Showing 199 of total 199 results (show query)
jsugarelli
quantification:Quantification of Qualitative Survey Data
Provides different functions for quantifying qualitative survey data. It supports the Carlson-Parkin method, the regression approach, the balance approach and the conditional expectations method.
Maintained by Joachim Zuckarelli. Last updated 7 years ago.
carlson-parkinquantificationsurveysurvey-analysissurvey-data
65.0 match 4 stars 3.90 score 4 scripts
bioc
psichomics:Graphical Interface for Alternative Splicing Quantification, Analysis and Visualisation
Interactive R package with an intuitive Shiny-based graphical interface for alternative splicing quantification and integrative analyses of alternative splicing and gene expression based on The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression project (GTEx), Sequence Read Archive (SRA) and user-provided data. The tool interactively performs survival, dimensionality reduction and median- and variance-based differential splicing and gene expression analyses that benefit from the incorporation of clinical and molecular sample-associated features (such as tumour stage or survival). Interactive visual access to genomic mapping and functional annotation of selected alternative splicing events is also included.
Maintained by Nuno Saraiva-Agostinho. Last updated 5 months ago.
sequencingrnaseqalternativesplicingdifferentialsplicingtranscriptionguiprincipalcomponentsurvivalbiomedicalinformaticstranscriptomicsimmunooncologyvisualizationmultiplecomparisongeneexpressiondifferentialexpressionalternative-splicingbioconductordata-analysesdifferential-gene-expressiondifferential-splicing-analysisgene-expressiongtexrecount2rna-seq-datasplicing-quantificationsratcgavast-toolscpp
20.2 match 36 stars 6.95 score 31 scriptsbioc
bambu:Context-Aware Transcript Quantification from Long Read RNA-Seq data
bambu is a R package for multi-sample transcript discovery and quantification using long read RNA-Seq data. You can use bambu after read alignment to obtain expression estimates for known and novel transcripts and genes. The output from bambu can directly be used for visualisation and downstream analysis such as differential gene expression or transcript usage.
Maintained by Ying Chen. Last updated 1 months ago.
alignmentcoveragedifferentialexpressionfeatureextractiongeneexpressiongenomeannotationgenomeassemblyimmunooncologylongreadmultiplecomparisonnormalizationrnaseqregressionsequencingsoftwaretranscriptiontranscriptomicsbambubioconductorlong-readsnanoporenanopore-sequencingrna-seqrna-seq-analysistranscript-quantificationtranscript-reconstructioncpp
15.1 match 197 stars 9.03 score 91 scripts 1 dependents
drostlab
philentropy:Similarity and Distance Quantification Between Probability Functions
Computes 46 optimized distance and similarity measures for comparing probability functions (Drost (2018) <doi:10.21105/joss.00765>). These comparisons between probability functions have their foundations in a broad range of scientific disciplines from mathematics to ecology. The aim of this package is to provide a core framework for clustering, classification, statistical inference, goodness-of-fit, non-parametric statistics, information theory, and machine learning tasks that are based on comparing univariate or multivariate probability functions.
Maintained by Hajk-Georg Drost. Last updated 3 months ago.
distance-measuresdistance-quantificationinformation-theoryjensen-shannon-divergenceparametric-distributionssimilarity-measuresstatisticscpp
10.5 match 137 stars 12.44 score 484 scripts 24 dependents
cpanse
protViz:Visualizing and Analyzing Mass Spectrometry Related Data in Proteomics
Helps with quality checks, visualizations and analysis of mass spectrometry data, coming from proteomics experiments. The package is developed, tested and used at the Functional Genomics Center Zurich <https://fgcz.ch>. We use this package mainly for prototyping, teaching, and having fun with proteomics data. But it can also be used to do data analysis for small scale data sets.
Maintained by Christian Panse. Last updated 1 years ago.
funmass-spectrometrypeptide-identificationproteomicsquantificationvisualizationcpp
15.0 match 11 stars 7.88 score 72 scripts 2 dependents
tvpham
iq:Protein Quantification in Mass Spectrometry-Based Proteomics
An implementation of the MaxLFQ algorithm by Cox et al. (2014) <doi:10.1074/mcp.M113.031591> in a comprehensive pipeline for processing proteomics data in data-independent acquisition mode (Pham et al. 2020 <doi:10.1093/bioinformatics/btz961>). It offers additional options for protein quantification using the N most intense fragment ions, using all fragment ions, and a wrapper for the median polish algorithm by Tukey (1977, ISBN:0201076160). In general, the tool can be used to integrate multiple proportional observations into a single quantitative value.
Maintained by Thang Pham. Last updated 15 days ago.
17.2 match 27 stars 6.49 score 25 scriptsbioc
tximeta:Transcript Quantification Import with Automatic Metadata
Transcript quantification import from Salmon and other quantifiers with automatic attachment of transcript ranges and release information, and other associated metadata. De novo transcriptomes can be linked to the appropriate sources with linkedTxomes and shared for computational reproducibility.
Maintained by Michael Love. Last updated 2 months ago.
annotationgenomeannotationdataimportpreprocessingrnaseqsinglecelltranscriptomicstranscriptiongeneexpressionfunctionalgenomicsreproducibleresearchreportwritingimmunooncology
10.2 match 67 stars 10.58 score 466 scripts 1 dependents
aphalo
photobiology:Photobiological Calculations
Definitions of classes, methods, operators and functions for use in photobiology and radiation meteorology and climatology. Calculation of effective (weighted) and not-weighted irradiances/doses, fluence rates, transmittance, reflectance, absorptance, absorbance and diverse ratios and other derived quantities from spectral data. Local maxima and minima: peaks, valleys and spikes. Conversion between energy-and photon-based units. Wavelength interpolation. Astronomical calculations related solar angles and day length. Colours and vision. This package is part of the 'r4photobiology' suite, Aphalo, P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Maintained by Pedro J. Aphalo. Last updated 3 days ago.
lightphotobiologyquantificationr4photobiology-suiteradiationspectrasun-position
10.0 match 4 stars 9.35 score 604 scripts 12 dependentsbioc
artMS:Analytical R tools for Mass Spectrometry
artMS provides a set of tools for the analysis of proteomics label-free datasets. It takes as input the MaxQuant search result output (evidence.txt file) and performs quality control, relative quantification using MSstats, downstream analysis and integration. artMS also provides a set of functions to re-format and make it compatible with other analytical tools, including, SAINTq, SAINTexpress, Phosfate, and PHOTON. Check [http://artms.org](http://artms.org) for details.
Maintained by David Jimenez-Morales. Last updated 5 months ago.
proteomicsdifferentialexpressionbiomedicalinformaticssystemsbiologymassspectrometryannotationqualitycontrolgenesetenrichmentclusteringnormalizationimmunooncologymultiplecomparisonanalysisanalyticalap-msbioconductorbioinformaticsmass-spectrometryphosphoproteomicspost-translational-modificationquantitative-analysis
14.1 match 14 stars 6.41 score 13 scriptsbioc
MSstats:Protein Significance Analysis in DDA, SRM and DIA for Label-free or Label-based Proteomics Experiments
A set of tools for statistical relative protein significance analysis in DDA, SRM and DIA experiments.
Maintained by Meena Choi. Last updated 11 days ago.
immunooncologymassspectrometryproteomicssoftwarenormalizationqualitycontroltimecourseopenblascpp
9.4 match 8.49 score 164 scripts 7 dependents
billdenney
PKNCA:Perform Pharmacokinetic Non-Compartmental Analysis
Compute standard Non-Compartmental Analysis (NCA) parameters for typical pharmacokinetic analyses and summarize them.
Maintained by Bill Denney. Last updated 16 days ago.
ncanoncompartmental-analysispharmacokinetics
6.2 match 73 stars 12.61 score 214 scripts 4 dependentsbioc
TCGAbiolinks:TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data
The aim of TCGAbiolinks is : i) facilitate the GDC open-access data retrieval, ii) prepare the data using the appropriate pre-processing strategies, iii) provide the means to carry out different standard analyses and iv) to easily reproduce earlier research results. In more detail, the package provides multiple methods for analysis (e.g., differential expression analysis, identifying differentially methylated regions) and methods for visualization (e.g., survival plots, volcano plots, starburst plots) in order to easily develop complete analysis pipelines.
Maintained by Tiago Chedraoui Silva. Last updated 27 days ago.
dnamethylationdifferentialmethylationgeneregulationgeneexpressionmethylationarraydifferentialexpressionpathwaysnetworksequencingsurvivalsoftwarebiocbioconductorgdcintegrative-analysistcgatcga-datatcgabiolinks
5.3 match 305 stars 14.45 score 1.6k scripts 6 dependentsbioc
GEOquery:Get data from NCBI Gene Expression Omnibus (GEO)
The NCBI Gene Expression Omnibus (GEO) is a public repository of microarray data. Given the rich and varied nature of this resource, it is only natural to want to apply BioConductor tools to these data. GEOquery is the bridge between GEO and BioConductor.
Maintained by Sean Davis. Last updated 5 months ago.
microarraydataimportonechanneltwochannelsagebioconductorbioinformaticsdata-sciencegenomicsncbi-geo
5.2 match 92 stars 14.46 score 4.1k scripts 44 dependentsbioc
RImmPort:RImmPort: Enabling Ready-for-analysis Immunology Research Data
The RImmPort package simplifies access to ImmPort data for analysis in the R environment. It provides a standards-based interface to the ImmPort study data that is in a proprietary format.
Maintained by Zicheng Hu. Last updated 5 months ago.
biomedicalinformaticsdataimportdatarepresentation
16.8 match 4.33 score 27 scripts
techtonique
learningmachine:Machine Learning with Explanations and Uncertainty Quantification
Regression-based Machine Learning with explanations and uncertainty quantification.
Maintained by T. Moudiki. Last updated 4 months ago.
conformal-predictionmachine-learningmachine-learning-algorithmsmachinelearningstatistical-learninguncertainty-quantificationcpp
11.1 match 5 stars 5.57 score 21 scriptsbioc
ISAnalytics:Analyze gene therapy vector insertion sites data identified from genomics next generation sequencing reads for clonal tracking studies
In gene therapy, stem cells are modified using viral vectors to deliver the therapeutic transgene and replace functional properties since the genetic modification is stable and inherited in all cell progeny. The retrieval and mapping of the sequences flanking the virus-host DNA junctions allows the identification of insertion sites (IS), essential for monitoring the evolution of genetically modified cells in vivo. A comprehensive toolkit for the analysis of IS is required to foster clonal trackign studies and supporting the assessment of safety and long term efficacy in vivo. This package is aimed at (1) supporting automation of IS workflow, (2) performing base and advance analysis for IS tracking (clonal abundance, clonal expansions and statistics for insertional mutagenesis, etc.), (3) providing basic biology insights of transduced stem cells in vivo.
Maintained by Francesco Gazzo. Last updated 3 months ago.
biomedicalinformaticssequencingsinglecell
9.8 match 3 stars 5.83 score 15 scriptsbioc
rnaseqcomp:Benchmarks for RNA-seq Quantification Pipelines
Several quantitative and visualized benchmarks for RNA-seq quantification pipelines. Two-condition quantifications for genes, transcripts, junctions or exons by each pipeline with necessary meta information should be organized into numeric matrices in order to proceed the evaluation.
Maintained by Mingxiang Teng. Last updated 5 months ago.
rnaseqvisualizationqualitycontrol
9.6 match 8 stars 5.90 score 3 scripts
bioc
IsoformSwitchAnalyzeR:Identify, Annotate and Visualize Isoform Switches with Functional Consequences from both short- and long-read RNA-seq data
Analysis of alternative splicing and isoform switches with predicted functional consequences (e.g. gain/loss of protein domains etc.) from quantification of all types of RNASeq by tools such as Kallisto, Salmon, StringTie, Cufflinks/Cuffdiff etc.
Maintained by Kristoffer Vitting-Seerup. Last updated 5 months ago.
geneexpressiontranscriptionalternativesplicingdifferentialexpressiondifferentialsplicingvisualizationstatisticalmethodtranscriptomevariantbiomedicalinformaticsfunctionalgenomicssystemsbiologytranscriptomicsrnaseqannotationfunctionalpredictiongenepredictiondataimportmultiplecomparisonbatcheffectimmunooncology
5.7 match 108 stars 9.26 score 125 scriptstechtonique
ahead:Time Series Forecasting with uncertainty quantification
Univariate and multivariate time series forecasting with uncertainty quantification.
Maintained by T. Moudiki. Last updated 27 days ago.
forecastingmachine-learningpredictive-modelingstatistical-learningtime-seriestime-series-forecastinguncertainty-quantificationcpp
11.1 match 21 stars 4.77 score 51 scriptsbioc
FLAMES:FLAMES: Full Length Analysis of Mutations and Splicing in long read RNA-seq data
Semi-supervised isoform detection and annotation from both bulk and single-cell long read RNA-seq data. Flames provides automated pipelines for analysing isoforms, as well as intermediate functions for manual execution.
Maintained by Changqing Wang. Last updated 6 days ago.
rnaseqsinglecelltranscriptomicsdataimportdifferentialsplicingalternativesplicinggeneexpressionlongreadzlibcurlbzip2xz-utilscpp
6.5 match 31 stars 7.95 score 12 scriptsbioc
SGSeq:Splice event prediction and quantification from RNA-seq data
SGSeq is a software package for analyzing splice events from RNA-seq data. Input data are RNA-seq reads mapped to a reference genome in BAM format. Genes are represented as a splice graph, which can be obtained from existing annotation or predicted from the mapped sequence reads. Splice events are identified from the graph and are quantified locally using structurally compatible reads at the start or end of each splice variant. The software includes functions for splice event prediction, quantification, visualization and interpretation.
