes in cells are analysed for their effect on the global gene expression profile. Those profiles give evidence for the Boolean regulation of down-stream nodes in the network, e.g., whether two parents activate their child independently (OR-gate) or jointly (AND-gate).

Maintained by Martin Pirkl. Last updated 5 months ago.

pathways systemsbiology networkinference network geneexpression generegulation preprocessing

8.1 match 2 stars 4.60 score 5 scripts

bioc

CNORode:ODE add-on to CellNOptR

Logic based ordinary differential equation (ODE) add-on to CellNOptR.

Maintained by Attila Gabor. Last updated 5 months ago.

immunooncology cellbasedassays cellbiology proteomics bioinformatics timecourse

6.1 match 6.05 score 37 scripts 1 dependents

branchlab

metasnf:Meta Clustering with Similarity Network Fusion

Framework to facilitate patient subtyping with similarity network fusion and meta clustering. The similarity network fusion (SNF) algorithm was introduced by Wang et al. (2014) in <doi:10.1038/nmeth.2810>. SNF is a data integration approach that can transform high-dimensional and diverse data types into a single similarity network suitable for clustering with minimal loss of information from each initial data source. The meta clustering approach was introduced by Caruana et al. (2006) in <doi:10.1109/ICDM.2006.103>. Meta clustering involves generating a wide range of cluster solutions by adjusting clustering hyperparameters, then clustering the solutions themselves into a manageable number of qualitatively similar solutions, and finally characterizing representative solutions to find ones that are best for the user's specific context. This package provides a framework to easily transform multi-modal data into a wide range of similarity network fusion-derived cluster solutions as well as to visualize, characterize, and validate those solutions. Core package functionality includes easy customization of distance metrics, clustering algorithms, and SNF hyperparameters to generate diverse clustering solutions; calculation and plotting of associations between features, between patients, and between cluster solutions; and standard cluster validation approaches including resampled measures of cluster stability, standard metrics of cluster quality, and label propagation to evaluate generalizability in unseen data. Associated vignettes guide the user through using the package to identify patient subtypes while adhering to best practices for unsupervised learning.

Maintained by Prashanth S Velayudhan. Last updated 5 days ago.

bioinformatics clustering metaclustering snf

4.5 match 8 stars 8.21 score 30 scripts

r-forge

RHRV:Heart Rate Variability Analysis of ECG Data

Allows users to import data files containing heartbeat positions in the most broadly used formats, to remove outliers or points with unacceptable physiological values present in the time series, to plot HRV data, and to perform time domain, frequency domain and nonlinear HRV analysis. See Garcia et al. (2017) <DOI:10.1007/978-3-319-65355-6>.

Maintained by Leandro Rodriguez-Linares. Last updated 6 months ago.

5.4 match 6.79 score 63 scripts 1 dependents

romanflury

mrbsizeR:Scale Space Multiresolution Analysis of Random Signals

A method for the multiresolution analysis of spatial fields and images to capture scale-dependent features. mrbsizeR is based on scale space smoothing and uses differences of smooths at neighbouring scales for finding features on different scales. To infer which of the captured features are credible, Bayesian analysis is used. The scale space multiresolution analysis has three steps: (1) Bayesian signal reconstruction. (2) Using differences of smooths, scale-dependent features of the reconstructed signal can be found. (3) Posterior credibility analysis of the differences of smooths created. The method has first been proposed by Holmstrom, Pasanen, Furrer, Sain (2011) <DOI:10.1016/j.csda.2011.04.011>. Matlab code is available under <http://cc.oulu.fi/~lpasanen/MRBSiZer/>.

Maintained by Roman Flury. Last updated 5 years ago.

cpp

8.6 match 1 stars 4.22 score 33 scripts

bioc

GenomicDistributions:GenomicDistributions: fast analysis of genomic intervals with Bioconductor

If you have a set of genomic ranges, this package can help you with visualization and comparison. It produces several kinds of plots, for example: Chromosome distribution plots, which visualize how your regions are distributed over chromosomes; feature distance distribution plots, which visualizes how your regions are distributed relative to a feature of interest, like Transcription Start Sites (TSSs); genomic partition plots, which visualize how your regions overlap given genomic features such as promoters, introns, exons, or intergenic regions. It also makes it easy to compare one set of ranges to another.

Maintained by Kristyna Kupkova. Last updated 5 months ago.

software genomeannotation genomeassembly datarepresentation sequencing coverage functionalgenomics visualization

4.9 match 26 stars 7.44 score 25 scripts

wviechtb

metadat:Meta-Analysis Datasets

A collection of meta-analysis datasets for teaching purposes, illustrating/testing meta-analytic methods, and validating published analyses.

Maintained by Wolfgang Viechtbauer. Last updated 2 days ago.

dataset datasets meta-analysis

3.4 match 30 stars 10.54 score 65 scripts 93 dependents

animint

animint2:Animated Interactive Grammar of Graphics

Functions are provided for defining animated, interactive data visualizations in R code, and rendering on a web page. The 2018 Journal of Computational and Graphical Statistics paper, <doi:10.1080/10618600.2018.1513367> describes the concepts implemented.

Maintained by Toby Hocking. Last updated 28 days ago.

4.0 match 64 stars 8.87 score 173 scripts

bioc

branchpointer:Prediction of intronic splicing branchpoints

Predicts branchpoint probability for sites in intronic branchpoint windows. Queries can be supplied as intronic regions; or to evaluate the effects of mutations, SNPs.

Maintained by Beth Signal. Last updated 5 months ago.

software genomeannotation genomicvariation motifannotation

9.8 match 3.62 score 21 scripts

yulab-smu

shinyTempSignal:Explore Temporal and Other Phylogenetic Signals

Sequences sampled at different time points can be used to infer molecular phylogenies on natural time scales, but if the sequences records inaccurate sampling times, that are not the actual sampling times, then it will affect the molecular phylogenetic analysis. This shiny application helps exploring temporal characteristics of the evolutionary trees through linear regression analysis and with the ability to identify and remove incorrect labels. The method was extended to support exploring other phylogenetic signals under strict and relaxed models.

Maintained by Guangchuang Yu. Last updated 1 years ago.

molecular-clock phylogenetics shiny-app

6.3 match 9 stars 5.56 score 7 scripts

roaldarbol

animovement:An R toolbox for analysing animal movement across space and time

An R toolbox for analysing animal movement across space and time.

Maintained by Mikkel Roald-Arbøl. Last updated 2 months ago.

animal-behaviour animal-movement neuroethology neuroscience

7.1 match 10 stars 4.81 score 8 scripts

bioc

statTarget:Statistical Analysis of Molecular Profiles

A streamlined tool provides a graphical user interface for quality control based signal drift correction (QC-RFSC), integration of data from multi-batch MS-based experiments, and the comprehensive statistical analysis in metabolomics and proteomics.

Maintained by Hemi Luan. Last updated 5 months ago.

immunooncology metabolomics proteomics machine learning lipidomics massspectrometry qualitycontrol normalization qc-rfsc combat differentialexpression batcheffect visualization multiplecomparison preprocessing software

5.9 match 5.64 score 24 scripts

cran

cusum:Cumulative Sum (CUSUM) Charts for Monitoring of Hospital Performance

Provides functions for constructing and evaluating CUSUM charts and RA-CUSUM charts with focus on false signal probability.

Maintained by Lena Hubig. Last updated 5 years ago.

cpp

8.7 match 3.81 score 16 scripts

r-lib

cli:Helpers for Developing Command Line Interfaces

A suite of tools to build attractive command line interfaces ('CLIs'), from semantic elements: headings, lists, alerts, paragraphs, etc. Supports custom themes via a 'CSS'-like language. It also contains a number of lower level 'CLI' elements: rules, boxes, trees, and 'Unicode' symbols with 'ASCII' alternatives. It support ANSI colors and text styles as well.

