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.
Last updated 19 hours ago
functionalgenomicsmicroarrayrnaseqpathwaysgenesetenrichmentgene-set-enrichmentgenomicspathway-enrichment-analysis
14.74 score 213 stars 19 dependents 1.6k scripts 12k downloadsqpgraph - Estimation of Genetic and Molecular Regulatory Networks from High-Throughput Genomics Data
Estimate gene and eQTL networks from high-throughput expression and genotyping assays.
Last updated 6 days ago
microarraygeneexpressiontranscriptionpathwaysnetworkinferencegraphandnetworkgeneregulationgeneticsgeneticvariabilitysnpsoftwareopenblas
8.72 score 3 stars 3 dependents 20 scripts 482 downloadsGenomicScores - Infrastructure to work with genomewide position-specific scores
Provide infrastructure to store and access genomewide position-specific scores within R and Bioconductor.
Last updated 2 months ago
infrastructuregeneticsannotationsequencingcoverageannotationhubsoftware
8.71 score 8 stars 6 dependents 83 scripts 1.2k downloadsVariantFiltering - Filtering of coding and non-coding genetic variants
Filter genetic variants using different criteria such as inheritance model, amino acid change consequence, minor allele frequencies across human populations, splice site strength, conservation, etc.
Last updated 2 months ago
geneticshomo_sapiensannotationsnpsequencinghighthroughputsequencing
6.23 score 4 stars 21 scripts 373 downloadsatena - 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.
Last updated 2 months ago
transcriptiontranscriptomicsrnaseqsequencingpreprocessingsoftwaregeneexpressioncoveragedifferentialexpressionfunctionalgenomics
6.18 score 10 stars 1 scripts 360 downloadsgDNAx - Diagnostics for assessing genomic DNA contamination in RNA-seq data
Provides diagnostics for assessing genomic DNA contamination in RNA-seq data, as well as plots representing these diagnostics. Moreover, the package can be used to get an insight into the strand library protocol used and, in case of strand-specific libraries, the strandedness of the data. Furthermore, it provides functionality to filter out reads of potential gDNA origin.
Last updated 2 months ago
transcriptiontranscriptomicsrnaseqsequencingpreprocessingsoftwaregeneexpressioncoveragedifferentialexpressionfunctionalgenomicssplicedalignmentalignment
4.90 score 1 stars 3 scripts 240 downloads