Maintained by Leonard Goldstein. Last updated 5 months ago.
alternativesplicingimmunooncologyrnaseqtranscription
7.6 match 5.91 score 45 scripts 3 dependentsbioc
MsQuality:MsQuality - Quality metric calculation from Spectra and MsExperiment objects
The MsQuality provides functionality to calculate quality metrics for mass spectrometry-derived, spectral data at the per-sample level. MsQuality relies on the mzQC framework of quality metrics defined by the Human Proteom Organization-Proteomics Standards Initiative (HUPO-PSI). These metrics quantify the quality of spectral raw files using a controlled vocabulary. The package is especially addressed towards users that acquire mass spectrometry data on a large scale (e.g. data sets from clinical settings consisting of several thousands of samples). The MsQuality package allows to calculate low-level quality metrics that require minimum information on mass spectrometry data: retention time, m/z values, and associated intensities. MsQuality relies on the Spectra package, or alternatively the MsExperiment package, and its infrastructure to store spectral data.
Maintained by Thomas Naake. Last updated 2 months ago.
metabolomicsproteomicsmassspectrometryqualitycontrolmass-spectrometryqc
8.2 match 7 stars 5.45 score 2 scriptsbioc
isobar:Analysis and quantitation of isobarically tagged MSMS proteomics data
isobar provides methods for preprocessing, normalization, and report generation for the analysis of quantitative mass spectrometry proteomics data labeled with isobaric tags, such as iTRAQ and TMT. Features modules for integrating and validating PTM-centric datasets (isobar-PTM). More information on http://www.ms-isobar.org.
Maintained by Florian P Breitwieser. Last updated 5 months ago.
immunooncologyproteomicsmassspectrometrybioinformaticsmultiplecomparisonsqualitycontrol
6.0 match 10 stars 6.96 score 19 scriptsbioc
scviR:experimental inferface from R to scvi-tools
This package defines interfaces from R to scvi-tools. A vignette works through the totalVI tutorial for analyzing CITE-seq data. Another vignette compares outputs of Chapter 12 of the OSCA book with analogous outputs based on totalVI quantifications. Future work will address other components of scvi-tools, with a focus on building understanding of probabilistic methods based on variational autoencoders.
Maintained by Vincent Carey. Last updated 5 months ago.
infrastructuresinglecelldataimportbioconductorcite-seqscverse
6.8 match 6 stars 5.60 score 11 scriptsbioc
QuasR:Quantify and Annotate Short Reads in R
This package provides a framework for the quantification and analysis of Short Reads. It covers a complete workflow starting from raw sequence reads, over creation of alignments and quality control plots, to the quantification of genomic regions of interest. Read alignments are either generated through Rbowtie (data from DNA/ChIP/ATAC/Bis-seq experiments) or Rhisat2 (data from RNA-seq experiments that require spliced alignments), or can be provided in the form of bam files.
Maintained by Michael Stadler. Last updated 23 days ago.
geneticspreprocessingsequencingchipseqrnaseqmethylseqcoveragealignmentqualitycontrolimmunooncologycurlbzip2xz-utilszlibcpp
4.4 match 6 stars 8.70 score 79 scripts 1 dependentsbioc
SingleCellAlleleExperiment:S4 Class for Single Cell Data with Allele and Functional Levels for Immune Genes
Defines a S4 class that is based on SingleCellExperiment. In addition to the usual gene layer the object can also store data for immune genes such as HLAs, Igs and KIRs at allele and functional level. The package is part of a workflow named single-cell ImmunoGenomic Diversity (scIGD), that firstly incorporates allele-aware quantification data for immune genes. This new data can then be used with the here implemented data structure and functionalities for further data handling and data analysis.
Maintained by Jonas Schuck. Last updated 2 months ago.
datarepresentationinfrastructuresinglecelltranscriptomicsgeneexpressiongeneticsimmunooncologydataimport
5.7 match 7 stars 6.30 score 12 scriptsbioc
SingleMoleculeFootprinting:Analysis tools for Single Molecule Footprinting (SMF) data
SingleMoleculeFootprinting provides functions to analyze Single Molecule Footprinting (SMF) data. Following the workflow exemplified in its vignette, the user will be able to perform basic data analysis of SMF data with minimal coding effort. Starting from an aligned bam file, we show how to perform quality controls over sequencing libraries, extract methylation information at the single molecule level accounting for the two possible kind of SMF experiments (single enzyme or double enzyme), classify single molecules based on their patterns of molecular occupancy, plot SMF information at a given genomic location.
Maintained by Guido Barzaghi. Last updated 28 days ago.
dnamethylationcoveragenucleosomepositioningdatarepresentationepigeneticsmethylseqqualitycontrolsequencing
5.5 match 2 stars 6.43 score 27 scripts
ropensci
tidyqpcr:Quantitative PCR Analysis with the Tidyverse
For reproducible quantitative PCR (qPCR) analysis building on packages from the ’tidyverse’, notably ’dplyr’ and ’ggplot2’. It normalizes (by ddCq), summarizes, and plots pre-calculated Cq data, and plots raw amplification and melt curves from Roche Lightcycler (tm) machines. It does NOT (yet) calculate Cq data from amplification curves.
Maintained by Edward Wallace. Last updated 11 months ago.
miqeqpcrqpcr-analysistidyverse
6.0 match 54 stars 5.64 score 20 scripts
kestrel99
pmxTools:Pharmacometric and Pharmacokinetic Toolkit
Pharmacometric tools for common data analytical tasks; closed-form solutions for calculating concentrations at given times after dosing based on compartmental PK models (1-compartment, 2-compartment and 3-compartment, covering infusions, zero- and first-order absorption, and lag times, after single doses and at steady state, per Bertrand & Mentre (2008) <http://lixoft.com/wp-content/uploads/2016/03/PKPDlibrary.pdf>); parametric simulation from NONMEM-generated parameter estimates and other output; and parsing, tabulating and plotting results generated by Perl-speaks-NONMEM (PsN).
Maintained by Justin Wilkins. Last updated 7 months ago.
nonmempharmacokineticssimulation
5.3 match 30 stars 6.40 score 84 scripts
griefl
qad:Quantification of Asymmetric Dependence
A copula-based measure for quantifying asymmetry in dependence and associations. Documentation and theory about 'qad' is provided by the paper by Junker, Griessenberger & Trutschnig (2021, <doi:10.1016/j.csda.2020.107058>), and the paper by Trutschnig (2011, <doi:10.1016/j.jmaa.2011.06.013>).
Maintained by Thimo Kasper. Last updated 3 years ago.
7.1 match 4.45 score 19 scripts 1 dependentsbioc
Rsubread:Mapping, quantification and variant analysis of sequencing data
Alignment, quantification and analysis of RNA sequencing data (including both bulk RNA-seq and scRNA-seq) and DNA sequenicng data (including ATAC-seq, ChIP-seq, WGS, WES etc). Includes functionality for read mapping, read counting, SNP calling, structural variant detection and gene fusion discovery. Can be applied to all major sequencing techologies and to both short and long sequence reads.
Maintained by Wei Shi. Last updated 2 days ago.
sequencingalignmentsequencematchingrnaseqchipseqsinglecellgeneexpressiongeneregulationgeneticsimmunooncologysnpgeneticvariabilitypreprocessingqualitycontrolgenomeannotationgenefusiondetectionindeldetectionvariantannotationvariantdetectionmultiplesequencealignmentzlib
3.4 match 9.24 score 892 scripts 10 dependents
ecospat
ecospat:Spatial Ecology Miscellaneous Methods
Collection of R functions and data sets for the support of spatial ecology analyses with a focus on pre, core and post modelling analyses of species distribution, niche quantification and community assembly. Written by current and former members and collaborators of the ecospat group of Antoine Guisan, Department of Ecology and Evolution (DEE) and Institute of Earth Surface Dynamics (IDYST), University of Lausanne, Switzerland. Read Di Cola et al. (2016) <doi:10.1111/ecog.02671> for details.
Maintained by Olivier Broennimann. Last updated 1 months ago.
3.4 match 32 stars 9.35 score 418 scripts 1 dependents
ronkeizer
vpc:Create Visual Predictive Checks
Visual predictive checks are a commonly used diagnostic plot in pharmacometrics, showing how certain statistics (percentiles) for observed data compare to those same statistics for data simulated from a model. The package can generate VPCs for continuous, categorical, censored, and (repeated) time-to-event data.
Maintained by Ron Keizer. Last updated 9 months ago.
3.5 match 36 stars 9.01 score 318 scripts 11 dependentsbioc
MSstatsTMT:Protein Significance Analysis in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling
The package provides statistical tools for detecting differentially abundant proteins in shotgun mass spectrometry-based proteomic experiments with tandem mass tag (TMT) labeling. It provides multiple functionalities, including aata visualization, protein quantification and normalization, and statistical modeling and inference. Furthermore, it is inter-operable with other data processing tools, such as Proteome Discoverer, MaxQuant, OpenMS and SpectroMine.
Maintained by Devon Kohler. Last updated 11 days ago.
immunooncologymassspectrometryproteomicssoftware
4.6 match 6.60 score 35 scripts 3 dependentsbioc
HicAggR:Set of 3D genomic interaction analysis tools
This package provides a set of functions useful in the analysis of 3D genomic interactions. It includes the import of standard HiC data formats into R and HiC normalisation procedures. The main objective of this package is to improve the visualization and quantification of the analysis of HiC contacts through aggregation. The package allows to import 1D genomics data, such as peaks from ATACSeq, ChIPSeq, to create potential couples between features of interest under user-defined parameters such as distance between pairs of features of interest. It allows then the extraction of contact values from the HiC data for these couples and to perform Aggregated Peak Analysis (APA) for visualization, but also to compare normalized contact values between conditions. Overall the package allows to integrate 1D genomics data with 3D genomics data, providing an easy access to HiC contact values.
Maintained by Olivier Cuvier. Last updated 5 months ago.
softwarehicdataimportdatarepresentationnormalizationvisualizationdna3dstructureatacseqchipseqdnaseseqrnaseq
5.9 match 4.90 score 3 scriptsbioc
VaSP:Quantification and Visualization of Variations of Splicing in Population
Discovery of genome-wide variable alternative splicing events from short-read RNA-seq data and visualizations of gene splicing information for publication-quality multi-panel figures in a population. (Warning: The visualizing function is removed due to the dependent package Sushi deprecated. If you want to use it, please change back to an older version.)
Maintained by Huihui Yu. Last updated 5 months ago.
rnaseqalternativesplicingdifferentialsplicingstatisticalmethodvisualizationpreprocessingclusteringdifferentialexpressionkeggimmunooncology3s-scoresalternative-splicingballgownrna-seqsplicingsqtlstatistics
5.9 match 3 stars 4.78 score 3 scriptsbioc
ptairMS:Pre-processing PTR-TOF-MS Data
This package implements a suite of methods to preprocess data from PTR-TOF-MS instruments (HDF5 format) and generates the 'sample by features' table of peak intensities in addition to the sample and feature metadata (as a singl<e ExpressionSet object for subsequent statistical analysis). This package also permit usefull tools for cohorts management as analyzing data progressively, visualization tools and quality control. The steps include calibration, expiration detection, peak detection and quantification, feature alignment, missing value imputation and feature annotation. Applications to exhaled air and cell culture in headspace are described in the vignettes and examples. This package was used for data analysis of Gassin Delyle study on adults undergoing invasive mechanical ventilation in the intensive care unit due to severe COVID-19 or non-COVID-19 acute respiratory distress syndrome (ARDS), and permit to identfy four potentiel biomarquers of the infection.
Maintained by camille Roquencourt. Last updated 5 months ago.
softwaremassspectrometrypreprocessingmetabolomicspeakdetectionalignmentcpp
5.4 match 7 stars 5.15 score 3 scripts
ssnn-airr
shazam:Immunoglobulin Somatic Hypermutation Analysis
Provides a computational framework for analyzing mutations in immunoglobulin (Ig) sequences. Includes methods for Bayesian estimation of antigen-driven selection pressure, mutational load quantification, building of somatic hypermutation (SHM) models, and model-dependent distance calculations. Also includes empirically derived models of SHM for both mice and humans. Citations: Gupta and Vander Heiden, et al (2015) <doi:10.1093/bioinformatics/btv359>, Yaari, et al (2012) <doi:10.1093/nar/gks457>, Yaari, et al (2013) <doi:10.3389/fimmu.2013.00358>, Cui, et al (2016) <doi:10.4049/jimmunol.1502263>.
Maintained by Susanna Marquez. Last updated 2 months ago.
3.6 match 7.43 score 222 scripts 2 dependents
kaiaragaki
qp:A toolkit for analyzing protein quantification results
What the package does (one paragraph).
Maintained by Kai Aragaki. Last updated 10 months ago.
8.8 match 3.00 score 8 scriptsbioc
quantiseqr:Quantification of the Tumor Immune contexture from RNA-seq data
This package provides a streamlined workflow for the quanTIseq method, developed to perform the quantification of the Tumor Immune contexture from RNA-seq data. The quantification is performed against the TIL10 signature (dissecting the contributions of ten immune cell types), carefully crafted from a collection of human RNA-seq samples. The TIL10 signature has been extensively validated using simulated, flow cytometry, and immunohistochemistry data.
Maintained by Federico Marini. Last updated 3 months ago.
geneexpressionsoftwaretranscriptiontranscriptomicssequencingmicroarrayvisualizationannotationimmunooncologyfeatureextractionclassificationstatisticalmethodexperimenthubsoftwareflowcytometry
5.5 match 4.65 score 3 scripts 1 dependentsbioc
FISHalyseR:FISHalyseR a package for automated FISH quantification
FISHalyseR provides functionality to process and analyse digital cell culture images, in particular to quantify FISH probes within nuclei. Furthermore, it extract the spatial location of each nucleus as well as each probe enabling spatial co-localisation analysis.
Maintained by Karesh Arunakirinathan. Last updated 5 months ago.
7.6 match 3.30 score 2 scriptsbioc
alevinQC:Generate QC Reports For Alevin Output
Generate QC reports summarizing the output from an alevin, alevin-fry, or simpleaf run. Reports can be generated as html or pdf files, or as shiny applications.
Maintained by Charlotte Soneson. Last updated 3 months ago.