Maintained by Gábor Csárdi. Last updated 2 days ago.

cli

1.7 match 664 stars 19.33 score 1.4k scripts 14k dependents

manuelrausch

statConfR:Models of Decision Confidence and Measures of Metacognition

Provides fitting functions and other tools for decision confidence and metacognition researchers, including meta-d'/d', often considered to be the gold standard to measure metacognitive efficiency, and information-theoretic measures of metacognition. Also allows to fit several static models of decision making and confidence.

Maintained by Manuel Rausch. Last updated 13 days ago.

cognitive-modeling information-theory metacognition signal-detection-theory

6.7 match 5 stars 4.93 score 8 scripts

ropensci

ohun:Optimizing Acoustic Signal Detection

Facilitates the automatic detection of acoustic signals, providing functions to diagnose and optimize the performance of detection routines. Detections from other software can also be explored and optimized. This package has been peer-reviewed by rOpenSci. Araya-Salas et al. (2022) <doi:10.1101/2022.12.13.520253>.

Maintained by Marcelo Araya-Salas. Last updated 5 months ago.

audio-processing bioacoustics sound-event-detection spectrogram streamline-analysis

4.8 match 14 stars 6.78 score 24 scripts 1 dependents

ocean-tracking-network

glatos:A package for the Great Lakes Acoustic Telemetry Observation System

Functions useful to members of the Great Lakes Acoustic Telemetry Observation System https://glatos.glos.us; many more broadly relevant to simulating, processing, analysing, and visualizing acoustic telemetry data.

Maintained by Christopher Holbrook. Last updated 6 months ago.

5.0 match 10 stars 6.38 score 112 scripts

alanarnholt

BSDA:Basic Statistics and Data Analysis

Data sets for book "Basic Statistics and Data Analysis" by Larry J. Kitchens.

Maintained by Alan T. Arnholt. Last updated 2 years ago.

3.5 match 7 stars 9.11 score 1.3k scripts 6 dependents

michbur

signalHsmm:Predict Presence of Signal Peptides

Predicts the presence of signal peptides in eukaryotic protein using hidden semi-Markov models. The implemented algorithm can be accessed from both the command line and GUI.

Maintained by Michal Burdukiewicz. Last updated 5 years ago.

cpp

9.0 match 2 stars 3.48 score 7 scripts

pachadotdev

cpp11armadillo:An 'Armadillo' Interface

Provides function declarations and inline function definitions that facilitate communication between R and the 'Armadillo' 'C++' library for linear algebra and scientific computing. This implementation is detailed in Vargas Sepulveda and Schneider Malamud (2024) <doi:10.48550/arXiv.2408.11074>.

Maintained by Mauricio Vargas Sepulveda. Last updated 26 days ago.

armadillo cpp cpp11 hacktoberfest linear-algebra

3.3 match 9 stars 9.14 score 1 scripts 16 dependents

bioc

ComplexHeatmap:Make Complex Heatmaps

Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. Here the ComplexHeatmap package provides a highly flexible way to arrange multiple heatmaps and supports various annotation graphics.

Maintained by Zuguang Gu. Last updated 5 months ago.

software visualization sequencing clustering complex-heatmaps heatmap

1.8 match 1.3k stars 16.93 score 16k scripts 151 dependents

bioc

BiocParallel:Bioconductor facilities for parallel evaluation

This package provides modified versions and novel implementation of functions for parallel evaluation, tailored to use with Bioconductor objects.

Maintained by Martin Morgan. Last updated 26 days ago.

infrastructure bioconductor-package core-package u24ca289073 cpp

1.8 match 67 stars 17.40 score 7.3k scripts 1.1k dependents

joshuaulrich

quantmod:Quantitative Financial Modelling Framework

Specify, build, trade, and analyse quantitative financial trading strategies.

Maintained by Joshua M. Ulrich. Last updated 14 days ago.

algorithmic-trading charting data-import finance time-series

1.9 match 839 stars 16.17 score 8.1k scripts 343 dependents

joshuaulrich

TTR:Technical Trading Rules

A collection of over 50 technical indicators for creating technical trading rules. The package also provides fast implementations of common rolling-window functions, and several volatility calculations.

Maintained by Joshua Ulrich. Last updated 1 years ago.

algorithmic-trading finance technical-analysis

2.0 match 338 stars 15.11 score 2.8k scripts 359 dependents

emmanuelparadis

ape:Analyses of Phylogenetics and Evolution

Functions for reading, writing, plotting, and manipulating phylogenetic trees, analyses of comparative data in a phylogenetic framework, ancestral character analyses, analyses of diversification and macroevolution, computing distances from DNA sequences, reading and writing nucleotide sequences as well as importing from BioConductor, and several tools such as Mantel's test, generalized skyline plots, graphical exploration of phylogenetic data (alex, trex, kronoviz), estimation of absolute evolutionary rates and clock-like trees using mean path lengths and penalized likelihood, dating trees with non-contemporaneous sequences, translating DNA into AA sequences, and assessing sequence alignments. Phylogeny estimation can be done with the NJ, BIONJ, ME, MVR, SDM, and triangle methods, and several methods handling incomplete distance matrices (NJ*, BIONJ*, MVR*, and the corresponding triangle method). Some functions call external applications (PhyML, Clustal, T-Coffee, Muscle) whose results are returned into R.

Maintained by Emmanuel Paradis. Last updated 16 hours ago.

openblas cpp

1.8 match 64 stars 17.22 score 13k scripts 599 dependents

martakarass

adept:Adaptive Empirical Pattern Transformation

Designed for optimal use in performing fast, accurate walking strides segmentation from high-density data collected from a wearable accelerometer worn during continuous walking activity.

Maintained by Marta Karas. Last updated 4 years ago.

5.6 match 7 stars 5.35 score 16 scripts

agleontyev

SSRTcalc:Easy SSRT Calculation

This is a collection of functions to calculate stop-signal reaction time (SSRT). Includes functions for both "integration" and "mean" methods; both fixed and adaptive stop-signal delays are supported (see appropriate functions). Calculation is based on Verbruggen et al. (2019) <doi:10.7554/eLife.46323.001> and Verbruggen et al. (2013) <doi:10.1177/0956797612457390>.

Maintained by Anton Leontyev. Last updated 3 months ago.

11.1 match 2.70 score

stefanodamato

FVDDPpkg:Implement Fleming-Viot-Dependent Dirichlet Processes

A Bayesian Nonparametric model for the study of time-evolving frequencies, which has become renowned in the study of population genetics. The model consists of a Hidden Markov Model (HMM) in which the latent signal is a distribution-valued stochastic process that takes the form of a finite mixture of Dirichlet Processes, indexed by vectors that count how many times each value is observed in the population. The package implements methodologies presented in Ascolani, Lijoi and Ruggiero (2021) <doi:10.1214/20-BA1206> and Ascolani, Lijoi and Ruggiero (2023) <doi:10.3150/22-BEJ1504> that make it possible to study the process at the time of data collection or to predict its evolution in future or in the past.

Maintained by Stefano Damato. Last updated 8 months ago.

cpp

7.4 match 4.00 score 1 scripts

bioc

SingleCellSignalR:Cell Signalling Using Single Cell RNAseq Data Analysis

Allows single cell RNA seq data analysis, clustering, creates internal network and infers cell-cell interactions.

