R-universe search: exports:plotDensity

Showing 13 of total 13 results (show query)

bioc

MSnbase:Base Functions and Classes for Mass Spectrometry and Proteomics

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

Maintained by Laurent Gatto. Last updated 14 days ago.

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

131 stars 12.76 score 772 scripts 36 dependents

bioc

affy:Methods for Affymetrix Oligonucleotide Arrays

The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.

Maintained by Robert D. Shear. Last updated 3 months ago.

microarray onechannel preprocessing

11.12 score 2.5k scripts 98 dependents

bioc

netZooR:Unified methods for the inference and analysis of gene regulatory networks

netZooR unifies the implementations of several Network Zoo methods (netzoo, netzoo.github.io) into a single package by creating interfaces between network inference and network analysis methods. Currently, the package has 3 methods for network inference including PANDA and its optimized implementation OTTER (network reconstruction using mutliple lines of biological evidence), LIONESS (single-sample network inference), and EGRET (genotype-specific networks). Network analysis methods include CONDOR (community detection), ALPACA (differential community detection), CRANE (significance estimation of differential modules), MONSTER (estimation of network transition states). In addition, YARN allows to process gene expresssion data for tissue-specific analyses and SAMBAR infers missing mutation data based on pathway information.

Maintained by Tara Eicher. Last updated 10 days ago.

networkinference network generegulation geneexpression transcription microarray graphandnetwork gene-regulatory-network transcription-factors

105 stars 7.98 score

bioc

aroma.light:Light-Weight Methods for Normalization and Visualization of Microarray Data using Only Basic R Data Types

Methods for microarray analysis that take basic data types such as matrices and lists of vectors. These methods can be used standalone, be utilized in other packages, or be wrapped up in higher-level classes.

Maintained by Henrik Bengtsson. Last updated 5 months ago.

infrastructure microarray onechannel twochannel multichannel visualization preprocessing bioconductor

1 stars 6.43 score 26 scripts 20 dependents

bioc

lumi:BeadArray Specific Methods for Illumina Methylation and Expression Microarrays

The lumi package provides an integrated solution for the Illumina microarray data analysis. It includes functions of Illumina BeadStudio (GenomeStudio) data input, quality control, BeadArray-specific variance stabilization, normalization and gene annotation at the probe level. It also includes the functions of processing Illumina methylation microarrays, especially Illumina Infinium methylation microarrays.

Maintained by Lei Huang. Last updated 5 months ago.

microarray onechannel preprocessing dnamethylation qualitycontrol twochannel

6.26 score 294 scripts 5 dependents

henrikbengtsson

aroma.affymetrix:Analysis of Large Affymetrix Microarray Data Sets

A cross-platform R framework that facilitates processing of any number of Affymetrix microarray samples regardless of computer system. The only parameter that limits the number of chips that can be processed is the amount of available disk space. The Aroma Framework has successfully been used in studies to process tens of thousands of arrays. This package has actively been used since 2006.

Maintained by Henrik Bengtsson. Last updated 1 years ago.

infrastructure proprietaryplatforms exonarray microarray onechannel gui dataimport datarepresentation preprocessing qualitycontrol visualization reportwriting acgh copynumbervariants differentialexpression geneexpression snp transcription affymetrix analysis copy-number dna expression hpc large-scale notebook reproducibility rna

10 stars 5.79 score 112 scripts 3 dependents

wlenhard

cNORM:Continuous Norming

A comprehensive toolkit for generating continuous test norms in psychometrics and biometrics, and analyzing model fit. The package offers both distribution-free modeling using Taylor polynomials and parametric modeling using the beta-binomial distribution. Originally developed for achievement tests, it is applicable to a wide range of mental, physical, or other test scores dependent on continuous or discrete explanatory variables. The package provides several advantages: It minimizes deviations from representativeness in subsamples, interpolates between discrete levels of explanatory variables, and significantly reduces the required sample size compared to conventional norming per age group. cNORM enables graphical and analytical evaluation of model fit, accommodates a wide range of scales including those with negative and descending values, and even supports conventional norming. It generates norm tables including confidence intervals. It also includes methods for addressing representativeness issues through Iterative Proportional Fitting.