3.6 match 31 stars 6.89 score 21 scripts
squidgroup
squid:Statistical Quantification of Individual Differences
A simulation-based tool made to help researchers to become familiar with multilevel variations, and to build up sampling designs for their study. This tool has two main objectives: First, it provides an educational tool useful for students, teachers and researchers who want to learn to use mixed-effects models. Users can experience how the mixed-effects model framework can be used to understand distinct biological phenomena by interactively exploring simulated multilevel data. Second, it offers research opportunities to those who are already familiar with mixed-effects models, as it enables the generation of data sets that users may download and use for a range of simulation-based statistical analyses such as power and sensitivity analysis of multilevel and multivariate data [Allegue, H., Araya-Ajoy, Y.G., Dingemanse, N.J., Dochtermann N.A., Garamszegi, L.Z., Nakagawa, S., Reale, D., Schielzeth, H. and Westneat, D.F. (2016) <doi: 10.1111/2041-210X.12659>].
Maintained by Hassen Allegue. Last updated 3 years ago.
linear-mixed-effects-modellingmultilevel-datapersonalityphenotypic-equationphenotypic-plasticityreaction-normrepeatabilitysimulationsvariance-components
4.7 match 34 stars 4.76 score 17 scriptsbioc
tximport:Import and summarize transcript-level estimates for transcript- and gene-level analysis
Imports transcript-level abundance, estimated counts and transcript lengths, and summarizes into matrices for use with downstream gene-level analysis packages. Average transcript length, weighted by sample-specific transcript abundance estimates, is provided as a matrix which can be used as an offset for different expression of gene-level counts.
Maintained by Michael Love. Last updated 5 months ago.
dataimportpreprocessingrnaseqtranscriptomicstranscriptiongeneexpressionimmunooncologybioconductordeseq2
1.7 match 137 stars 12.95 score 2.6k scripts 11 dependentsbioc
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.
immunooncologyinfrastructureproteomicsmassspectrometryqualitycontroldataimportbioconductorbioinformaticsmass-spectrometryproteomics-datavisualisationcpp
1.7 match 130 stars 12.81 score 772 scripts 36 dependents
constantino-garcia
nonlinearTseries:Nonlinear Time Series Analysis
Functions for nonlinear time series analysis. This package permits the computation of the most-used nonlinear statistics/algorithms including generalized correlation dimension, information dimension, largest Lyapunov exponent, sample entropy and Recurrence Quantification Analysis (RQA), among others. Basic routines for surrogate data testing are also included. Part of this work was based on the book "Nonlinear time series analysis" by Holger Kantz and Thomas Schreiber (ISBN: 9780521529020).
Maintained by Constantino A. Garcia. Last updated 6 months ago.
chaoschaotic-systemsnonlinear-dynamicsnonlinear-time-seriestime-seriesopenblascpp
2.4 match 35 stars 8.98 score 123 scripts 7 dependents
bioc
INSPEcT:Modeling RNA synthesis, processing and degradation with RNA-seq data
INSPEcT (INference of Synthesis, Processing and dEgradation rates from Transcriptomic data) RNA-seq data in time-course experiments or steady-state conditions, with or without the support of nascent RNA data.
Maintained by Stefano de Pretis. Last updated 5 months ago.
sequencingrnaseqgeneregulationtimecoursesystemsbiology
4.5 match 4.38 score 9 scripts
dgrun
FateID:Quantification of Fate Bias in Multipotent Progenitors
Application of 'FateID' allows computation and visualization of cell fate bias for multi-lineage single cell transcriptome data. Herman, J.S., Sagar, Grün D. (2018) <DOI:10.1038/nmeth.4662>.
Maintained by Dominic Grün. Last updated 3 years ago.
3.0 match 22 stars 6.50 score 48 scripts 1 dependents
nixtla
nixtlar:A Software Development Kit for 'Nixtla''s 'TimeGPT'
A Software Development Kit for working with 'Nixtla''s 'TimeGPT', a foundation model for time series forecasting. 'API' is an acronym for 'application programming interface'; this package allows users to interact with 'TimeGPT' via the 'API'. You can set and validate 'API' keys and generate forecasts via 'API' calls. It is compatible with 'tsibble' and base R. For more details visit <https://docs.nixtla.io/>.
Maintained by Mariana Menchero. Last updated 28 days ago.
2.4 match 30 stars 8.16 score 38 scriptsbioc
atena:Analysis of Transposable Elements
Quantify expression of transposable elements (TEs) from RNA-seq data through different methods, including ERVmap, TEtranscripts and Telescope. A common interface is provided to use each of these methods, which consists of building a parameter object, calling the quantification function with this object and getting a SummarizedExperiment object as output container of the quantified expression profiles. The implementation allows one to quantify TEs and gene transcripts in an integrated manner.
Maintained by Robert Castelo. Last updated 1 months ago.
transcriptiontranscriptomicsrnaseqsequencingpreprocessingsoftwaregeneexpressioncoveragedifferentialexpressionfunctionalgenomics
3.1 match 10 stars 6.18 score 1 scripts
schochastics
netrankr:Analyzing Partial Rankings in Networks
Implements methods for centrality related analyses of networks. While the package includes the possibility to build more than 20 indices, its main focus lies on index-free assessment of centrality via partial rankings obtained by neighborhood-inclusion or positional dominance. These partial rankings can be analyzed with different methods, including probabilistic methods like computing expected node ranks and relative rank probabilities (how likely is it that a node is more central than another?). The methodology is described in depth in the vignettes and in Schoch (2018) <doi:10.1016/j.socnet.2017.12.003>.
Maintained by David Schoch. Last updated 1 months ago.
network-analysisnetwork-centralityopenblascppopenmp
2.0 match 49 stars 9.56 score 91 scripts 2 dependents
b-cubed-eu
dubicube:Calculation and Interpretation of Data Cube Indicator Uncertainty
This R package provides functions to explore data cubes using simple measures and cross-validation techniques. It can also be used for uncertainty calculation using the bootstrap resampling method, and functionality is provided for efficient interpretation and visualisation of uncertainty related to indicators based on occurrence cubes.
Maintained by Ward Langeraert. Last updated 3 days ago.
biodiversity-indicatorsdata-cubesuncertainty-quantificationuncertainty-visualisation
7.5 match 2.48 score 1 scripts
liukf10
DDPNA:Disease-Drived Differential Proteins Co-Expression Network Analysis
Functions designed to connect disease-related differential proteins and co-expression network. It provides the basic statics analysis included t test, ANOVA analysis. The network construction is not offered by the package, you can used 'WGCNA' package which you can learn in Peter et al. (2008) <doi:10.1186/1471-2105-9-559>. It also provides module analysis included PCA analysis, two enrichment analysis, Planner maximally filtered graph extraction and hub analysis.
Maintained by Kefu Liu. Last updated 3 years ago.
6.1 match 2 stars 3.00 score 4 scripts
stevenvb12
patternize:Quantification of Color Pattern Variation
Quantification of variation in organismal color patterns as obtained from image data. Patternize defines homology between pattern positions across images either through fixed landmarks or image registration. Pattern identification is performed by categorizing the distribution of colors using RGB thresholds or image segmentation.
Maintained by Steven Van Belleghem. Last updated 9 months ago.
3.6 match 31 stars 4.97 score 30 scriptsbioc
transcriptR:An Integrative Tool for ChIP- And RNA-Seq Based Primary Transcripts Detection and Quantification
The differences in the RNA types being sequenced have an impact on the resulting sequencing profiles. mRNA-seq data is enriched with reads derived from exons, while GRO-, nucRNA- and chrRNA-seq demonstrate a substantial broader coverage of both exonic and intronic regions. The presence of intronic reads in GRO-seq type of data makes it possible to use it to computationally identify and quantify all de novo continuous regions of transcription distributed across the genome. This type of data, however, is more challenging to interpret and less common practice compared to mRNA-seq. One of the challenges for primary transcript detection concerns the simultaneous transcription of closely spaced genes, which needs to be properly divided into individually transcribed units. The R package transcriptR combines RNA-seq data with ChIP-seq data of histone modifications that mark active Transcription Start Sites (TSSs), such as, H3K4me3 or H3K9/14Ac to overcome this challenge. The advantage of this approach over the use of, for example, gene annotations is that this approach is data driven and therefore able to deal also with novel and case specific events. Furthermore, the integration of ChIP- and RNA-seq data allows the identification all known and novel active transcription start sites within a given sample.
Maintained by Armen R. Karapetyan. Last updated 5 months ago.
immunooncologytranscriptionsoftwaresequencingrnaseqcoverage
5.5 match 3.30 score 2 scriptsbioc
qsvaR:Generate Quality Surrogate Variable Analysis for Degradation Correction
The qsvaR package contains functions for removing the effect of degration in rna-seq data from postmortem brain tissue. The package is equipped to help users generate principal components associated with degradation. The components can be used in differential expression analysis to remove the effects of degradation.
Maintained by Hedia Tnani. Last updated 3 months ago.
softwareworkflowstepnormalizationbiologicalquestiondifferentialexpressionsequencingcoveragebioconductorbraindegradationhumanqsva
3.4 match 5.26 score 4 scriptsbioc
variancePartition:Quantify and interpret drivers of variation in multilevel gene expression experiments
Quantify and interpret multiple sources of biological and technical variation in gene expression experiments. Uses a linear mixed model to quantify variation in gene expression attributable to individual, tissue, time point, or technical variables. Includes dream differential expression analysis for repeated measures.
Maintained by Gabriel E. Hoffman. Last updated 2 months ago.
rnaseqgeneexpressiongenesetenrichmentdifferentialexpressionbatcheffectqualitycontrolregressionepigeneticsfunctionalgenomicstranscriptomicsnormalizationpreprocessingmicroarrayimmunooncologysoftware
1.5 match 7 stars 11.69 score 1.1k scripts 3 dependents
pmartr
pmartR:Panomics Marketplace - Quality Control and Statistical Analysis for Panomics Data
Provides functionality for quality control processing and statistical analysis of mass spectrometry (MS) omics data, in particular proteomic (either at the peptide or the protein level), lipidomic, and metabolomic data, as well as RNA-seq based count data and nuclear magnetic resonance (NMR) data. This includes data transformation, specification of groups that are to be compared against each other, filtering of features and/or samples, data normalization, data summarization (correlation, PCA), and statistical comparisons between defined groups. Implements methods described in: Webb-Robertson et al. (2014) <doi:10.1074/mcp.M113.030932>. Webb-Robertson et al. (2011) <doi:10.1002/pmic.201100078>. Matzke et al. (2011) <doi:10.1093/bioinformatics/btr479>. Matzke et al. (2013) <doi:10.1002/pmic.201200269>. Polpitiya et al. (2008) <doi:10.1093/bioinformatics/btn217>. Webb-Robertson et al. (2010) <doi:10.1021/pr1005247>.
Maintained by Lisa Bramer. Last updated 3 days ago.
data-summarizationlipidsmass-spectrometrymetabolitesmetabolomics-datapeptidesproteinsrna-seq-analysisopenblascpp
2.3 match 40 stars 7.69 score 144 scripts
ligophorus
FuzzyQ:Fuzzy Quantification of Common and Rare Species
Fuzzy clustering of species in an ecological community as common or rare based on their abundance and occupancy. It also includes functions to compute confidence intervals of classification metrics and plot results. See Balbuena et al. (2020, <doi:10.1101/2020.08.12.247502>).
Maintained by Juan A. Balbuena. Last updated 4 years ago.
6.4 match 2.70 score 7 scripts
andregustavom
mlquantify:Algorithms for Class Distribution Estimation
Quantification is a prominent machine learning task that has received an increasing amount of attention in the last years. The objective is to predict the class distribution of a data sample. This package is a collection of machine learning algorithms for class distribution estimation. This package include algorithms from different paradigms of quantification. These methods are described in the paper: A. Maletzke, W. Hassan, D. dos Reis, and G. Batista. The importance of the test set size in quantification assessment. In Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI20, pages 2640–2646, 2020. <doi:10.24963/ijcai.2020/366>.
Maintained by Andre Maletzke. Last updated 3 years ago.
4.7 match 7 stars 3.54 score 1 scripts
olink-proteomics
OlinkAnalyze:Facilitate Analysis of Proteomic Data from Olink
A collection of functions to facilitate analysis of proteomic data from Olink, primarily NPX data that has been exported from Olink Software. The functions also work on QUANT data from Olink by log- transforming the QUANT data. The functions are focused on reading data, facilitating data wrangling and quality control analysis, performing statistical analysis and generating figures to visualize the results of the statistical analysis. The goal of this package is to help users extract biological insights from proteomic data run on the Olink platform.
Maintained by Kathleen Nevola. Last updated 20 days ago.
olinkproteomicsproteomics-data-analysis
1.7 match 104 stars 9.72 score 61 scriptsbioc
GSVA:Gene Set Variation Analysis for Microarray and RNA-Seq Data
Gene Set Variation Analysis (GSVA) is a non-parametric, unsupervised method for estimating variation of gene set enrichment through the samples of a expression data set. GSVA performs a change in coordinate systems, transforming the data from a gene by sample matrix to a gene-set by sample matrix, thereby allowing the evaluation of pathway enrichment for each sample. This new matrix of GSVA enrichment scores facilitates applying standard analytical methods like functional enrichment, survival analysis, clustering, CNV-pathway analysis or cross-tissue pathway analysis, in a pathway-centric manner.
Maintained by Robert Castelo. Last updated 5 days ago.
functionalgenomicsmicroarrayrnaseqpathwaysgenesetenrichmentgene-set-enrichmentgenomicspathway-enrichment-analysis
1.1 match 210 stars 14.72 score 1.6k scripts 19 dependents
bioc
mspms:Tools for the analysis of MSP-MS data
This package provides functions for the analysis of data generated by the multiplex substrate profiling by mass spectrometry for proteases (MSP-MS) method. Data exported from upstream proteomics software is accepted as input and subsequently processed for analysis. Tools for statistical analysis, visualization, and interpretation of the data are provided.