Maintained by Jacques Colinge Developer. Last updated 5 months ago.

singlecell network clustering rnaseq classification

5.1 match 5.87 score 35 scripts 1 dependents

tengmcing

autovi:Auto Visual Inference with Computer Vision Models

Provides automated visual inference of residual plots using computer vision models, facilitating diagnostic checks for classical normal linear regression models.

Maintained by Weihao Li. Last updated 4 months ago.

7.2 match 1 stars 4.13 score 16 scripts

gangwug

MetaCycle:Evaluate Periodicity in Large Scale Data

There are two functions-meta2d and meta3d for detecting rhythmic signals from time-series datasets. For analyzing time-series datasets without individual information, 'meta2d' is suggested, which could incorporates multiple methods from ARSER, JTK_CYCLE and Lomb-Scargle in the detection of interested rhythms. For analyzing time-series datasets with individual information, 'meta3d' is suggested, which takes use of any one of these three methods to analyze time-series data individual by individual and gives out integrated values based on analysis result of each individual.

Maintained by Gang Wu. Last updated 2 years ago.

3.9 match 26 stars 7.60 score 51 scripts 1 dependents

dirkmittelstrass

OSLdecomposition:Signal Component Analysis for Optically Stimulated Luminescence

Function library for the identification and separation of exponentially decaying signal components in continuous-wave optically stimulated luminescence measurements. A special emphasis is laid on luminescence dating with quartz, which is known for systematic errors due to signal components with unequal physical behaviour. Also, this package enables an easy to use signal decomposition of data sets imported and analysed with the R package 'Luminescence'. This includes the optional automatic creation of HTML reports. Further information and tutorials can be found at <https://luminescence.de>.

Maintained by Dirk Mittelstraß. Last updated 8 months ago.

8.9 match 2 stars 3.30 score 2 scripts

gallegoj

tfarima:Transfer Function and ARIMA Models

Building customized transfer function and ARIMA models with multiple operators and parameter restrictions. Functions for model identification, model estimation (exact or conditional maximum likelihood), model diagnostic checking, automatic outlier detection, calendar effects, forecasting and seasonal adjustment. See Bell and Hillmer (1983) <doi:10.1080/01621459.1983.10478005>, Box, Jenkins, Reinsel and Ljung <ISBN:978-1-118-67502-1>, Box, Pierce and Newbold (1987) <doi:10.1080/01621459.1987.10478430>, Box and Tiao (1975) <doi:10.1080/01621459.1975.10480264>, Chen and Liu (1993) <doi:10.1080/01621459.1993.10594321>.

Maintained by Jose L. Gallego. Last updated 12 months ago.

openblas cpp openmp

7.2 match 2 stars 4.04 score 11 scripts

pauleilers

JOPS:Practical Smoothing with P-Splines

Functions and data to reproduce all plots in the book "Practical Smoothing. The Joys of P-splines" by Paul H.C. Eilers and Brian D. Marx (2021, ISBN:978-1108482950).

Maintained by Paul Eilers. Last updated 2 years ago.

8.4 match 1 stars 3.43 score 296 scripts 3 dependents

dipterix

readNSx:Read 'Blackrock-Microsystems' Files ('NEV', 'NSx')

Loads 'Blackrock' <https://blackrockneurotech.com> neural signal data files into the memory, provides utility tools to extract the data into common formats such as plain-text 'tsv' and 'HDF5'.

Maintained by Zhengjia Wang. Last updated 6 months ago.

data-formats dbi ieeg ieeg-data neuroscience-data cpp

5.2 match 3 stars 5.43 score 7 scripts 2 dependents

dkaschek

dMod:Dynamic Modeling and Parameter Estimation in ODE Models

The framework provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives.

Maintained by Daniel Kaschek. Last updated 10 days ago.

3.4 match 20 stars 8.35 score 251 scripts

gillian-earthscope

IRISSeismic:Classes and Methods for Seismic Data Analysis

Provides classes and methods for seismic data analysis. The base classes and methods are inspired by the python code found in the 'ObsPy' python toolbox <https://github.com/obspy/obspy>. Additional classes and methods support data returned by web services provided by EarthScope. <https://service.earthscope.org/>.

Maintained by Gillian Sharer. Last updated 3 months ago.

8.8 match 3.18 score 50 scripts 1 dependents

rpatin

segclust2d:Bivariate Segmentation/Clustering Methods and Tools

Provides two methods for segmentation and joint segmentation/clustering of bivariate time-series. Originally intended for ecological segmentation (home-range and behavioural modes) but easily applied on other series, the package also provides tools for analysing outputs from R packages 'moveHMM' and 'marcher'. The segmentation method is a bivariate extension of Lavielle's method available in 'adehabitatLT' (Lavielle, 1999 <doi:10.1016/S0304-4149(99)00023-X> and 2005 <doi:10.1016/j.sigpro.2005.01.012>). This method rely on dynamic programming for efficient segmentation. The segmentation/clustering method alternates steps of dynamic programming with an Expectation-Maximization algorithm. This is an extension of Picard et al (2007) <doi:10.1111/j.1541-0420.2006.00729.x> method (formerly available in 'cghseg' package) to the bivariate case. The method is fully described in Patin et al (2018) <doi:10.1101/444794>.

Maintained by Remi Patin. Last updated 11 months ago.

cpp

5.1 match 7 stars 5.50 score 30 scripts

khliland

EMSC:Extended Multiplicative Signal Correction

Background correction of spectral like data. Handles variations in scaling, polynomial baselines, interferents, constituents and replicate variation. Parameters for corrections are stored for further analysis, and spectra are corrected accordingly.

Maintained by Kristian Hovde Liland. Last updated 1 years ago.

6.6 match 3 stars 4.18 score 9 scripts

shikokuchuo

nanonext:NNG (Nanomsg Next Gen) Lightweight Messaging Library

R binding for NNG (Nanomsg Next Gen), a successor to ZeroMQ. NNG is a socket library for reliable, high-performance messaging over in-process, IPC, TCP, WebSocket and secure TLS transports. Implements 'Scalability Protocols', a standard for common communications patterns including publish/subscribe, request/reply and service discovery. As its own threaded concurrency framework, provides a toolkit for asynchronous programming and distributed computing. Intuitive 'aio' objects resolve automatically when asynchronous operations complete, and synchronisation primitives allow R to wait upon events signalled by concurrent threads.

Maintained by Charlie Gao. Last updated 2 days ago.

concurrency https ipc-message messaging-library nng rpc socket-communication synchronization-primitives tcp-protocol websocket mbedtls

2.8 match 60 stars 9.81 score 28 scripts 9 dependents

michbur

biogram:N-Gram Analysis of Biological Sequences

Tools for extraction and analysis of various n-grams (k-mers) derived from biological sequences (proteins or nucleic acids). Contains QuiPT (quick permutation test) for fast feature-filtering of the n-gram data.

Maintained by Michal Burdukiewicz. Last updated 7 months ago.

biological-sequences ngram-analysis

3.6 match 10 stars 7.50 score 87 scripts 3 dependents

cran

mixAK:Multivariate Normal Mixture Models and Mixtures of Generalized Linear Mixed Models Including Model Based Clustering

Contains a mixture of statistical methods including the MCMC methods to analyze normal mixtures. Additionally, model based clustering methods are implemented to perform classification based on (multivariate) longitudinal (or otherwise correlated) data. The basis for such clustering is a mixture of multivariate generalized linear mixed models. The package is primarily related to the publications Komárek (2009, Comp. Stat. and Data Anal.) <doi:10.1016/j.csda.2009.05.006> and Komárek and Komárková (2014, J. of Stat. Soft.) <doi:10.18637/jss.v059.i12>. It also implements methods published in Komárek and Komárková (2013, Ann. of Appl. Stat.) <doi:10.1214/12-AOAS580>, Hughes, Komárek, Bonnett, Czanner, García-Fiñana (2017, Stat. in Med.) <doi:10.1002/sim.7397>, Jaspers, Komárek, Aerts (2018, Biom. J.) <doi:10.1002/bimj.201600253> and Hughes, Komárek, Czanner, García-Fiñana (2018, Stat. Meth. in Med. Res) <doi:10.1177/0962280216674496>.