Maintained by Wolfgang Lenhard. Last updated 4 months ago.

beta-binomial biometrics continuous-norming growth-curve norm-scores norm-tables normalization-techniques percentile psychometrics regression-based-norming taylor-series

2 stars 5.49 score 75 scripts

bioc

rCGH:Comprehensive Pipeline for Analyzing and Visualizing Array-Based CGH Data

A comprehensive pipeline for analyzing and interactively visualizing genomic profiles generated through commercial or custom aCGH arrays. As inputs, rCGH supports Agilent dual-color Feature Extraction files (.txt), from 44 to 400K, Affymetrix SNP6.0 and cytoScanHD probeset.txt, cychp.txt, and cnchp.txt files exported from ChAS or Affymetrix Power Tools. rCGH also supports custom arrays, provided data complies with the expected format. This package takes over all the steps required for individual genomic profiles analysis, from reading files to profiles segmentation and gene annotations. This package also provides several visualization functions (static or interactive) which facilitate individual profiles interpretation. Input files can be in compressed format, e.g. .bz2 or .gz.

Maintained by Frederic Commo. Last updated 5 months ago.

acgh copynumbervariation preprocessing featureextraction

4 stars 5.10 score 26 scripts 1 dependents

bioc

scider:Spatial cell-type inter-correlation by density in R

scider is a user-friendly R package providing functions to model the global density of cells in a slide of spatial transcriptomics data. All functions in the package are built based on the SpatialExperiment object, allowing integration into various spatial transcriptomics-related packages from Bioconductor. After modelling density, the package allows for serveral downstream analysis, including colocalization analysis, boundary detection analysis and differential density analysis.

Maintained by Yunshun Chen. Last updated 5 months ago.

spatial transcriptomics

3 stars 5.08 score 3 scripts

bioc

decontX:Decontamination of single cell genomics data

This package contains implementation of DecontX (Yang et al. 2020), a decontamination algorithm for single-cell RNA-seq, and DecontPro (Yin et al. 2023), a decontamination algorithm for single cell protein expression data. DecontX is a novel Bayesian method to computationally estimate and remove RNA contamination in individual cells without empty droplet information. DecontPro is a Bayesian method that estimates the level of contamination from ambient and background sources in CITE-seq ADT dataset and decontaminate the dataset.

Maintained by Joshua Campbell. Last updated 1 months ago.

singlecell bayesian cpp

4.94 score 29 scripts

bioc

yarn:YARN: Robust Multi-Condition RNA-Seq Preprocessing and Normalization

Expedite large RNA-Seq analyses using a combination of previously developed tools. YARN is meant to make it easier for the user in performing basic mis-annotation quality control, filtering, and condition-aware normalization. YARN leverages many Bioconductor tools and statistical techniques to account for the large heterogeneity and sparsity found in very large RNA-seq experiments.

Maintained by Joseph N Paulson. Last updated 5 months ago.

software qualitycontrol geneexpression sequencing preprocessing normalization annotation visualization clustering

4.49 score 31 scripts

bioc

cn.farms:cn.FARMS - factor analysis for copy number estimation

This package implements the cn.FARMS algorithm for copy number variation (CNV) analysis. cn.FARMS allows to analyze the most common Affymetrix (250K-SNP6.0) array types, supports high-performance computing using snow and ff.

Maintained by Andreas Mitterecker. Last updated 5 months ago.

microarray copynumbervariation cpp

3.30 score 7 scripts

friendly

WordPools:Word Pools Used in Studies of Learning and Memory

Collects several classical word pools used most often to provide lists of words in psychological studies of learning and memory. It provides a simple function, 'pickList' for selecting random samples of words within given ranges.

Maintained by Michael Friendly. Last updated 1 years ago.

experiment memory wordlist-generator

3 stars 3.18 score 8 scripts