Maintained by Charlie Bayne. Last updated 3 months ago.
proteomicsmassspectrometrypreprocessingproteaseproteomics-data-analysis
3.3 match 4.95 score 4 scripts
jpquast
protti:Bottom-Up Proteomics and LiP-MS Quality Control and Data Analysis Tools
Useful functions and workflows for proteomics quality control and data analysis of both limited proteolysis-coupled mass spectrometry (LiP-MS) (Feng et. al. (2014) <doi:10.1038/nbt.2999>) and regular bottom-up proteomics experiments. Data generated with search tools such as 'Spectronaut', 'MaxQuant' and 'Proteome Discover' can be easily used due to flexibility of functions.
Maintained by Jan-Philipp Quast. Last updated 5 months ago.
data-analysislip-msmass-spectrometryomicsproteinproteomicssystems-biology
1.9 match 61 stars 8.58 score 83 scriptsbioc
PhosR:A set of methods and tools for comprehensive analysis of phosphoproteomics data
PhosR is a package for the comprenhensive analysis of phosphoproteomic data. There are two major components to PhosR: processing and downstream analysis. PhosR consists of various processing tools for phosphoproteomics data including filtering, imputation, normalisation, and functional analysis for inferring active kinases and signalling pathways.
Maintained by Taiyun Kim. Last updated 5 months ago.
softwareresearchfieldproteomics
3.4 match 4.71 score 51 scripts
gastonstat
plspm:Tools for Partial Least Squares Path Modeling (PLS-PM)
Partial Least Squares Path Modeling (PLS-PM) analysis for both metric and non-metric data, as well as REBUS analysis for latent class detection.
Maintained by Gaston Sanchez. Last updated 3 years ago.
2.3 match 67 stars 6.97 score 115 scripts
hiweller
countcolors:Locates and Counts Pixels Within Color Range(s) in Images
Counts colors within color range(s) in images, and provides a masked version of the image with targeted pixels changed to a different color. Output includes the locations of the pixels in the images, and the proportion of the image within the target color range with optional background masking. Users can specify multiple color ranges for masking.
Maintained by Hannah Weller. Last updated 5 years ago.
2.9 match 10 stars 5.34 score 22 scripts
jranke
chemCal:Calibration Functions for Analytical Chemistry
Simple functions for plotting linear calibration functions and estimating standard errors for measurements according to the Handbook of Chemometrics and Qualimetrics: Part A by Massart et al. (1997) There are also functions estimating the limit of detection (LOD) and limit of quantification (LOQ). The functions work on model objects from - optionally weighted - linear regression (lm) or robust linear regression ('rlm' from the 'MASS' package).
Maintained by Johannes Ranke. Last updated 2 months ago.
2.4 match 6 stars 6.52 score 55 scriptsbioc
Rmmquant:RNA-Seq multi-mapping Reads Quantification Tool
RNA-Seq is currently used routinely, and it provides accurate information on gene transcription. However, the method cannot accurately estimate duplicated genes expression. Several strategies have been previously used, but all of them provide biased results. With Rmmquant, if a read maps at different positions, the tool detects that the corresponding genes are duplicated; it merges the genes and creates a merged gene. The counts of ambiguous reads is then based on the input genes and the merged genes. Rmmquant is a drop-in replacement of the widely used tools findOverlaps and featureCounts that handles multi-mapping reads in an unabiased way.
Maintained by Zytnicki Matthias. Last updated 5 months ago.
geneexpressiontranscriptionzlibcpp
4.5 match 3.30 score 5 scriptskaiaragaki
gplate:A Grammar of Plates
`gplate` attempts to provide a succinct yet powerful grammar to describe common microwell layouts to aide in both plotting and tidying.
Maintained by Kai Aragaki. Last updated 7 months ago.
3.2 match 4 stars 4.56 score 9 scripts 3 dependentsbioc
GRaNIE:GRaNIE: Reconstruction cell type specific gene regulatory networks including enhancers using single-cell or bulk chromatin accessibility and RNA-seq data
Genetic variants associated with diseases often affect non-coding regions, thus likely having a regulatory role. To understand the effects of genetic variants in these regulatory regions, identifying genes that are modulated by specific regulatory elements (REs) is crucial. The effect of gene regulatory elements, such as enhancers, is often cell-type specific, likely because the combinations of transcription factors (TFs) that are regulating a given enhancer have cell-type specific activity. This TF activity can be quantified with existing tools such as diffTF and captures differences in binding of a TF in open chromatin regions. Collectively, this forms a gene regulatory network (GRN) with cell-type and data-specific TF-RE and RE-gene links. Here, we reconstruct such a GRN using single-cell or bulk RNAseq and open chromatin (e.g., using ATACseq or ChIPseq for open chromatin marks) and optionally (Capture) Hi-C data. Our network contains different types of links, connecting TFs to regulatory elements, the latter of which is connected to genes in the vicinity or within the same chromatin domain (TAD). We use a statistical framework to assign empirical FDRs and weights to all links using a permutation-based approach.
Maintained by Christian Arnold. Last updated 5 months ago.
softwaregeneexpressiongeneregulationnetworkinferencegenesetenrichmentbiomedicalinformaticsgeneticstranscriptomicsatacseqrnaseqgraphandnetworkregressiontranscriptionchipseq
2.7 match 5.40 score 24 scriptsbioc
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.
chipseqdifferentialpeakcallingsequencingnormalization
3.6 match 4.00 score 1 scripts
cran
dynRB:Dynamic Range Boxes
Improves the concept of multivariate range boxes, which is highly susceptible for outliers and does not consider the distribution of the data. The package uses dynamic range boxes to overcome these problems.
Maintained by Marco Tschimpke. Last updated 2 years ago.
6.4 match 2.20 score 16 scripts
khvorov45
impactflu:Quantification of Population-Level Impact of Vaccination
Implements the compartment model from Tokars (2018) <doi:10.1016/j.vaccine.2018.10.026>. This enables quantification of population-wide impact of vaccination against vaccine-preventable diseases such as influenza.
Maintained by Arseniy Khvorov. Last updated 4 years ago.
3.5 match 4.00 score 3 scripts
laurabruckman
netSEM:Network Structural Equation Modeling
The network structural equation modeling conducts a network statistical analysis on a data frame of coincident observations of multiple continuous variables [1]. It builds a pathway model by exploring a pool of domain knowledge guided candidate statistical relationships between each of the variable pairs, selecting the 'best fit' on the basis of a specific criteria such as adjusted r-squared value. This material is based upon work supported by the U.S. National Science Foundation Award EEC-2052776 and EEC-2052662 for the MDS-Rely IUCRC Center, under the NSF Solicitation: NSF 20-570 Industry-University Cooperative Research Centers Program [1] Bruckman, Laura S., Nicholas R. Wheeler, Junheng Ma, Ethan Wang, Carl K. Wang, Ivan Chou, Jiayang Sun, and Roger H. French. (2013) <doi:10.1109/ACCESS.2013.2267611>.
Maintained by Laura S. Bruckman. Last updated 2 years ago.
3.8 match 3.72 score 13 scripts
gabrielelubatti
MitoHEAR:Quantification of Mitochondrial DNA Heteroplasmy
R package that allows the estimation and downstream statistical analysis of the mitochondrial DNA Heteroplasmy calculated from single-cell datasets.
Maintained by Gabriele Lubatti. Last updated 3 years ago.
3.1 match 4.45 score 14 scriptsbioc
MPRAnalyze:Statistical Analysis of MPRA data
MPRAnalyze provides statistical framework for the analysis of data generated by Massively Parallel Reporter Assays (MPRAs), used to directly measure enhancer activity. MPRAnalyze can be used for quantification of enhancer activity, classification of active enhancers and comparative analyses of enhancer activity between conditions. MPRAnalyze construct a nested pair of generalized linear models (GLMs) to relate the DNA and RNA observations, easily adjustable to various experimental designs and conditions, and provides a set of rigorous statistical testig schemes.
Maintained by Tal Ashuach. Last updated 5 months ago.
immunooncologysoftwarestatisticalmethodsequencinggeneexpressioncellbiologycellbasedassaysdifferentialexpressionexperimentaldesignclassification
2.0 match 12 stars 6.86 score 30 scripts
kingaa
ouch:Ornstein-Uhlenbeck Models for Phylogenetic Comparative Hypotheses
Fit and compare Ornstein-Uhlenbeck models for evolution along a phylogenetic tree.
Maintained by Aaron A. King. Last updated 4 months ago.
adaptive-regimebrownian-motionornstein-uhlenbeckornstein-uhlenbeck-modelsouchphylogenetic-comparative-hypothesesphylogenetic-comparative-methodsphylogenetic-datareact
2.0 match 15 stars 6.87 score 68 scripts 4 dependentsbioc
GenomicDataCommons:NIH / NCI Genomic Data Commons Access
Programmatically access the NIH / NCI Genomic Data Commons RESTful service.
Maintained by Sean Davis. Last updated 1 months ago.
dataimportsequencingapi-clientbioconductorbioinformaticscancercore-servicesdata-sciencegenomicsncitcgavignette
1.1 match 87 stars 11.94 score 238 scripts 12 dependents
bioc
AlpsNMR:Automated spectraL Processing System for NMR
Reads Bruker NMR data directories both zipped and unzipped. It provides automated and efficient signal processing for untargeted NMR metabolomics. It is able to interpolate the samples, detect outliers, exclude regions, normalize, detect peaks, align the spectra, integrate peaks, manage metadata and visualize the spectra. After spectra proccessing, it can apply multivariate analysis on extracted data. Efficient plotting with 1-D data is also available. Basic reading of 1D ACD/Labs exported JDX samples is also available.
Maintained by Sergio Oller Moreno. Last updated 5 months ago.
softwarepreprocessingvisualizationclassificationcheminformaticsmetabolomicsdataimport
1.8 match 15 stars 7.59 score 12 scripts 1 dependentsbioc
adductomicsR:Processing of adductomic mass spectral datasets
Processes MS2 data to identify potentially adducted peptides from spectra that has been corrected for mass drift and retention time drift and quantifies MS1 level mass spectral peaks.
Maintained by Josie Hayes. Last updated 5 months ago.
massspectrometrymetabolomicssoftwarethirdpartyclientdataimportgui
3.3 match 1 stars 4.00 score 5 scriptsbioc
TargetSearch:A package for the analysis of GC-MS metabolite profiling data
This packages provides a flexible, fast and accurate method for targeted pre-processing of GC-MS data. The user provides a (often very large) set of GC chromatograms and a metabolite library of targets. The package will automatically search those targets in the chromatograms resulting in a data matrix that can be used for further data analysis.
Maintained by Alvaro Cuadros-Inostroza. Last updated 4 months ago.
massspectrometrypreprocessingdecisiontreeimmunooncologybiocbioconductorgc-msmass-spectrometry
1.8 match 4 stars 7.42 score 3 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.
1.9 match 6.79 score 63 scripts 1 dependentsbioc
DifferentialRegulation:Differentially regulated genes from scRNA-seq data
DifferentialRegulation is a method for detecting differentially regulated genes between two groups of samples (e.g., healthy vs. disease, or treated vs. untreated samples), by targeting differences in the balance of spliced and unspliced mRNA abundances, obtained from single-cell RNA-sequencing (scRNA-seq) data. From a mathematical point of view, DifferentialRegulation accounts for the sample-to-sample variability, and embeds multiple samples in a Bayesian hierarchical model. Furthermore, our method also deals with two major sources of mapping uncertainty: i) 'ambiguous' reads, compatible with both spliced and unspliced versions of a gene, and ii) reads mapping to multiple genes. In particular, ambiguous reads are treated separately from spliced and unsplced reads, while reads that are compatible with multiple genes are allocated to the gene of origin. Parameters are inferred via Markov chain Monte Carlo (MCMC) techniques (Metropolis-within-Gibbs).
Maintained by Simone Tiberi. Last updated 5 months ago.
differentialsplicingbayesiangeneticsrnaseqsequencingdifferentialexpressiongeneexpressionmultiplecomparisonsoftwaretranscriptionstatisticalmethodvisualizationsinglecellgenetargetopenblascpp
2.3 match 10 stars 5.30 score 4 scripts
uupharmacometrics
xpose4:Diagnostics for Nonlinear Mixed-Effect Models
A model building aid for nonlinear mixed-effects (population) model analysis using NONMEM, facilitating data set checkout, exploration and visualization, model diagnostics, candidate covariate identification and model comparison. The methods are described in Keizer et al. (2013) <doi:10.1038/psp.2013.24>, and Jonsson et al. (1999) <doi:10.1016/s0169-2607(98)00067-4>.
Maintained by Andrew C. Hooker. Last updated 1 years ago.
diagnosticsnonmempharmacometricspopulation-modelxpose
1.7 match 35 stars 7.30 score 315 scripts
core-bioinformatics
noisyr:Noise Quantification in High Throughput Sequencing Output
Quantifies and removes technical noise from high-throughput sequencing data. Two approaches are used, one based on the count matrix, and one using the alignment BAM files directly. Contains several options for every step of the process, as well as tools to quality check and assess the stability of output.
Maintained by Ilias Moutsopoulos. Last updated 3 years ago.
2.9 match 9 stars 4.13 score 5 scripts 1 dependentsbioc
MADSEQ:Mosaic Aneuploidy Detection and Quantification using Massive Parallel Sequencing Data
The MADSEQ package provides a group of hierarchical Bayeisan models for the detection of mosaic aneuploidy, the inference of the type of aneuploidy and also for the quantification of the fraction of aneuploid cells in the sample.
Maintained by Yu Kong. Last updated 5 months ago.
genomicvariationsomaticmutationvariantdetectionbayesiancopynumbervariationsequencingcoveragejagscpp
3.3 match 4 stars 3.60 score 1 scriptskaiaragaki
amplify:Automate PCR Tasks Reproducibly
PCR tasks - like plate layout planning, dilution calculations, visualization, and analysis - are often repetitive, tedious, prone to error, and poorly documented. amplify seeks to automate these tasks, as well as documenting them (through both code and generated reports) as a bonus.
Maintained by Kai Aragaki. Last updated 5 months ago.
3.1 match 3.78 score 4 scripts
kwb-r
kwb.resilience:R Package for the Quantification of Technical Resilience
kwb.resilience allows quantification of a number of resilience indicators. Calculation requires a time series of performance values of a technical system, as well as values for acceptable and worst case performance.