Maintained by Arnošt Komárek. Last updated 6 months ago.

openblas

7.6 match 4 stars 3.55 score 3 dependents

tpronk

splithalfr:Estimate Split-Half Reliabilities

Estimates split-half reliabilities for scoring algorithms of cognitive tasks and questionnaires. The 'splithalfr' supports researcher-provided scoring algorithms, with six vignettes illustrating how on included datasets. The package provides four splitting methods (first-second, odd-even, permutated, Monte Carlo), the option to stratify splits by task design, a number of reliability coefficients, and the option to sub-sample data.

Maintained by Thomas Pronk. Last updated 1 years ago.

4.6 match 5 stars 5.86 score 41 scripts

raim

segmenTier:Similarity-Based Segmentation of Multidimensional Signals

A dynamic programming solution to segmentation based on maximization of arbitrary similarity measures within segments. The general idea, theory and this implementation are described in Machne, Murray & Stadler (2017) <doi:10.1038/s41598-017-12401-8>. In addition to the core algorithm, the package provides time-series processing and clustering functions as described in the publication. These are generally applicable where a `k-means` clustering yields meaningful results, and have been specifically developed for clustering of the Discrete Fourier Transform of periodic gene expression data (`circadian' or `yeast metabolic oscillations'). This clustering approach is outlined in the supplemental material of Machne & Murray (2012) <doi:10.1371/journal.pone.0037906>), and here is used as a basis of segment similarity measures. Notably, the time-series processing and clustering functions can also be used as stand-alone tools, independent of segmentation, e.g., for transcriptome data already mapped to genes.

Maintained by Rainer Machne. Last updated 4 years ago.

cpp

5.9 match 3 stars 4.48 score 8 scripts

crp2a

gamma:Dose Rate Estimation from in-Situ Gamma-Ray Spectrometry Measurements

Process in-situ Gamma-Ray Spectrometry for Luminescence Dating. This package allows to import, inspect and correct the energy shifts of gamma-ray spectra. It provides methods for estimating the gamma dose rate by the use of a calibration curve as described in Mercier and Falguères (2007). The package only supports Canberra CNF and TKA and Kromek SPE files.

Maintained by Archéosciences Bordeaux. Last updated 6 months ago.

archaeometry gamma-spectrometry geochronology luminescence-dating

3.8 match 6 stars 6.99 score 11 scripts 1 dependents

bioc

CARNIVAL:A CAusal Reasoning tool for Network Identification (from gene expression data) using Integer VALue programming

An upgraded causal reasoning tool from Melas et al in R with updated assignments of TFs' weights from PROGENy scores. Optimization parameters can be freely adjusted and multiple solutions can be obtained and aggregated.

Maintained by Attila Gabor. Last updated 5 months ago.

transcriptomics geneexpression network causal-models footprints integer-linear-programming pathway-enrichment-analysis

2.8 match 57 stars 9.03 score 90 scripts 1 dependents

guenardg

MPSEM:Modelling Phylogenetic Signals using Eigenvector Maps

Computational tools to represent phylogenetic signals using adapted eigenvector maps.

Maintained by Guillaume Guénard. Last updated 6 months ago.

5.2 match 4.80 score 21 scripts 1 dependents

liamrevell

phytools:Phylogenetic Tools for Comparative Biology (and Other Things)

A wide range of methods for phylogenetic analysis - concentrated in phylogenetic comparative biology, but also including numerous techniques for visualizing, analyzing, manipulating, reading or writing, and even inferring phylogenetic trees. Included among the functions in phylogenetic comparative biology are various for ancestral state reconstruction, model-fitting, and simulation of phylogenies and trait data. A broad range of plotting methods for phylogenies and comparative data include (but are not restricted to) methods for mapping trait evolution on trees, for projecting trees into phenotype space or a onto a geographic map, and for visualizing correlated speciation between trees. Lastly, numerous functions are designed for reading, writing, analyzing, inferring, simulating, and manipulating phylogenetic trees and comparative data. For instance, there are functions for computing consensus phylogenies from a set, for simulating phylogenetic trees and data under a range of models, for randomly or non-randomly attaching species or clades to a tree, as well as for a wide range of other manipulations and analyses that phylogenetic biologists might find useful in their research.

Maintained by Liam J. Revell. Last updated 28 days ago.

1.8 match 218 stars 13.85 score 4.8k scripts 76 dependents

cran

IDetect:Isolate-Detect Methodology for Multiple Change-Point Detection

Provides efficient implementation of the Isolate-Detect methodology for the consistent estimation of the number and location of multiple change-points in one-dimensional data sequences from the "deterministic + noise" model. For details on the Isolate-Detect methodology, please see Anastasiou and Fryzlewicz (2018) <https://docs.wixstatic.com/ugd/24cdcc_6a0866c574654163b8255e272bc0001b.pdf>. Currently implemented scenarios are: piecewise-constant signal with Gaussian noise, piecewise-constant signal with heavy-tailed noise, continuous piecewise-linear signal with Gaussian noise, continuous piecewise-linear signal with heavy-tailed noise.

Maintained by Andreas Anastasiou. Last updated 7 years ago.

16.6 match 1.48 score 1 dependents

leerichardson

swdft:Sliding Window Discrete Fourier Transform (SWDFT)

Implements the Sliding Window Discrete Fourier Transform (SWDFT). Also provides statistical methods based on the SWDFT, and graphical tools to display the outputs.

Maintained by Lee F. Richardson. Last updated 6 years ago.

9.1 match 1 stars 2.70 score 6 scripts

frankiethull

maize:Specialty Kernels for SVMs

Bindings for svm kernels via kernlab for use with the 'parsnip' package. Specifically related to specialty kernels for support vector machines not available in parsnip. package includes interface for various kernlab kernels and custom kernels too.

Maintained by Frankie T. Hull. Last updated 9 hours ago.

6.8 match 7 stars 3.54 score 3 scripts

bioc

NADfinder:Call wide peaks for sequencing data

Nucleolus is an important structure inside the nucleus in eukaryotic cells. It is the site for transcribing rDNA into rRNA and for assembling ribosomes, aka ribosome biogenesis. In addition, nucleoli are dynamic hubs through which numerous proteins shuttle and contact specific non-rDNA genomic loci. Deep sequencing analyses of DNA associated with isolated nucleoli (NAD- seq) have shown that specific loci, termed nucleolus- associated domains (NADs) form frequent three- dimensional associations with nucleoli. NAD-seq has been used to study the biological functions of NAD and the dynamics of NAD distribution during embryonic stem cell (ESC) differentiation. Here, we developed a Bioconductor package NADfinder for bioinformatic analysis of the NAD-seq data, including baseline correction, smoothing, normalization, peak calling, and annotation.

Maintained by Jianhong Ou. Last updated 2 months ago.

sequencing dnaseq generegulation peakdetection

5.8 match 4.18 score 1 scripts

bioc

CSSQ:Chip-seq Signal Quantifier Pipeline

This package is desgined to perform statistical analysis to identify statistically significant differentially bound regions between multiple groups of ChIP-seq dataset.