Maintained by Andreas Matzinger. Last updated 5 years ago.
project-fakinproject-networks4resilience
3.5 match 3.30 score 1 scripts
uncertaintyquantification
FastGaSP:Fast and Exact Computation of Gaussian Stochastic Process
Implements fast and exact computation of Gaussian stochastic process with the Matern kernel using forward filtering and backward smoothing algorithm. It includes efficient implementations of the inverse Kalman filter, with applications such as estimating particle interaction functions. These tools support models with or without noise. Additionally, the package offers algorithms for fast parameter estimation in latent factor models, where the factor loading matrix is orthogonal, and latent processes are modeled by Gaussian processes. See the references: 1) Mengyang Gu and Yanxun Xu (2020), Journal of Computational and Graphical Statistics; 2) Xinyi Fang and Mengyang Gu (2024), <doi:10.48550/arXiv.2407.10089>; 3) Mengyang Gu and Weining Shen (2020), Journal of Machine Learning Research; 4) Yizi Lin, Xubo Liu, Paul Segall and Mengyang Gu (2025), <doi:10.48550/arXiv.2501.01324>.
Maintained by Mengyang Gu. Last updated 1 months ago.
5.1 match 2.18 score 25 scripts 1 dependents
nilsmechtel
MetAlyzer:Read and Analyze 'MetIDQ™' Software Output Files
The 'MetAlyzer' S4 object provides methods to read and reformat metabolomics data for convenient data handling, statistics and downstream analysis. The resulting format corresponds to input data of the Shiny app 'MetaboExtract' (<https://www.metaboextract.shiny.dkfz.de/MetaboExtract/>).
Maintained by Nils Mechtel. Last updated 3 months ago.
2.0 match 3 stars 5.35 score 4 scriptsbioc
scTensor:Detection of cell-cell interaction from single-cell RNA-seq dataset by tensor decomposition
The algorithm is based on the non-negative tucker decomposition (NTD2) of nnTensor.
Maintained by Koki Tsuyuzaki. Last updated 5 months ago.
dimensionreductionsinglecellsoftwaregeneexpression
2.5 match 4.18 score 2 scriptsbioc
BgeeCall:Automatic RNA-Seq present/absent gene expression calls generation
BgeeCall allows to generate present/absent gene expression calls without using an arbitrary cutoff like TPM<1. Calls are generated based on reference intergenic sequences. These sequences are generated based on expression of all RNA-Seq libraries of each species integrated in Bgee (https://bgee.org).
Maintained by Julien Wollbrett. Last updated 5 months ago.
softwaregeneexpressionrnaseqbiologygene-expressiongene-levelintergenic-regionspresent-absent-callsrna-seqrna-seq-librariesscrna-seq
1.8 match 3 stars 5.56 score 9 scripts
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.
brainmrimrsmrshubspectroscopyfortran
1.2 match 25 stars 8.52 score 81 scripts
mooresm
serrsBayes:Bayesian Modelling of Raman Spectroscopy
Sequential Monte Carlo (SMC) algorithms for fitting a generalised additive mixed model (GAMM) to surface-enhanced resonance Raman spectroscopy (SERRS), using the method of Moores et al. (2016) <arXiv:1604.07299>. Multivariate observations of SERRS are highly collinear and lend themselves to a reduced-rank representation. The GAMM separates the SERRS signal into three components: a sequence of Lorentzian, Gaussian, or pseudo-Voigt peaks; a smoothly-varying baseline; and additive white noise. The parameters of each component of the model are estimated iteratively using SMC. The posterior distributions of the parameters given the observed spectra are represented as a population of weighted particles.
Maintained by Matt Moores. Last updated 4 years ago.
bayesianchemometricsramansequential-monte-carlospectroscopycpp
1.8 match 8 stars 5.46 score 36 scriptsbioc
CleanUpRNAseq:Detect and Correct Genomic DNA Contamination in RNA-seq Data
RNA-seq data generated by some library preparation methods, such as rRNA-depletion-based method and the SMART-seq method, might be contaminated by genomic DNA (gDNA), if DNase I disgestion is not performed properly during RNA preparation. CleanUpRNAseq is developed to check if RNA-seq data is suffered from gDNA contamination. If so, it can perform correction for gDNA contamination and reduce false discovery rate of differentially expressed genes.
Maintained by Haibo Liu. Last updated 4 months ago.
qualitycontrolsequencinggeneexpression
1.8 match 5 stars 5.44 score 4 scripts
bioc
yamss:Tools for high-throughput metabolomics
Tools to analyze and visualize high-throughput metabolomics data aquired using chromatography-mass spectrometry. These tools preprocess data in a way that enables reliable and powerful differential analysis. At the core of these methods is a peak detection phase that pools information across all samples simultaneously. This is in contrast to other methods that detect peaks in a sample-by-sample basis.
Maintained by Leslie Myint. Last updated 5 months ago.
massspectrometrymetabolomicspeakdetectionsoftware
1.7 match 3 stars 5.08 score 9 scriptsuncertaintyquantification
AIUQ:Ab Initio Uncertainty Quantification
Uncertainty quantification and inverse estimation by probabilistic generative models from the beginning of the data analysis. An example is a Fourier basis method for inverse estimation in scattering analysis of microscopy videos. It does not require specifying a certain range of Fourier bases and it substantially reduces computational cost via the generalized Schur algorithm. See the reference: Mengyang Gu, Yue He, Xubo Liu and Yimin Luo (2023), <doi:10.48550/arXiv.2309.02468>.
Maintained by Mengyang Gu. Last updated 9 months ago.
3.6 match 2.30 score 1 scriptsbioc
ddCt:The ddCt Algorithm for the Analysis of Quantitative Real-Time PCR (qRT-PCR)
The Delta-Delta-Ct (ddCt) Algorithm is an approximation method to determine relative gene expression with quantitative real-time PCR (qRT-PCR) experiments. Compared to other approaches, it requires no standard curve for each primer-target pair, therefore reducing the working load and yet returning accurate enough results as long as the assumptions of the amplification efficiency hold. The ddCt package implements a pipeline to collect, analyse and visualize qRT-PCR results, for example those from TaqMan SDM software, mainly using the ddCt method. The pipeline can be either invoked by a script in command-line or through the API consisting of S4-Classes, methods and functions.
Maintained by Jitao David Zhang. Last updated 5 months ago.
geneexpressiondifferentialexpressionmicrotitreplateassayqpcr
1.9 match 4.38 score 8 scriptscran
CB2:CRISPR Pooled Screen Analysis using Beta-Binomial Test
Provides functions for hit gene identification and quantification of sgRNA (single-guided RNA) abundances for CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) pooled screen data analysis. Details are in Jeong et al. (2019) <doi:10.1101/gr.245571.118> and Baggerly et al. (2003) <doi:10.1093/bioinformatics/btg173>.
Maintained by Hyun-Hwan Jeong. Last updated 5 years ago.
2.2 match 3.60 score 40 scripts
benbruyneel
proteinDiscover:ProteinDiscover
Provides an interface to the data contained in Proteome Discoverer (Thermo Scientific) results.
Maintained by Ben Bruyneel. Last updated 1 years ago.
mass-spectrometryproteomicsproteomics-data-analysis
2.7 match 2 stars 3.00 score 2 scriptsbioc
srnadiff:Finding differentially expressed unannotated genomic regions from RNA-seq data
srnadiff is a package that finds differently expressed regions from RNA-seq data at base-resolution level without relying on existing annotation. To do so, the package implements the identify-then-annotate methodology that builds on the idea of combining two pipelines approachs differential expressed regions detection and differential expression quantification. It reads BAM files as input, and outputs a list differentially regions, together with the adjusted p-values.
Maintained by Zytnicki Matthias. Last updated 2 months ago.
immunooncologygeneexpressioncoveragesmallrnaepigeneticsstatisticalmethodpreprocessingdifferentialexpressioncpp
2.0 match 3.70 score 3 scripts
maressyl
LPS:Linear Predictor Score, for Binary Inference from Multiple Continuous Variables
An implementation of the Linear Predictor Score approach, as initiated by Radmacher et al. (J Comput Biol 2001) and enhanced by Wright et al. (PNAS 2003) for gene expression signatures. Several tools for unsupervised clustering of gene expression data are also provided.
Maintained by Sylvain Mareschal. Last updated 4 years ago.
1.9 match 1 stars 3.74 score 11 scriptsbioc
ivygapSE:A SummarizedExperiment for Ivy-GAP data
Define a SummarizedExperiment and exploratory app for Ivy-GAP glioblastoma image, expression, and clinical data.
Maintained by VJ Carey. Last updated 5 months ago.
transcriptionsoftwarevisualizationsurvivalgeneexpressionsequencing
1.7 match 4.20 score 16 scripts
dplecko
fairadapt:Fair Data Adaptation with Quantile Preservation
An implementation of the fair data adaptation with quantile preservation described in Plecko & Meinshausen (2019) <arXiv:1911.06685>. The adaptation procedure uses the specified causal graph to pre-process the given training and testing data in such a way to remove the bias caused by the protected attribute. The procedure uses tree ensembles for quantile regression.
Maintained by Drago Plecko. Last updated 2 years ago.
causal-inferencefairnessmachine-learning
1.5 match 2 stars 4.63 score 43 scriptsbioc
limpca:An R package for the linear modeling of high-dimensional designed data based on ASCA/APCA family of methods
This package has for objectives to provide a method to make Linear Models for high-dimensional designed data. limpca applies a GLM (General Linear Model) version of ASCA and APCA to analyse multivariate sample profiles generated by an experimental design. ASCA/APCA provide powerful visualization tools for multivariate structures in the space of each effect of the statistical model linked to the experimental design and contrarily to MANOVA, it can deal with mutlivariate datasets having more variables than observations. This method can handle unbalanced design.
Maintained by Manon Martin. Last updated 5 months ago.
statisticalmethodprincipalcomponentregressionvisualizationexperimentaldesignmultiplecomparisongeneexpressionmetabolomics
1.2 match 2 stars 5.73 score 2 scriptscran
riskSimul:Risk Quantification for Stock Portfolios under the T-Copula Model
Implements efficient simulation procedures to estimate tail loss probabilities and conditional excess for a stock portfolio. The log-returns are assumed to follow a t-copula model with generalized hyperbolic or t marginals.
Maintained by Wolfgang Hormann. Last updated 1 years ago.
4.6 match 3 stars 1.48 score 2 scriptsbioc
cfdnakit:Fragmen-length analysis package from high-throughput sequencing of cell-free DNA (cfDNA)
This package provides basic functions for analyzing shallow whole-genome sequencing (~0.3X or more) of cell-free DNA (cfDNA). The package basically extracts the length of cfDNA fragments and aids the vistualization of fragment-length information. The package also extract fragment-length information per non-overlapping fixed-sized bins and used it for calculating ctDNA estimation score (CES).
Maintained by Pitithat Puranachot. Last updated 5 months ago.
copynumbervariationsequencingwholegenome
1.3 match 8 stars 5.20 score 8 scripts
fpaskali
LFApp:Shiny Apps for Lateral Flow Assays
Shiny apps for the quantitative analysis of images from lateral flow assays (LFAs). The images are segmented and background corrected and color intensities are extracted. The apps can be used to import and export intensity data and to calibrate LFAs by means of linear, loess, or gam models. The calibration models can further be saved and applied to intensity data from new images for determining concentrations.
Maintained by Filip Paskali. Last updated 10 months ago.
calibrationimage-processingmedical-image-processingshiny
1.3 match 3 stars 4.78 score 2 scriptscran
phoenics:Pathways Longitudinal and Differential Analysis in Metabolomics
Perform a differential analysis at pathway level based on metabolite quantifications and information on pathway metabolite composition. The method is based on a Principal Component Analysis step and on a linear mixed model. Automatic query of metabolic pathways is also implemented.
Maintained by Camille Guilmineau. Last updated 2 months ago.
2.3 match 2.70 scorebioc
fishpond:Fishpond: downstream methods and tools for expression data
Fishpond contains methods for differential transcript and gene expression analysis of RNA-seq data using inferential replicates for uncertainty of abundance quantification, as generated by Gibbs sampling or bootstrap sampling. Also the package contains a number of utilities for working with Salmon and Alevin quantification files.
Maintained by Michael Love. Last updated 5 months ago.
sequencingrnaseqgeneexpressiontranscriptionnormalizationregressionmultiplecomparisonbatcheffectvisualizationdifferentialexpressiondifferentialsplicingalternativesplicingsinglecellbioconductorgene-expressiongenomicssalmonscrnaseqstatisticstranscriptomics
0.8 match 28 stars 7.83 score 150 scriptsbioc
MSstatsPTM:Statistical Characterization of Post-translational Modifications
MSstatsPTM provides general statistical methods for quantitative characterization of post-translational modifications (PTMs). Supports DDA, DIA, SRM, and tandem mass tag (TMT) labeling. Typically, the analysis involves the quantification of PTM sites (i.e., modified residues) and their corresponding proteins, as well as the integration of the quantification results. MSstatsPTM provides functions for summarization, estimation of PTM site abundance, and detection of changes in PTMs across experimental conditions.
Maintained by Devon Kohler. Last updated 4 months ago.
immunooncologymassspectrometryproteomicssoftwaredifferentialexpressiononechanneltwochannelnormalizationqualitycontrolpost-translational-modificationcpp
0.8 match 10 stars 7.98 score 36 scripts 2 dependentsbioc
ddPCRclust:Clustering algorithm for ddPCR data
The ddPCRclust algorithm can automatically quantify the CPDs of non-orthogonal ddPCR reactions with up to four targets. In order to determine the correct droplet count for each target, it is crucial to both identify all clusters and label them correctly based on their position. For more information on what data can be analyzed and how a template needs to be formatted, please check the vignette.
Maintained by Benedikt G. Brink. Last updated 5 months ago.
ddpcrclusteringbiological-data-analysis
1.7 match 4 stars 3.60 score 4 scriptscran
PepMapViz:A Versatile Toolkit for Peptide Mapping, Visualization, and Comparative Exploration
A versatile R visualization package that empowers researchers with comprehensive visualization tools for seamlessly mapping peptides to protein sequences, identifying distinct domains and regions of interest, accentuating mutations, and highlighting post-translational modifications, all while enabling comparisons across diverse experimental conditions. Potential applications of 'PepMapViz' include the visualization of cross-software mass spectrometry results at the peptide level for specific protein and domain details in a linearized format and post-translational modification coverage across different experimental conditions; unraveling insights into disease mechanisms. It also enables visualization of major histocompatibility complex-presented peptides in different antibody regions predicting immunogenicity in antibody drug development.
Maintained by Zhenru Zhou. Last updated 4 months ago.
immunogenicitymassspectrometryproteomicspeptidomicssoftwarevisualization
2.3 match 2.70 score
aljensen89
CommKern:Network-Based Communities and Kernel Machine Methods
Analysis of network community objects with applications to neuroimaging data. There are two main components to this package. The first is the hierarchical multimodal spinglass (HMS) algorithm, which is a novel community detection algorithm specifically tailored to the unique issues within brain connectivity. The other is a suite of semiparametric kernel machine methods that allow for statistical inference to be performed to test for potential associations between these community structures and an outcome of interest (binary or continuous).
Maintained by Alexandria Jensen. Last updated 2 years ago.
1.3 match 4.11 score 26 scriptscran
qmd:Quantification of Multivariate Dependence
A multivariate copula-based dependence measure. For more information, see Griessenberger, Junker, Trutschnig (2022), On a multivariate copula-based dependence measure and its estimation, Electronic Journal of Statistics, 16, 2206-2251.
Maintained by Nicolas Dietrich. Last updated 3 years ago.
5.3 match 1.00 scorebioc
BASiCS:Bayesian Analysis of Single-Cell Sequencing data
Single-cell mRNA sequencing can uncover novel cell-to-cell heterogeneity in gene expression levels in seemingly homogeneous populations of cells. However, these experiments are prone to high levels of technical noise, creating new challenges for identifying genes that show genuine heterogeneous expression within the population of cells under study. BASiCS (Bayesian Analysis of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model to perform statistical analyses of single-cell RNA sequencing datasets in the context of supervised experiments (where the groups of cells of interest are known a priori, e.g. experimental conditions or cell types). BASiCS performs built-in data normalisation (global scaling) and technical noise quantification (based on spike-in genes). BASiCS provides an intuitive detection criterion for highly (or lowly) variable genes within a single group of cells. Additionally, BASiCS can compare gene expression patterns between two or more pre-specified groups of cells. Unlike traditional differential expression tools, BASiCS quantifies changes in expression that lie beyond comparisons of means, also allowing the study of changes in cell-to-cell heterogeneity. The latter can be quantified via a biological over-dispersion parameter that measures the excess of variability that is observed with respect to Poisson sampling noise, after normalisation and technical noise removal. Due to the strong mean/over-dispersion confounding that is typically observed for scRNA-seq datasets, BASiCS also tests for changes in residual over-dispersion, defined by residual values with respect to a global mean/over-dispersion trend.
Maintained by Catalina Vallejos. Last updated 5 months ago.
immunooncologynormalizationsequencingrnaseqsoftwaregeneexpressiontranscriptomicssinglecelldifferentialexpressionbayesiancellbiologybioconductor-packagegene-expressionrcpprcpparmadilloscrna-seqsingle-cellopenblascppopenmp
0.5 match 83 stars 10.26 score 368 scripts 1 dependents
mlysy
optimCheck:Graphical and Numerical Checks for Mode-Finding Routines
Tools for checking that the output of an optimization algorithm is indeed at a local mode of the objective function. This is accomplished graphically by calculating all one-dimensional "projection plots" of the objective function, i.e., varying each input variable one at a time with all other elements of the potential solution being fixed. The numerical values in these plots can be readily extracted for the purpose of automated and systematic unit-testing of optimization routines.
Maintained by Martin Lysy. Last updated 6 months ago.
1.3 match 1 stars 3.70 score 1 scriptsbioc
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.
chipseqdataimportsequencingchiponchipcoverage
1.2 match 4.03 score 54 scriptsbioc
GladiaTOX:R Package for Processing High Content Screening data
GladiaTOX R package is an open-source, flexible solution to high-content screening data processing and reporting in biomedical research. GladiaTOX takes advantage of the tcpl core functionalities and provides a number of extensions: it provides a web-service solution to fetch raw data; it computes severity scores and exports ToxPi formatted files; furthermore it contains a suite of functionalities to generate pdf reports for quality control and data processing.
Maintained by PMP S.A. R Support. Last updated 5 months ago.
softwareworkflowstepnormalizationpreprocessingqualitycontrol
1.2 match 4.00 score 2 scriptscran
econet:Estimation of Parameter-Dependent Network Centrality Measures
Provides methods for estimating parameter-dependent network centrality measures with linear-in-means models. Both non linear least squares and maximum likelihood estimators are implemented. The methods allow for both link and node heterogeneity in network effects, endogenous network formation and the presence of unconnected nodes. The routines also compare the explanatory power of parameter-dependent network centrality measures with those of standard measures of network centrality. Benefits and features of the 'econet' package are illustrated using data from Battaglini and Patacchini (2018) and Battaglini, Patacchini, and Leone Sciabolazza (2020). For additional details, see the vignette <doi:10.18637/jss.v102.i08>.
Maintained by Valerio Leone Sciabolazza. Last updated 8 months ago.
1.7 match 1 stars 2.70 score
bhaibeka
SIGN:Similarity Identification in Gene Expression
Provides a classification framework to use expression patterns of pathways as features to identify similarity between biological samples. It provides a new measure for quantifying similarity between expression patterns of pathways.
Maintained by Benjamin Haibe-Kains. Last updated 6 years ago.
geneexpressionclassificationclusteringsurvival
1.6 match 2.70 score 3 scriptsbioc
SPIAT:Spatial Image Analysis of Tissues
SPIAT (**Sp**atial **I**mage **A**nalysis of **T**issues) is an R package with a suite of data processing, quality control, visualization and data analysis tools. SPIAT is compatible with data generated from single-cell spatial proteomics platforms (e.g. OPAL, CODEX, MIBI, cellprofiler). SPIAT reads spatial data in the form of X and Y coordinates of cells, marker intensities and cell phenotypes. SPIAT includes six analysis modules that allow visualization, calculation of cell colocalization, categorization of the immune microenvironment relative to tumor areas, analysis of cellular neighborhoods, and the quantification of spatial heterogeneity, providing a comprehensive toolkit for spatial data analysis.
Maintained by Yuzhou Feng. Last updated 14 hours ago.
biomedicalinformaticscellbiologyspatialclusteringdataimportimmunooncologyqualitycontrolsinglecellsoftwarevisualization
0.5 match 22 stars 8.59 score 69 scriptsbioc
DEqMS:a tool to perform statistical analysis of differential protein expression for quantitative proteomics data.
DEqMS is developped on top of Limma. However, Limma assumes same prior variance for all genes. In proteomics, the accuracy of protein abundance estimates varies by the number of peptides/PSMs quantified in both label-free and labelled data. Proteins quantification by multiple peptides or PSMs are more accurate. DEqMS package is able to estimate different prior variances for proteins quantified by different number of PSMs/peptides, therefore acchieving better accuracy. The package can be applied to analyze both label-free and labelled proteomics data.
Maintained by Yafeng Zhu. Last updated 5 months ago.
immunooncologyproteomicsmassspectrometrypreprocessingdifferentialexpressionmultiplecomparisonnormalizationbayesianexperimenthubsoftwarelimmaquantitative-proteomic-analysis
0.5 match 23 stars 8.18 score 58 scripts 1 dependents
josemaga
stabilo:Stabilometric Signal Quantification
Functions for stabilometric signal quantification. The input is a data frame containing the x, y coordinates of the center-of-pressure displacement. Jose Magalhaes de Oliveira (2017) <doi:10.3758/s13428-016-0706-4> "Statokinesigram normalization method"; T E Prieto, J B Myklebust, R G Hoffmann, E G Lovett, B M Myklebust (1996) <doi:10.1109/10.532130> "Measures of postural steadiness: Differences between healthy young and elderly adults"; L F Oliveira et al (1996) <doi:10.1088/0967-3334/17/4/008> "Calculation of area of stabilometric signals using principal component analisys".
Maintained by Jose Oliveira. Last updated 2 years ago.
3.8 match 1.00 score
pasraia
RRphylo:Phylogenetic Ridge Regression Methods for Comparative Studies
Functions for phylogenetic analysis (Castiglione et al., 2018 <doi:10.1111/2041-210X.12954>). The functions perform the estimation of phenotypic evolutionary rates, identification of phenotypic evolutionary rate shifts, quantification of direction and size of evolutionary change in multivariate traits, the computation of ontogenetic shape vectors and test for morphological convergence.
Maintained by Silvia Castiglione. Last updated 7 months ago.
0.5 match 10 stars 7.48 score 83 scriptsbioc
SpatialDecon:Deconvolution of mixed cells from spatial and/or bulk gene expression data
Using spatial or bulk gene expression data, estimates abundance of mixed cell types within each observation. Based on "Advances in mixed cell deconvolution enable quantification of cell types in spatial transcriptomic data", Danaher (2022). Designed for use with the NanoString GeoMx platform, but applicable to any gene expression data.
Maintained by Maddy Griswold. Last updated 5 months ago.
immunooncologyfeatureextractiongeneexpressiontranscriptomicsspatial
0.5 match 36 stars 7.40 score 58 scriptsbioc
CAGEfightR:Analysis of Cap Analysis of Gene Expression (CAGE) data using Bioconductor
CAGE is a widely used high throughput assay for measuring transcription start site (TSS) activity. CAGEfightR is an R/Bioconductor package for performing a wide range of common data analysis tasks for CAGE and 5'-end data in general. Core functionality includes: import of CAGE TSSs (CTSSs), tag (or unidirectional) clustering for TSS identification, bidirectional clustering for enhancer identification, annotation with transcript and gene models, correlation of TSS and enhancer expression, calculation of TSS shapes, quantification of CAGE expression as expression matrices and genome brower visualization.
Maintained by Malte Thodberg. Last updated 5 months ago.
softwaretranscriptioncoveragegeneexpressiongeneregulationpeakdetectiondataimportdatarepresentationtranscriptomicssequencingannotationgenomebrowsersnormalizationpreprocessingvisualization
0.5 match 8 stars 7.46 score 67 scripts 1 dependents
insightsengineering
goshawk:Longitudinal Visualization Functions
Functions that plot and summarize biomarkers/labs of interest. Visualizations include: box plot, correlation plot, density distribution, line plot and spaghetti plot. Data are expected in ADaM structure. Requires analysis subject level (ADSL) and analysis laboratory (ADLB) data sets. Beyond core variables, Limit of Quantification flag variable (LOQFL) is expected with levels 'Y', 'N' or NA.
Maintained by Nick Paszty. Last updated 20 days ago.
0.5 match 5 stars 6.67 score 1 dependents
nepem-ufsc
pliman:Tools for Plant Image Analysis
Tools for both single and batch image manipulation and analysis (Olivoto, 2022 <doi:10.1111/2041-210X.13803>) and phytopathometry (Olivoto et al., 2022 <doi:10.1007/S40858-021-00487-5>). The tools can be used for the quantification of leaf area, object counting, extraction of image indexes, shape measurement, object landmark identification, and Elliptical Fourier Analysis of object outlines (Claude (2008) <doi:10.1007/978-0-387-77789-4>). The package also provides a comprehensive pipeline for generating shapefiles with complex layouts and supports high-throughput phenotyping of RGB, multispectral, and hyperspectral orthomosaics. This functionality facilitates field phenotyping using UAV- or satellite-based imagery.
Maintained by Tiago Olivoto. Last updated 2 days ago.
0.5 match 10 stars 6.68 score 476 scriptsinsightsengineering
teal.goshawk:Longitudinal Visualization `teal` Modules
Modules that produce web interfaces through which longitudinal visualizations can be dynamically modified and displayed. These included box plot, correlation plot, density distribution plot, line plot, scatter plot and spaghetti plot with accompanying summary. Data are expected in ADaM structure. Requires analysis subject level (ADSL) and analysis laboratory (ADLB) data sets. Beyond core variables, Limit of Quantification flag variable (LOQFL) is expected with levels 'Y', 'N' or NA.
Maintained by Nick Paszty. Last updated 19 days ago.
0.5 match 3 stars 6.59 score 2 scriptsbioc
PRONE:The PROteomics Normalization Evaluator
High-throughput omics data are often affected by systematic biases introduced throughout all the steps of a clinical study, from sample collection to quantification. Normalization methods aim to adjust for these biases to make the actual biological signal more prominent. However, selecting an appropriate normalization method is challenging due to the wide range of available approaches. Therefore, a comparative evaluation of unnormalized and normalized data is essential in identifying an appropriate normalization strategy for a specific data set. This R package provides different functions for preprocessing, normalizing, and evaluating different normalization approaches. Furthermore, normalization methods can be evaluated on downstream steps, such as differential expression analysis and statistical enrichment analysis. Spike-in data sets with known ground truth and real-world data sets of biological experiments acquired by either tandem mass tag (TMT) or label-free quantification (LFQ) can be analyzed.
Maintained by Lis Arend. Last updated 17 days ago.
proteomicspreprocessingnormalizationdifferentialexpressionvisualizationdata-analysisevaluation
0.8 match 2 stars 4.38 score 9 scripts
marmalade-icecream
lifecourse:Quantification of Lifecourse Fluidity
Provides in built datasets and three functions. These functions are mobility_index, nonStanTest and linkedLives. The mobility_index function facilitates the calculation of lifecourse fluidity, whilst the nonStanTest and the linkedLives functions allow the user to determine the probability that the observed sequence data was due to chance. The linkedLives function acknowledges the fact that some individuals may have identical sequences. The datasets available provide sequence data on marital status(maritalData) and mobility (mydata) for a selected group of individuals from the British Household Panel Study (BHPS). In addition, personal and house ID's for 100 individuals are provided in a third dataset (myHouseID) from the BHPS.