Maintained by Fan Lab at Georgia Institute of Technology. Last updated 5 months ago.

chipseq differentialpeakcalling sequencing normalization

6.0 match 4.00 score 1 scripts

bioc

treeclimbR:An algorithm to find optimal signal levels in a tree

The arrangement of hypotheses in a hierarchical structure appears in many research fields and often indicates different resolutions at which data can be viewed. This raises the question of which resolution level the signal should best be interpreted on. treeclimbR provides a flexible method to select optimal resolution levels (potentially different levels in different parts of the tree), rather than cutting the tree at an arbitrary level. treeclimbR uses a tuning parameter to generate candidate resolutions and from these selects the optimal one.

Maintained by Charlotte Soneson. Last updated 3 months ago.

statisticalmethod cellbasedassays

3.4 match 20 stars 7.00 score 45 scripts

wincowgerdev

OpenSpecy:Analyze, Process, Identify, and Share Raman and (FT)IR Spectra

Raman and (FT)IR spectral analysis tool for plastic particles and other environmental samples (Cowger et al. 2021, <doi:10.1021/acs.analchem.1c00123>). With read_any(), Open Specy provides a single function for reading individual, batch, or map spectral data files like .asp, .csv, .jdx, .spc, .spa, .0, and .zip. process_spec() simplifies processing spectra, including smoothing, baseline correction, range restriction and flattening, intensity conversions, wavenumber alignment, and min-max normalization. Spectra can be identified in batch using an onboard reference library (Cowger et al. 2020, <doi:10.1177/0003702820929064>) using match_spec(). A Shiny app is available via run_app() or online at <https://openanalysis.org/openspecy/>.

Maintained by Win Cowger. Last updated 17 days ago.

3.1 match 29 stars 7.58 score 22 scripts

bioc

puma:Propagating Uncertainty in Microarray Analysis(including Affymetrix tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0)

Most analyses of Affymetrix GeneChip data (including tranditional 3' arrays and exon arrays and Human Transcriptome Array 2.0) are based on point estimates of expression levels and ignore the uncertainty of such estimates. By propagating uncertainty to downstream analyses we can improve results from microarray analyses. For the first time, the puma package makes a suite of uncertainty propagation methods available to a general audience. In additon to calculte gene expression from Affymetrix 3' arrays, puma also provides methods to process exon arrays and produces gene and isoform expression for alternative splicing study. puma also offers improvements in terms of scope and speed of execution over previously available uncertainty propagation methods. Included are summarisation, differential expression detection, clustering and PCA methods, together with useful plotting functions.

Maintained by Xuejun Liu. Last updated 5 months ago.

microarray onechannel preprocessing differentialexpression clustering exonarray geneexpression mrnamicroarray chiponchip alternativesplicing differentialsplicing bayesian twochannel dataimport hta2.0

5.2 match 4.53 score 17 scripts

andrewzm

EFDR:Wavelet-Based Enhanced FDR for Detecting Signals from Complete or Incomplete Spatially Aggregated Data

Enhanced False Discovery Rate (EFDR) is a tool to detect anomalies in an image. The image is first transformed into the wavelet domain in order to decorrelate any noise components, following which the coefficients at each resolution are standardised. Statistical tests (in a multiple hypothesis testing setting) are then carried out to find the anomalies. The power of EFDR exceeds that of standard FDR, which would carry out tests on every wavelet coefficient: EFDR choose which wavelets to test based on a criterion described in Shen et al. (2002). The package also provides elementary tools to interpolate spatially irregular data onto a grid of the required size. The work is based on Shen, X., Huang, H.-C., and Cressie, N. 'Nonparametric hypothesis testing for a spatial signal.' Journal of the American Statistical Association 97.460 (2002): 1122-1140.

Maintained by Andrew Zammit-Mangion. Last updated 2 years ago.

4.9 match 5 stars 4.74 score 22 scripts

doccstat

fastcpd:Fast Change Point Detection via Sequential Gradient Descent

Implements fast change point detection algorithm based on the paper "Sequential Gradient Descent and Quasi-Newton's Method for Change-Point Analysis" by Xianyang Zhang, Trisha Dawn <https://proceedings.mlr.press/v206/zhang23b.html>. The algorithm is based on dynamic programming with pruning and sequential gradient descent. It is able to detect change points a magnitude faster than the vanilla Pruned Exact Linear Time(PELT). The package includes examples of linear regression, logistic regression, Poisson regression, penalized linear regression data, and whole lot more examples with custom cost function in case the user wants to use their own cost function.

Maintained by Xingchi Li. Last updated 3 hours ago.

change-point-detection cpp custom-function gradient-descent lasso linear-regression logistic-regression offline pelt penalized-regression poisson-regression quasi-newton statistics time-series warm-start fortran openblas cpp openmp

3.3 match 22 stars 7.00 score 7 scripts

cran

ica:Independent Component Analysis

Independent Component Analysis (ICA) using various algorithms: FastICA, Information-Maximization (Infomax), and Joint Approximate Diagonalization of Eigenmatrices (JADE).

Maintained by Nathaniel E. Helwig. Last updated 3 years ago.

3.6 match 1 stars 6.43 score 78 scripts 83 dependents

dkimstatlab

EPT:Ensemble Patch Transform, Visualization and Decomposition

For multiscale analysis, this package carries out ensemble patch transform, its visualization and multiscale decomposition. The detailed procedure is described in Kim et al. (2020), and Oh and Kim (2020). D. Kim, G. Choi, H.-S. Oh, Ensemble patch transformation: a flexible framework for decomposition and filtering of signal, EURASIP Journal on Advances in Signal Processing 30 (2020) 1-27 <doi:10.1186/s13634-020-00690-7>. H.-S. Oh, D. Kim, Image decomposition by bidimensional ensemble patch transform, Pattern Recognition Letters 135 (2020) 173-179 <doi:10.1016/j.patrec.2020.03.029>.

Maintained by Donghoh Kim. Last updated 3 years ago.

11.5 match 2.00 score 3 scripts

bioc

chopsticks:The 'snp.matrix' and 'X.snp.matrix' Classes

Implements classes and methods for large-scale SNP association studies

Maintained by Hin-Tak Leung. Last updated 3 months ago.

microarray snpsandgeneticvariability snp geneticvariability

6.6 match 3.48 score 5 scripts

bioc

epistack:Heatmaps of Stack Profiles from Epigenetic Signals

The epistack package main objective is the visualizations of stacks of genomic tracks (such as, but not restricted to, ChIP-seq, ATAC-seq, DNA methyation or genomic conservation data) centered at genomic regions of interest. epistack needs three different inputs: 1) a genomic score objects, such as ChIP-seq coverage or DNA methylation values, provided as a `GRanges` (easily obtained from `bigwig` or `bam` files). 2) a list of feature of interest, such as peaks or transcription start sites, provided as a `GRanges` (easily obtained from `gtf` or `bed` files). 3) a score to sort the features, such as peak height or gene expression value.

Maintained by DEVAILLY Guillaume. Last updated 5 months ago.

rnaseq preprocessing chipseq geneexpression coverage bioinformatics

4.3 match 6 stars 5.26 score 5 scripts

karlines

diagram:Functions for Visualising Simple Graphs (Networks), Plotting Flow Diagrams

Visualises simple graphs (networks) based on a transition matrix, utilities to plot flow diagrams, visualising webs, electrical networks, etc. Support for the book "A practical guide to ecological modelling - using R as a simulation platform" by Karline Soetaert and Peter M.J. Herman (2009), Springer. and the book "Solving Differential Equations in R" by Karline Soetaert, Jeff Cash and Francesca Mazzia (2012), Springer. Includes demo(flowchart), demo(plotmat), demo(plotweb).

Maintained by Karline Soetaert. Last updated 4 years ago.