Maintained by Glenna Nightingale. Last updated 9 years ago.
3.3 match 1.00 score 7 scripts
brauckhoff
biopixR:Extracting Insights from Biological Images
Combines the 'magick' and 'imager' packages to streamline image analysis, focusing on feature extraction and quantification from biological images, especially microparticles. By providing high throughput pipelines and clustering capabilities, 'biopixR' facilitates efficient insight generation for researchers (Schneider J. et al. (2019) <doi:10.21037/jlpm.2019.04.05>).
Maintained by Tim Brauckhoff. Last updated 4 months ago.
0.5 match 5 stars 6.36 score 23 scripts
zsteinmetz
envalysis:Miscellaneous Functions for Environmental Analyses
Small toolbox for data analyses in environmental chemistry and ecotoxicology. Provides, for example, calibration() to calculate calibration curves and corresponding limits of detection (LODs) and limits of quantification (LOQs) according to German DIN 32645 (2008). texture() makes it easy to estimate soil particle size distributions from hydrometer measurements (ASTM D422-63, 2007).
Maintained by Zacharias Steinmetz. Last updated 5 months ago.
analyticschemistryecotoxicologyenvironmentsoil
0.5 match 8 stars 6.30 score 83 scripts
bioc
esATAC:An Easy-to-use Systematic pipeline for ATACseq data analysis
This package provides a framework and complete preset pipeline for quantification and analysis of ATAC-seq Reads. It covers raw sequencing reads preprocessing (FASTQ files), reads alignment (Rbowtie2), aligned reads file operations (SAM, BAM, and BED files), peak calling (F-seq), genome annotations (Motif, GO, SNP analysis) and quality control report. The package is managed by dataflow graph. It is easy for user to pass variables seamlessly between processes and understand the workflow. Users can process FASTQ files through end-to-end preset pipeline which produces a pretty HTML report for quality control and preliminary statistical results, or customize workflow starting from any intermediate stages with esATAC functions easily and flexibly.
Maintained by Zheng Wei. Last updated 5 months ago.
immunooncologysequencingdnaseqqualitycontrolalignmentpreprocessingcoverageatacseqdnaseseqatac-seqbioconductorpipelinecppopenjdk
0.5 match 23 stars 6.11 score 3 scripts
bsynth:Bayesian Synthetic Control
Implements the Bayesian Synthetic Control method for causal inference in comparative case studies. This package provides tools for estimating treatment effects in settings with a single treated unit and multiple control units, allowing for uncertainty quantification and flexible modeling of time-varying effects. The methodology is based on the paper by Vives and Martinez (2022) <doi:10.48550/arXiv.2206.01779>.
Maintained by Ignacio Martinez. Last updated 5 hours ago.
0.5 match 18 stars 6.03 score 4 scripts
mbinois
GPareto:Gaussian Processes for Pareto Front Estimation and Optimization
Gaussian process regression models, a.k.a. Kriging models, are applied to global multi-objective optimization of black-box functions. Multi-objective Expected Improvement and Step-wise Uncertainty Reduction sequential infill criteria are available. A quantification of uncertainty on Pareto fronts is provided using conditional simulations.
Maintained by Mickael Binois. Last updated 1 years ago.
0.5 match 16 stars 5.96 score 38 scripts 1 dependents
biooss
mistral:Methods in Structural Reliability
Various reliability analysis methods for rare event inference (computing failure probability and quantile from model/function outputs).
Maintained by Bertrand Iooss. Last updated 1 years ago.
1.3 match 1 stars 2.43 score 27 scriptsbioc
Statial:A package to identify changes in cell state relative to spatial associations
Statial is a suite of functions for identifying changes in cell state. The functionality provided by Statial provides robust quantification of cell type localisation which are invariant to changes in tissue structure. In addition to this Statial uncovers changes in marker expression associated with varying levels of localisation. These features can be used to explore how the structure and function of different cell types may be altered by the agents they are surrounded with.
Maintained by Farhan Ameen. Last updated 5 months ago.
singlecellspatialclassificationsingle-cell
0.5 match 5 stars 5.49 score 23 scriptsbioc
VDJdive:Analysis Tools for 10X V(D)J Data
This package provides functions for handling and analyzing immune receptor repertoire data, such as produced by the CellRanger V(D)J pipeline. This includes reading the data into R, merging it with paired single-cell data, quantifying clonotype abundances, calculating diversity metrics, and producing common plots. It implements the E-M Algorithm for clonotype assignment, along with other methods, which makes use of ambiguous cells for improved quantification.
Maintained by Kelly Street. Last updated 5 months ago.
softwareimmunooncologysinglecellannotationrnaseqtargetedresequencingcpp
0.5 match 7 stars 5.32 score 1 scripts
bhelsel
agcounts:Calculate 'ActiGraph' Counts from Accelerometer Data
Calculate 'ActiGraph' counts from the X, Y, and Z axes of a triaxial accelerometer. This work was inspired by Neishabouri et al. who published the article "Quantification of Acceleration as Activity Counts in 'ActiGraph' Wearables" on February 24, 2022. The link to the article (<https://pubmed.ncbi.nlm.nih.gov/35831446>) and 'python' implementation of this code (<https://github.com/actigraph/agcounts>).
Maintained by Brian C. Helsel. Last updated 9 months ago.
0.5 match 10 stars 5.10 score 10 scripts
l-a-yates
cpam:Changepoint Additive Models for Time Series Omics Data
Provides a comprehensive framework for time series omics analysis, integrating changepoint detection, smooth and shape-constrained trends, and uncertainty quantification. It supports gene- and transcript-level inferences, p-value aggregation for improved power, and both case-only and case-control designs. It includes an interactive 'shiny' interface. The methods are described in Yates et al. (2024) <doi:10.1101/2024.12.22.630003>.
Maintained by Luke Yates. Last updated 3 days ago.
0.5 match 1 stars 5.06 scorebioc
ribosomeProfilingQC:Ribosome Profiling Quality Control
Ribo-Seq (also named ribosome profiling or footprinting) measures translatome (unlike RNA-Seq, which sequences the transcriptome) by direct quantification of the ribosome-protected fragments (RPFs). This package provides the tools for quality assessment of ribosome profiling. In addition, it can preprocess Ribo-Seq data for subsequent differential analysis.
Maintained by Jianhong Ou. Last updated 1 months ago.
riboseqsequencinggeneregulationqualitycontrolvisualizationcoverage
0.5 match 4.88 score 17 scriptsdgrun
RaceID:Identification of Cell Types, Inference of Lineage Trees, and Prediction of Noise Dynamics from Single-Cell RNA-Seq Data
Application of 'RaceID' allows inference of cell types and prediction of lineage trees by the 'StemID2' algorithm (Herman, J.S., Sagar, Grun D. (2018) <DOI:10.1038/nmeth.4662>). 'VarID2' is part of this package and allows quantification of biological gene expression noise at single-cell resolution (Rosales-Alvarez, R.E., Rettkowski, J., Herman, J.S., Dumbovic, G., Cabezas-Wallscheid, N., Grun, D. (2023) <DOI:10.1186/s13059-023-02974-1>).
Maintained by Dominic Grün. Last updated 4 months ago.
0.5 match 4.74 score 110 scripts
hpetren
chemodiv:Analysing Chemodiversity of Phytochemical Data
Quantify and visualise various measures of chemical diversity and dissimilarity, for phytochemical compounds and other sets of chemical composition data. Importantly, these measures can incorporate biosynthetic and/or structural properties of the chemical compounds, resulting in a more comprehensive quantification of diversity and dissimilarity. For details, see Petrén, Köllner and Junker (2023) <doi:10.1111/nph.18685>.
Maintained by Hampus Petrén. Last updated 2 years ago.
0.5 match 5 stars 4.57 score 15 scripts
mkomod
survival.svb:Fit High-Dimensional Proportional Hazards Models
Implementation of methodology designed to perform: (i) variable selection, (ii) effect estimation, and (iii) uncertainty quantification, for high-dimensional survival data. Our method uses a spike-and-slab prior with Laplace slab and Dirac spike and approximates the corresponding posterior using variational inference, a popular method in machine learning for scalable conditional inference. Although approximate, the variational posterior provides excellent point estimates and good control of the false discovery rate. For more information see Komodromos et al. (2021) <arXiv:2112.10270>.
Maintained by Michael Komodromos. Last updated 3 years ago.
bayesgene-expressionproportional-hazardssurvival-analysisvariational-inferencecpp
0.5 match 7 stars 4.54 score 4 scriptsbioc
cosmiq:cosmiq - COmbining Single Masses Into Quantities
cosmiq is a tool for the preprocessing of liquid- or gas - chromatography mass spectrometry (LCMS/GCMS) data with a focus on metabolomics or lipidomics applications. To improve the detection of low abundant signals, cosmiq generates master maps of the mZ/RT space from all acquired runs before a peak detection algorithm is applied. The result is a more robust identification and quantification of low-intensity MS signals compared to conventional approaches where peak picking is performed in each LCMS/GCMS file separately. The cosmiq package builds on the xcmsSet object structure and can be therefore integrated well with the package xcms as an alternative preprocessing step.
Maintained by David Fischer. Last updated 5 months ago.
immunooncologymassspectrometrymetabolomics
0.5 match 4.48 score 2 scripts
ijaljuli
metarep:Replicability-Analysis Tools for Meta-Analysis
User-friendly package for reporting replicability-analysis methods, affixed to meta-analyses summary. The replicability-analysis output provides an assessment of the investigated intervention, where it offers quantification of effect replicability and assessment of the consistency of findings. - Replicability-analysis for fixed-effects and random-effect meta analysis: - r(u)-value; - lower bounds on the number of studies with replicated positive and\or negative effect; - Allows detecting inconsistency of signals; - forest plots with the summary of replicability analysis results; - Allows Replicability-analysis with or without the common-effect assumption.
Maintained by Iman Jaljuli. Last updated 1 years ago.
0.5 match 5 stars 4.40 score 4 scripts
swarnendu-stat
bnns:Bayesian Neural Network with 'Stan'
Offers a flexible formula-based interface for building and training Bayesian Neural Networks powered by 'Stan'. The package supports modeling complex relationships while providing rigorous uncertainty quantification via posterior distributions. With features like user chosen priors, clear predictions, and support for regression, binary, and multi-class classification, it is well-suited for applications in clinical trials, finance, and other fields requiring robust Bayesian inference and decision-making. References: Neal(1996) <doi:10.1007/978-1-4612-0745-0>.
Maintained by Swarnendu Chatterjee. Last updated 1 months ago.
0.5 match 1 stars 4.40 score
alfodefalco
dPCP:Automated Analysis of Multiplex Digital PCR Data
The automated clustering and quantification of the digital PCR data is based on the combination of 'DBSCAN' (Hahsler et al. (2019) <doi:10.18637/jss.v091.i01>) and 'c-means' (Bezdek et al. (1981) <doi:10.1007/978-1-4757-0450-1>) algorithms. The analysis is independent of multiplexing geometry, dPCR system, and input amount. The details about input data and parameters are available in the vignette.
Maintained by Alfonso De Falco. Last updated 2 years ago.
0.5 match 2 stars 4.36 score 23 scriptsbioc
txcutr:Transcriptome CUTteR
Various mRNA sequencing library preparation methods generate sequencing reads specifically from the transcript ends. Analyses that focus on quantification of isoform usage from such data can be aided by using truncated versions of transcriptome annotations, both at the alignment or pseudo-alignment stage, as well as in downstream analysis. This package implements some convenience methods for readily generating such truncated annotations and their corresponding sequences.
Maintained by Mervin Fansler. Last updated 5 months ago.
alignmentannotationrnaseqsequencingtranscriptomics
0.5 match 4.30 score 9 scriptsbioc
EasyCellType:Annotate cell types for scRNA-seq data
We developed EasyCellType which can automatically examine the input marker lists obtained from existing software such as Seurat over the cell markerdatabases. Two quantification approaches to annotate cell types are provided: Gene set enrichment analysis (GSEA) and a modified versio of Fisher's exact test. The function presents annotation recommendations in graphical outcomes: bar plots for each cluster showing candidate cell types, as well as a dot plot summarizing the top 5 significant annotations for each cluster.
Maintained by Ruoxing Li. Last updated 5 months ago.
singlecellsoftwaregeneexpressiongenesetenrichment
0.5 match 4.30 score 6 scriptsbioc
hiReadsProcessor:Functions to process LM-PCR reads from 454/Illumina data
hiReadsProcessor contains set of functions which allow users to process LM-PCR products sequenced using any platform. Given an excel/txt file containing parameters for demultiplexing and sample metadata, the functions automate trimming of adaptors and identification of the genomic product. Genomic products are further processed for QC and abundance quantification.
Maintained by Nirav V Malani. Last updated 5 months ago.
0.5 match 4.18 score 7 scripts
niklhart
kldest:Sample-Based Estimation of Kullback-Leibler Divergence
Estimation algorithms for Kullback-Leibler divergence between two probability distributions, based on one or two samples, and including uncertainty quantification. Distributions can be uni- or multivariate and continuous, discrete or mixed.
Maintained by Niklas Hartung. Last updated 6 months ago.
0.5 match 3 stars 4.08 score 20 scripts
karlropkins
AQEval:Air Quality Evaluation
Developed for use by those tasked with the routine detection, characterisation and quantification of discrete changes in air quality time-series, such as identifying the impacts of air quality policy interventions. The main functions use signal isolation then break-point/segment (BP/S) methods based on 'strucchange' and 'segmented' methods to detect and quantify change events (Ropkins & Tate, 2021, <doi:10.1016/j.scitotenv.2020.142374>).
Maintained by Karl Ropkins. Last updated 1 months ago.