2.3 match 10.06 score 598 scripts 487 dependents

bioc

msPurity:Automated Evaluation of Precursor Ion Purity for Mass Spectrometry Based Fragmentation in Metabolomics

msPurity R package was developed to: 1) Assess the spectral quality of fragmentation spectra by evaluating the "precursor ion purity". 2) Process fragmentation spectra. 3) Perform spectral matching. What is precursor ion purity? -What we call "Precursor ion purity" is a measure of the contribution of a selected precursor peak in an isolation window used for fragmentation. The simple calculation involves dividing the intensity of the selected precursor peak by the total intensity of the isolation window. When assessing MS/MS spectra this calculation is done before and after the MS/MS scan of interest and the purity is interpolated at the recorded time of the MS/MS acquisition. Additionally, isotopic peaks can be removed, low abundance peaks are removed that are thought to have limited contribution to the resulting MS/MS spectra and the isolation efficiency of the mass spectrometer can be used to normalise the intensities used for the calculation.

Maintained by Thomas N. Lawson. Last updated 5 months ago.

massspectrometry metabolomics software bioconductor-package dims fragmentation lc-ms lc-msms mass-spectrometry precursor-ion-purity

3.2 match 15 stars 7.03 score 44 scripts

kwb-r

kwb.rain:Functions to Handle and Plot Rain Data at KWB

Functions to handle and plot rain data at KWB.

Maintained by Hauke Sonnenberg. Last updated 3 years ago.

data-import data-visualisation project-flusshygiene project-kuras

8.3 match 2.70 score

bioc

MSnbase:Base Functions and Classes for Mass Spectrometry and Proteomics

MSnbase provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data.

Maintained by Laurent Gatto. Last updated 2 days ago.

immunooncology infrastructure proteomics massspectrometry qualitycontrol dataimport bioconductor bioinformatics mass-spectrometry proteomics-data visualisation cpp

1.8 match 130 stars 12.81 score 772 scripts 36 dependents

wlandau

crew:A Distributed Worker Launcher Framework

In computationally demanding analysis projects, statisticians and data scientists asynchronously deploy long-running tasks to distributed systems, ranging from traditional clusters to cloud services. The 'NNG'-powered 'mirai' R package by Gao (2023) <doi:10.5281/zenodo.7912722> is a sleek and sophisticated scheduler that efficiently processes these intense workloads. The 'crew' package extends 'mirai' with a unifying interface for third-party worker launchers. Inspiration also comes from packages. 'future' by Bengtsson (2021) <doi:10.32614/RJ-2021-048>, 'rrq' by FitzJohn and Ashton (2023) <https://github.com/mrc-ide/rrq>, 'clustermq' by Schubert (2019) <doi:10.1093/bioinformatics/btz284>), and 'batchtools' by Lang, Bischel, and Surmann (2017) <doi:10.21105/joss.00135>.

Maintained by William Michael Landau. Last updated 2 days ago.

high-performance-computing

2.0 match 136 stars 11.19 score 243 scripts 2 dependents

adokter

vol2birdR:Vertical Profiles of Biological Signals in Weather Radar Data

'R' implementation of the 'vol2bird' software for generating vertical profiles of birds and other biological signals in weather radar data. See Dokter et al. (2011) <doi:10.1098/rsif.2010.0116> for a paper describing the methodology.

Maintained by Adriaan M. Dokter. Last updated 10 days ago.

proj hdf5 zlib gsl cpp

3.4 match 6 stars 6.61 score 19 scripts

jinghuazhao

gap:Genetic Analysis Package

As first reported [Zhao, J. H. 2007. "gap: Genetic Analysis Package". J Stat Soft 23(8):1-18. <doi:10.18637/jss.v023.i08>], it is designed as an integrated package for genetic data analysis of both population and family data. Currently, it contains functions for sample size calculations of both population-based and family-based designs, probability of familial disease aggregation, kinship calculation, statistics in linkage analysis, and association analysis involving genetic markers including haplotype analysis with or without environmental covariates. Over years, the package has been developed in-between many projects hence also in line with the name (gap).

Maintained by Jing Hua Zhao. Last updated 16 days ago.

genetics imputation lmm fortran

1.9 match 12 stars 11.88 score 448 scripts 16 dependents

stuart-lab

Signac:Analysis of Single-Cell Chromatin Data

A framework for the analysis and exploration of single-cell chromatin data. The 'Signac' package contains functions for quantifying single-cell chromatin data, computing per-cell quality control metrics, dimension reduction and normalization, visualization, and DNA sequence motif analysis. Reference: Stuart et al. (2021) <doi:10.1038/s41592-021-01282-5>.

Maintained by Tim Stuart. Last updated 7 months ago.

atac bioinformatics single-cell zlib cpp

1.8 match 349 stars 12.19 score 3.7k scripts 1 dependents

bioc

structToolbox:Data processing & analysis tools for Metabolomics and other omics

An extensive set of data (pre-)processing and analysis methods and tools for metabolomics and other omics, with a strong emphasis on statistics and machine learning. This toolbox allows the user to build extensive and standardised workflows for data analysis. The methods and tools have been implemented using class-based templates provided by the struct (Statistics in R Using Class-based Templates) package. The toolbox includes pre-processing methods (e.g. signal drift and batch correction, normalisation, missing value imputation and scaling), univariate (e.g. ttest, various forms of ANOVA, Kruskal–Wallis test and more) and multivariate statistical methods (e.g. PCA and PLS, including cross-validation and permutation testing) as well as machine learning methods (e.g. Support Vector Machines). The STATistics Ontology (STATO) has been integrated and implemented to provide standardised definitions for the different methods, inputs and outputs.

Maintained by Gavin Rhys Lloyd. Last updated 26 days ago.

workflowstep metabolomics bioconductor-package dims lc-ms machine-learning multivariate-analysis statistics univariate

3.5 match 10 stars 6.26 score 12 scripts

bjw34032

waveslim:Basic Wavelet Routines for One-, Two-, and Three-Dimensional Signal Processing

Basic wavelet routines for time series (1D), image (2D) and array (3D) analysis. The code provided here is based on wavelet methodology developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002). All figures in chapters 4-7 of GSW (2001) are reproducible using this package and R code available at the book website(s) below.

Maintained by Brandon Whitcher. Last updated 10 months ago.

wavelets

2.8 match 3 stars 7.88 score 108 scripts 23 dependents

rjdverse

rjd3sts:State Space Framework and Structural Time Series with 'JDemetra+ 3.x'

R Interface to 'JDemetra+ 3.x' (<https://github.com/jdemetra>) time series analysis software. It offers access to several functions on state space models and structural time series.

Maintained by Jean Palate. Last updated 8 months ago.

openjdk

3.3 match 2 stars 6.64 score 25 scripts 4 dependents

bioc

CAGEr:Analysis of CAGE (Cap Analysis of Gene Expression) sequencing data for precise mapping of transcription start sites and promoterome mining

The _CAGEr_ package identifies transcription start sites (TSS) and their usage frequency from CAGE (Cap Analysis Gene Expression) sequencing data. It normalises raw CAGE tag count, clusters TSSs into tag clusters (TC) and aggregates them across multiple CAGE experiments to construct consensus clusters (CC) representing the promoterome. CAGEr provides functions to profile expression levels of these clusters by cumulative expression and rarefaction analysis, and outputs the plots in ggplot2 format for further facetting and customisation. After clustering, CAGEr performs analyses of promoter width and detects differential usage of TSSs (promoter shifting) between samples. CAGEr also exports its data as genome browser tracks, and as R objects for downsteam expression analysis by other Bioconductor packages such as DESeq2, CAGEfightR, or seqArchR.

Maintained by Charles Plessy. Last updated 5 months ago.

preprocessing sequencing normalization functionalgenomics transcription geneexpression clustering visualization

3.5 match 6.12 score 73 scripts

jeromeecoac

seewave:Sound Analysis and Synthesis

Functions for analysing, manipulating, displaying, editing and synthesizing time waves (particularly sound). This package processes time analysis (oscillograms and envelopes), spectral content, resonance quality factor, entropy, cross correlation and autocorrelation, zero-crossing, dominant frequency, analytic signal, frequency coherence, 2D and 3D spectrograms and many other analyses. See Sueur et al. (2008) <doi:10.1080/09524622.2008.9753600> and Sueur (2018) <doi:10.1007/978-3-319-77647-7>.

Maintained by Jerome Sueur. Last updated 1 years ago.

2.4 match 18 stars 8.88 score 880 scripts 23 dependents

paws-r

paws:Amazon Web Services Software Development Kit

Interface to Amazon Web Services <https://aws.amazon.com>, including storage, database, and compute services, such as 'Simple Storage Service' ('S3'), 'DynamoDB' 'NoSQL' database, and 'Lambda' functions-as-a-service.

Maintained by Dyfan Jones. Last updated 4 days ago.

aws aws-sdk

1.9 match 332 stars 11.25 score 177 scripts 12 dependents

fellstat

ipc:Tools for Message Passing Between Processes

Provides tools for passing messages between R processes. Shiny examples are provided showing how to perform useful tasks such as: updating reactive values from within a future, progress bars for long running async tasks, and interrupting async tasks based on user input.

Maintained by Ian E. Fellows. Last updated 2 years ago.

3.2 match 56 stars 6.50 score 38 scripts 1 dependents

venpopov

bmm:Easy and Accessible Bayesian Measurement Models Using 'brms'

Fit computational and measurement models using full Bayesian inference. The package provides a simple and accessible interface by translating complex domain-specific models into 'brms' syntax, a powerful and flexible framework for fitting Bayesian regression models using 'Stan'. The package is designed so that users can easily apply state-of-the-art models in various research fields, and so that researchers can use it as a new model development framework. References: Frischkorn and Popov (2023) <doi:10.31234/osf.io/umt57>.

Maintained by Vencislav Popov. Last updated 13 days ago.

3.5 match 15 stars 5.92 score 35 scripts

cran

wavethresh:Wavelets Statistics and Transforms

Performs 1, 2 and 3D real and complex-valued wavelet transforms, nondecimated transforms, wavelet packet transforms, nondecimated wavelet packet transforms, multiple wavelet transforms, complex-valued wavelet transforms, wavelet shrinkage for various kinds of data, locally stationary wavelet time series, nonstationary multiscale transfer function modeling, density estimation.

Maintained by Guy Nason. Last updated 7 months ago.

3.5 match 5.89 score 41 dependents

klauschn

ICtest:Estimating and Testing the Number of Interesting Components in Linear Dimension Reduction

For different linear dimension reduction methods like principal components analysis (PCA), independent components analysis (ICA) and supervised linear dimension reduction tests and estimates for the number of interesting components (ICs) are provided.

Maintained by Klaus Nordhausen. Last updated 3 years ago.

openblas cpp

4.7 match 4.36 score 63 scripts 4 dependents

vankesteren

rpeaks:Fast detection of R peaks in ecg data

Package for fast detection of R peaks using a simplified pan-tompkins algorithm. Uses fast C++ code to speed up computations for long ecg recordings.

Maintained by Erik-Jan van Kesteren. Last updated 1 years ago.

ecg heart-rate-analysis qrs qrs-detection signal-processing openblas cpp

7.5 match 5 stars 2.70 score 5 scripts

bioc

sevenC:Computational Chromosome Conformation Capture by Correlation of ChIP-seq at CTCF motifs

Chromatin looping is an essential feature of eukaryotic genomes and can bring regulatory sequences, such as enhancers or transcription factor binding sites, in the close physical proximity of regulated target genes. Here, we provide sevenC, an R package that uses protein binding signals from ChIP-seq and sequence motif information to predict chromatin looping events. Cross-linking of proteins that bind close to loop anchors result in ChIP-seq signals at both anchor loci. These signals are used at CTCF motif pairs together with their distance and orientation to each other to predict whether they interact or not. The resulting chromatin loops might be used to associate enhancers or transcription factor binding sites (e.g., ChIP-seq peaks) to regulated target genes.

Maintained by Jonas Ibn-Salem. Last updated 5 months ago.

dna3dstructure chipchip coverage dataimport epigenetics functionalgenomics classification regression chipseq hic annotation 3d-genome chip-seq chromatin-interaction hi-c prediction sequence-motif transcription-factors

3.8 match 12 stars 5.38 score 3 scripts

cran

biosignalEMG:Tools for Electromyogram Signals (EMG) Analysis

Data processing tools to compute the rectified, integrated and the averaged EMG. Routines for automatic detection of activation phases. A routine to compute and plot the ensemble average of the EMG. An EMG signal simulator for general purposes.

Maintained by Antonio Guerrero. Last updated 7 years ago.

11.1 match 2 stars 1.81 score 32 scripts

bioc

Repitools:Epigenomic tools

Tools for the analysis of enrichment-based epigenomic data. Features include summarization and visualization of epigenomic data across promoters according to gene expression context, finding regions of differential methylation/binding, BayMeth for quantifying methylation etc.

Maintained by Mark Robinson. Last updated 5 months ago.

dnamethylation geneexpression methylseq

3.3 match 5.90 score 267 scripts

bioc

funtooNorm:Normalization Procedure for Infinium HumanMethylation450 BeadChip Kit

Provides a function to normalize Illumina Infinium Human Methylation 450 BeadChip (Illumina 450K), correcting for tissue and/or cell type.

Maintained by Kathleen Klein. Last updated 5 months ago.

dnamethylation preprocessing normalization

5.3 match 3.70 score

bioc

maftools:Summarize, Analyze and Visualize MAF Files

Analyze and visualize Mutation Annotation Format (MAF) files from large scale sequencing studies. This package provides various functions to perform most commonly used analyses in cancer genomics and to create feature rich customizable visualzations with minimal effort.

Maintained by Anand Mayakonda. Last updated 5 months ago.

datarepresentation dnaseq visualization drivermutation variantannotation featureextraction classification somaticmutation sequencing functionalgenomics survival bioinformatics cancer-genome-atlas cancer-genomics genomics maf-files tcga curl bzip2 xz-utils zlib

1.3 match 459 stars 14.63 score 948 scripts 18 dependents

lcrawlab

mvMAPIT:Multivariate Genome Wide Marginal Epistasis Test

Epistasis, commonly defined as the interaction between genetic loci, is known to play an important role in the phenotypic variation of complex traits. As a result, many statistical methods have been developed to identify genetic variants that are involved in epistasis, and nearly all of these approaches carry out this task by focusing on analyzing one trait at a time. Previous studies have shown that jointly modeling multiple phenotypes can often dramatically increase statistical power for association mapping. In this package, we present the 'multivariate MArginal ePIstasis Test' ('mvMAPIT') – a multi-outcome generalization of a recently proposed epistatic detection method which seeks to detect marginal epistasis or the combined pairwise interaction effects between a given variant and all other variants. By searching for marginal epistatic effects, one can identify genetic variants that are involved in epistasis without the need to identify the exact partners with which the variants interact – thus, potentially alleviating much of the statistical and computational burden associated with conventional explicit search based methods. Our proposed 'mvMAPIT' builds upon this strategy by taking advantage of correlation structure between traits to improve the identification of variants involved in epistasis. We formulate 'mvMAPIT' as a multivariate linear mixed model and develop a multi-trait variance component estimation algorithm for efficient parameter inference and P-value computation. Together with reasonable model approximations, our proposed approach is scalable to moderately sized genome-wide association studies. Crawford et al. (2017) <doi:10.1371/journal.pgen.1006869>. Stamp et al. (2023) <doi:10.1093/g3journal/jkad118>.