0.5 match 9 stars 4.13 score
franciscorichter
rgm:Advanced Inference with Random Graphical Models
Implements state-of-the-art Random Graphical Models (RGMs) for multivariate data analysis across multiple environments, offering tools for exploring network interactions and structural relationships. Capabilities include joint inference across environments, integration of external covariates, and a Bayesian framework for uncertainty quantification. Applicable in various fields, including microbiome analysis. Methods based on Vinciotti, V., Wit, E., & Richter, F. (2023). "Random Graphical Model of Microbiome Interactions in Related Environments." <arXiv:2304.01956>.
Maintained by Francisco Richter. Last updated 1 years ago.
0.5 match 4.00 score 5 scripts
bioc
SDAMS:Differential Abundant/Expression Analysis for Metabolomics, Proteomics and single-cell RNA sequencing Data
This Package utilizes a Semi-parametric Differential Abundance/expression analysis (SDA) method for metabolomics and proteomics data from mass spectrometry as well as single-cell RNA sequencing data. SDA is able to robustly handle non-normally distributed data and provides a clear quantification of the effect size.
Maintained by Yuntong Li. Last updated 5 months ago.
immunooncologydifferentialexpressionmetabolomicsproteomicsmassspectrometrysinglecell
0.5 match 3.60 score 1 scripts
laubok
PStrata:Principal Stratification Analysis in R
Estimating causal effects in the presence of post-treatment confounding using principal stratification. 'PStrata' allows for customized monotonicity assumptions and exclusion restriction assumptions, with automatic full Bayesian inference supported by 'Stan'. The main function to use in this package is PStrata(), which provides posterior estimates of principal causal effect with uncertainty quantification. Visualization tools are also provided for diagnosis and interpretation. See Liu and Li (2023) <arXiv:2304.02740> for details.
Maintained by Bo Liu. Last updated 1 years ago.
0.5 match 6 stars 3.48 score
fgu5tav0
OxSR:Soil Iron Oxides via Diffuse Reflectance
Calculate the ratio of iron oxides, hematite and goethite, in soil using the diffuse reflectance technique. The Kubelka-Munk theory, second derivative analysis, and spectral region amplitudes related to hematite and goethite content are used for quantification (Torrent, J., & Barron, V. (2008) <doi:10.2136/sssabookser5.5.c13>). Additionally, the package calculates soil color in the visible spectrum using Munsell and RGB color spaces, based on color theory (Viscarra et al. (2006) <doi:10.1016/j.geoderma.2005.07.017>).
Maintained by Frosi Gustavo. Last updated 6 days ago.
0.5 match 3.48 score
guanqiaoding
frapplot:Automatic Data Processing and Visualization for FRAP
Automatically process Fluorescence Recovery After Photobleaching (FRAP) data and generate consistent, publishable figures. Note: this package does not replace 'ImageJ' (or its equivalence) in raw image quantification. Some references about the methods: Sprague, Brian L. (2004) <doi:10.1529/biophysj.103.026765>; Day, Charles A. (2012) <doi:10.1002/0471142956.cy0219s62>.
Maintained by Guanqiao Ding. Last updated 6 years ago.
0.5 match 5 stars 3.40 score 4 scripts
g-corbelli
persval:Computing Personal Values Scores
Compute personal values scores from various questionnaires based on the theoretical constructs proposed by professor Shalom H. Schwartz. Designed for researchers and practitioners in psychology, sociology, and related fields, the package facilitates the quantification of different dimensions related to personal values from survey data. It incorporates the recommended statistical adjustment to enhance the accuracy and interpretation of the results. Note: The package 'persval' is independently developed based on the personal values theoretical framework, and is not directly endorsed by professor Schwartz.
Maintained by Giuseppe Corbelli. Last updated 7 months ago.
assessmentpersonalitypsychologypsychometricsquestionnaire-surveyvalues
0.5 match 2 stars 3.30 score
federicocomoglio
dupiR:Bayesian Inference from Count Data using Discrete Uniform Priors
We consider a set of sample counts obtained by sampling arbitrary fractions of a finite volume containing an homogeneously dispersed population of identical objects. This package implements a Bayesian derivation of the posterior probability distribution of the population size using a binomial likelihood and non-conjugate, discrete uniform priors under sampling with or without replacement. This can be used for a variety of statistical problems involving absolute quantification under uncertainty. See Comoglio et al. (2013) <doi:10.1371/journal.pone.0074388>.
Maintained by Federico Comoglio. Last updated 12 months ago.
0.5 match 1 stars 3.00 score 7 scripts
yonghuidong
CCWeights:Perform Weighted Linear Regression for Calibration Curve
Automated assessment and selection of weighting factors for accurate quantification using linear calibration curve. In addition, a 'shiny' App is provided, allowing users to analyze their data using an interactive graphical user interface, without any programming requirements.
Maintained by Yonghui Dong. Last updated 3 years ago.
analytical-chemistrycalibration-curves
0.5 match 2.70 scorecran
IDmeasurer:Assessment of Individual Identity in Animal Signals
Provides tools for assessment and quantification of individual identity information in animal signals. This package accompanies a research article by Linhart et al. (2019) <doi:10.1101/546143>: "Measuring individual identity information in animal signals: Overview and performance of available identity metrics".
Maintained by Pavel Linhart. Last updated 6 years ago.
0.5 match 2.70 score 4 scripts
dazzimonti
profExtrema:Compute and Visualize Profile Extrema Functions
Computes profile extrema functions for arbitrary functions. If the function is expensive-to-evaluate it computes profile extrema by emulating the function with a Gaussian process (using package 'DiceKriging'). In this case uncertainty quantification on the profile extrema can also be computed. The different plotting functions for profile extrema give the user a tool to better locate excursion sets.
Maintained by Dario Azzimonti. Last updated 4 months ago.
0.5 match 2.70 score 10 scripts
jameshucklesby
vmeasur:Quantify the contractile nature of vessels monitored under an operating microscope
A variety of tools to allow the quantification of videos of the lymphatic vasculature taken under an operating microscope. Lymphatic vessels that have been injected with a variety of blue dyes can be tracked throughout the video to determine their width over time. Code is optimised for efficient processing of multiple large video files. Functions to calculate physiologically relevant parameters and generate graphs from these values are also included.
Maintained by James Hucklesby. Last updated 3 years ago.
0.5 match 2.70 score
nilotpalsanyal
GWASinlps:Non-Local Prior Based Iterative Variable Selection Tool for Genome-Wide Association Studies
Performs variable selection with data from Genome-wide association studies (GWAS), or other high-dimensional data with continuous, binary or survival outcomes, combining in an iterative framework the computational efficiency of the structured screen-and-select variable selection strategy based on some association learning and the parsimonious uncertainty quantification provided by the use of non-local priors (see Sanyal et al., 2019 <DOI:10.1093/bioinformatics/bty472>).
Maintained by Nilotpal Sanyal. Last updated 2 years ago.
gwashigh-dimensionalnon-local-priorvariable-selectionopenblascpp
0.5 match 2.70 score 3 scripts
blakemoya
copre:Tools for Nonparametric Martingale Posterior Sampling
Performs Bayesian nonparametric density estimation using Martingale posterior distributions including the Copula Resampling (CopRe) algorithm. Also included are a Gibbs sampler for the marginal Gibbs-type mixture model and an extension to include full uncertainty quantification via a predictive sequence resampling (SeqRe) algorithm. The CopRe and SeqRe samplers generate random nonparametric distributions as output, leading to complete nonparametric inference on posterior summaries. Routines for calculating arbitrary functionals from the sampled distributions are included as well as an important algorithm for finding the number and location of modes, which can then be used to estimate the clusters in the data using, for example, k-means. Implements work developed in Moya B., Walker S. G. (2022). <doi:10.48550/arxiv.2206.08418>, Fong, E., Holmes, C., Walker, S. G. (2021) <doi:10.48550/arxiv.2103.15671>, and Escobar M. D., West, M. (1995) <doi:10.1080/01621459.1995.10476550>.
Maintained by Blake Moya. Last updated 10 months ago.
bayesiandirichlet-processnonparametriccppopenmp
0.5 match 1 stars 2.70 score 2 scripts
sandrinepavoine
adiv:Analysis of Diversity
Functions, data sets and examples for the calculation of various indices of biodiversity including species, functional and phylogenetic diversity. Part of the indices are expressed in terms of equivalent numbers of species. The package also provides ways to partition biodiversity across spatial or temporal scales (alpha, beta, gamma diversities). In addition to the quantification of biodiversity, ordination approaches are available which rely on diversity indices and allow the detailed identification of species, functional or phylogenetic differences between communities.
Maintained by Sandrine Pavoine. Last updated 1 years ago.
0.5 match 1 stars 2.28 score 63 scripts
hkestler
GiANT:Gene Set Uncertainty in Enrichment Analysis
Toolbox for various enrichment analysis methods and quantification of uncertainty of gene sets, Schmid et al. (2016) <doi:10.1093/bioinformatics/btw030>.
Maintained by Hans A. Kestler. Last updated 6 months ago.
0.5 match 2.00 score 4 scripts
gchowell
BayesianFitForecast:Bayesian Parameter Estimation and Forecasting for Epidemiological Models
Methods for Bayesian parameter estimation and forecasting in epidemiological models. Functions enable model fitting using Bayesian methods and generate forecasts with uncertainty quantification. Implements approaches described in <doi:10.48550/arXiv.2411.05371> and <doi:10.1002/sim.9164>.
Maintained by Gerardo Chowell. Last updated 3 months ago.
0.5 match 2.00 score
uncertaintyquantification
RobustCalibration:Robust Calibration of Imperfect Mathematical Models
Implements full Bayesian analysis for calibrating mathematical models with new methodology for modeling the discrepancy function. It allows for emulation, calibration and prediction using complex mathematical model outputs and experimental data. See the reference: Mengyang Gu and Long Wang, 2018, Journal of Uncertainty Quantification; Mengyang Gu, Fangzheng Xie and Long Wang, 2022, Journal of Uncertainty Quantification; Mengyang Gu, Kyle Anderson and Erika McPhillips, 2023, Technometrics.
Maintained by Mengyang Gu. Last updated 10 months ago.
0.8 match 1.23 score 17 scripts
vahidnassiri
BLOQ:Impute and Analyze Data with BLOQ Observations
It includes estimating the area under the concentrations versus time curve (AUC) and its standard error for data with Below the Limit of Quantification (BLOQ) observations. Two approaches are implemented: direct estimation using censored maximum likelihood, also by first imputing the BLOQ's using various methods, then compute AUC and its standard error using imputed data. Technical details can found in Barnett, Helen Yvette, Helena Geys, Tom Jacobs, and Thomas Jaki. "Methods for Non-Compartmental Pharmacokinetic Analysis With Observations Below the Limit of Quantification." Statistics in Biopharmaceutical Research (2020): 1-12. (available online: <https://www.tandfonline.com/doi/full/10.1080/19466315.2019.1701546>).
Maintained by Vahid Nassiri. Last updated 5 years ago.
0.8 match 1.11 score 13 scripts
pmair78
homals:Gifi Methods for Optimal Scaling
Performs a homogeneity analysis (multiple correspondence analysis) and various extensions. Rank restrictions on the category quantifications can be imposed (nonlinear PCA). The categories are transformed by means of optimal scaling with options for nominal, ordinal, and numerical scale levels (for rank-1 restrictions). Variables can be grouped into sets, in order to emulate regression analysis and canonical correlation analysis.
Maintained by Patrick Mair. Last updated 3 years ago.
0.5 match 1 stars 1.59 score 39 scripts
wimvde001
EffectTreat:Prediction of Therapeutic Success
In personalized medicine, one wants to know, for a given patient and his or her outcome for a predictor (pre-treatment variable), how likely it is that a treatment will be more beneficial than an alternative treatment. This package allows for the quantification of the predictive causal association (i.e., the association between the predictor variable and the individual causal effect of the treatment) and related metrics. Part of this software has been developed using funding provided from the European Union's 7th Framework Programme for research, technological development and demonstration under Grant Agreement no 602552.
Maintained by Wim Van der Elst. Last updated 5 years ago.
0.5 match 1.15 score 14 scripts
linusseelinger
umbridge:Integration for the UM-Bridge Protocol
A convenient wrapper for the UM-Bridge protocol. UM-Bridge is a protocol designed for coupling uncertainty quantification (or statistical / optimization) software to numerical models. A model is represented as a mathematical function with optional support for derivatives via Jacobian actions etc.
Maintained by Linus Seelinger. Last updated 2 years ago.
0.5 match 1.00 score 5 scriptscran
vfcp:Computation of v Values for U and Copula C(U, v)
Computation the value of one of two uniformly distributed marginals if the copula probability value is known and the value of the second marginal is also known. Computation and plotting corresponding cumulative distribution function or survival function. The numerical definition of a common area limited by lines of the cumulative distribution function and survival function. Approximate quantification of the probability of this area. In addition to 'amh', the copula dimension may be larger than 2.
Maintained by Josef Brejcha. Last updated 7 years ago.
0.5 match 1.00 scorecran
EstMix:Tumor Clones Percentage Estimations
Includes R functions for the estimation of tumor clones percentages for both snp data and (whole) genome sequencing data. See Cheng, Y., Dai, J. Y., Paulson, T. G., Wang, X., Li, X., Reid, B. J., & Kooperberg, C. (2017). Quantification of multiple tumor clones using gene array and sequencing data. The Annals of Applied Statistics, 11(2), 967-991, <doi:10.1214/17-AOAS1026> for more details.
Maintained by Xuan You. Last updated 7 years ago.
0.5 match 1.00 score
ksenia-kyzyurova
LinkedGASP:Linked Emulator of a Coupled System of Simulators
Prototypes for construction of a Gaussian Stochastic Process emulator (GASP) of a computer model. This is done within the objective Bayesian implementation of the GASP. The package allows for construction of a linked GASP of the composite computer model. Computational implementation follows the mathematical exposition given in publication: Ksenia N. Kyzyurova, James O. Berger, Robert L. Wolpert. Coupling computer models through linking their statistical emulators. SIAM/ASA Journal on Uncertainty Quantification, 6(3): 1151-1171, (2018).<DOI:10.1137/17M1157702>.
Maintained by Ksenia N. Kyzyurova. Last updated 6 years ago.
0.5 match 1.00 score 10 scripts