Maintained by Julian Stamp. Last updated 5 months ago.

cpp epistasis epistasis-analysis gwas gwas-tools linear-mixed-models mapit mvmapit variance-components openblas cpp openmp

2.8 match 11 stars 6.90 score 17 scripts 1 dependents

cemos-mannheim

MALDIcellassay:Automated MALDI Cell Assays Using Dose-Response Curve Fitting

Conduct automated cell-based assays using Matrix-Assisted Laser Desorption/Ionization (MALDI) methods for high-throughput screening of signals responsive to treatments. The package efficiently identifies high variance signals and fits dose-response curves to them. Quality metrics such as Z', V', log2 Fold-Change, and Curve response score (CRS) are provided for evaluating the potential of signals as biomarkers. The methodologies were introduced by Weigt et al. (2018) <doi:10.1038/s41598-018-29677-z> and refined by Unger et al. (2021) <doi:10.1038/s41596-021-00624-z>.

Maintained by Thomas Enzlein. Last updated 2 months ago.

cell-based-assay concentration-response-analysis maldi-tof-ms mass-spectrometry untargeted-metabolomics

4.0 match 4.74 score 9 scripts

bioc

soGGi:Visualise ChIP-seq, MNase-seq and motif occurrence as aggregate plots Summarised Over Grouped Genomic Intervals

The soGGi package provides a toolset to create genomic interval aggregate/summary plots of signal or motif occurence from BAM and bigWig files as well as PWM, rlelist, GRanges and GAlignments Bioconductor objects. soGGi allows for normalisation, transformation and arithmetic operation on and between summary plot objects as well as grouping and subsetting of plots by GRanges objects and user supplied metadata. Plots are created using the GGplot2 libary to allow user defined manipulation of the returned plot object. Coupled together, soGGi features a broad set of methods to visualise genomics data in the context of groups of genomic intervals such as genes, superenhancers and transcription factor binding events.

Maintained by Tom Carroll. Last updated 5 months ago.

sequencing chipseq coverage

4.3 match 4.49 score 51 scripts 1 dependents

neuropsychology

psycho:Efficient and Publishing-Oriented Workflow for Psychological Science

The main goal of the psycho package is to provide tools for psychologists, neuropsychologists and neuroscientists, to facilitate and speed up the time spent on data analysis. It aims at supporting best practices and tools to format the output of statistical methods to directly paste them into a manuscript, ensuring statistical reporting standardization and conformity.

Maintained by Dominique Makowski. Last updated 4 years ago.

apa apa6 bayesian correlation format interpretation mixed-models neuroscience psycho psychology rstanarm statistics

1.8 match 149 stars 10.86 score 628 scripts 5 dependents

anonymous-eco

phylosignalDB:Explore Phylogenetic Signals Using Distance-Based Methods

A unified method, called M statistic, is provided for detecting phylogenetic signals in continuous traits, discrete traits, and multi-trait combinations. Blomberg and Garland (2002) <doi:10.1046/j.1420-9101.2002.00472.x> provided a widely accepted statistical definition of the phylogenetic signal, which is the "tendency for related species to resemble each other more than they resemble species drawn at random from the tree". The M statistic strictly adheres to the definition of phylogenetic signal, formulating an index and developing a method of testing in strict accordance with the definition, instead of relying on correlation analysis or evolutionary models. The novel method equivalently expressed the textual definition of the phylogenetic signal as an inequality equation of the phylogenetic and trait distances and constructed the M statistic. Also, there are more distance-based methods under development.

Maintained by Liang Yao. Last updated 2 months ago.

5.6 match 3.40 score

gabrielodom

mvMonitoring:Multi-State Adaptive Dynamic Principal Component Analysis for Multivariate Process Monitoring

Use multi-state splitting to apply Adaptive-Dynamic PCA (ADPCA) to data generated from a continuous-time multivariate industrial or natural process. Employ PCA-based dimension reduction to extract linear combinations of relevant features, reducing computational burdens. For a description of ADPCA, see <doi:10.1007/s00477-016-1246-2>, the 2016 paper from Kazor et al. The multi-state application of ADPCA is from a manuscript under current revision entitled "Multi-State Multivariate Statistical Process Control" by Odom, Newhart, Cath, and Hering, and is expected to appear in Q1 of 2018.

Maintained by Gabriel Odom. Last updated 1 years ago.

3.6 match 4 stars 5.24 score 29 scripts

lawremi

objectSignals:Observer Pattern for S4

A mutable Signal object can report changes to its state, clients could register functions so that they are called whenever the signal is emitted. The signal could be emitted, disconnected, blocked, unblocked, and buffered.

Maintained by Michael Lawrence. Last updated 3 years ago.

8.6 match 2.18 score 7 scripts 5 dependents

fchamroukhi

samurais:Statistical Models for the Unsupervised Segmentation of Time-Series ('SaMUraiS')

Provides a variety of original and flexible user-friendly statistical latent variable models and unsupervised learning algorithms to segment and represent time-series data (univariate or multivariate), and more generally, longitudinal data, which include regime changes. 'samurais' is built upon the following packages, each of them is an autonomous time-series segmentation approach: Regression with Hidden Logistic Process ('RHLP'), Hidden Markov Model Regression ('HMMR'), Multivariate 'RHLP' ('MRHLP'), Multivariate 'HMMR' ('MHMMR'), Piece-Wise regression ('PWR'). For the advantages/differences of each of them, the user is referred to our mentioned paper references. These models are originally introduced and written in 'Matlab' by Faicel Chamroukhi <https://github.com/fchamroukhi?&tab=repositories&q=time-series&type=public&language=matlab>.

Maintained by Florian Lecocq. Last updated 5 years ago.

artificial-intelligence change-point-detection data-science dynamic-programming em-algorithm hidden-markov-models hidden-process-regression human-activity-recognition latent-variable-models model-selection multivariate-timeseries newton-raphson piecewise-regression statistical-inference statistical-learning time-series-analysis time-series-clustering openblas cpp

3.0 match 12 stars 6.18 score 28 scripts

bips-hb

wflsa:Weighted Fused LASSO Signal Approximator ('wFLSA')

A package for computing the Weighted Fused LASSO Signal Approximator (wFLSA).

Maintained by Louis Dijkstra. Last updated 1 months ago.

fused-lasso lasso lasso-regression cpp

6.8 match 2.70 score 3 scripts

cozygene

TCA:Tensor Composition Analysis

Tensor Composition Analysis (TCA) allows the deconvolution of two-dimensional data (features by observations) coming from a mixture of heterogeneous sources into a three-dimensional matrix of signals (features by observations by sources). The TCA framework further allows to test the features in the data for different statistical relations with an outcome of interest while modeling source-specific effects; particularly, it allows to look for statistical relations between source-specific signals and an outcome. For example, TCA can deconvolve bulk tissue-level DNA methylation data (methylation sites by individuals) into a three-dimensional tensor of cell-type-specific methylation levels for each individual (i.e. methylation sites by individuals by cell types) and it allows to detect cell-type-specific statistical relations (associations) with phenotypes. For more details see Rahmani et al. (2019) <DOI:10.1038/s41467-019-11052-9>.

Maintained by Elior Rahmani. Last updated 4 years ago.

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