Showing 6 of total 6 results (show query)
bioc
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
137 stars 12.95 score 2.6k scripts 11 dependentsbioc
tidybulk:Brings transcriptomics to the tidyverse
This is a collection of utility functions that allow to perform exploration of and calculations to RNA sequencing data, in a modular, pipe-friendly and tidy fashion.
Maintained by Stefano Mangiola. Last updated 15 days ago.
assaydomaininfrastructurernaseqdifferentialexpressiongeneexpressionnormalizationclusteringqualitycontrolsequencingtranscriptiontranscriptomicsbioconductorbulk-transcriptional-analysesdeseq2differential-expressionedgerensembl-idsentrezgene-symbolsgseamds-dimensionspcapiperedundancytibbletidytidy-datatidyversetranscriptstsne
171 stars 9.57 score 172 scripts 1 dependentsbioc
recount:Explore and download data from the recount project
Explore and download data from the recount project available at https://jhubiostatistics.shinyapps.io/recount/. Using the recount package you can download RangedSummarizedExperiment objects at the gene, exon or exon-exon junctions level, the raw counts, the phenotype metadata used, the urls to the sample coverage bigWig files or the mean coverage bigWig file for a particular study. The RangedSummarizedExperiment objects can be used by different packages for performing differential expression analysis. Using http://bioconductor.org/packages/derfinder you can perform annotation-agnostic differential expression analyses with the data from the recount project as described at http://www.nature.com/nbt/journal/v35/n4/full/nbt.3838.html.
Maintained by Leonardo Collado-Torres. Last updated 4 months ago.
coveragedifferentialexpressiongeneexpressionrnaseqsequencingsoftwaredataimportimmunooncologyannotation-agnosticbioconductorcountderfinderdeseq2exongenehumanilluminajunctionrecount
41 stars 9.57 score 498 scripts 3 dependentsbioc
regionReport:Generate HTML or PDF reports for a set of genomic regions or DESeq2/edgeR results
Generate HTML or PDF reports to explore a set of regions such as the results from annotation-agnostic expression analysis of RNA-seq data at base-pair resolution performed by derfinder. You can also create reports for DESeq2 or edgeR results.
Maintained by Leonardo Collado-Torres. Last updated 3 months ago.
differentialexpressionsequencingrnaseqsoftwarevisualizationtranscriptioncoveragereportwritingdifferentialmethylationdifferentialpeakcallingimmunooncologyqualitycontrolbioconductorderfinderdeseq2edgerregionreportrmarkdown
9 stars 7.22 score 46 scriptsbioc
ppcseq:Probabilistic Outlier Identification for RNA Sequencing Generalized Linear Models
Relative transcript abundance has proven to be a valuable tool for understanding the function of genes in biological systems. For the differential analysis of transcript abundance using RNA sequencing data, the negative binomial model is by far the most frequently adopted. However, common methods that are based on a negative binomial model are not robust to extreme outliers, which we found to be abundant in public datasets. So far, no rigorous and probabilistic methods for detection of outliers have been developed for RNA sequencing data, leaving the identification mostly to visual inspection. Recent advances in Bayesian computation allow large-scale comparison of observed data against its theoretical distribution given in a statistical model. Here we propose ppcseq, a key quality-control tool for identifying transcripts that include outlier data points in differential expression analysis, which do not follow a negative binomial distribution. Applying ppcseq to analyse several publicly available datasets using popular tools, we show that from 3 to 10 percent of differentially abundant transcripts across algorithms and datasets had statistics inflated by the presence of outliers.
Maintained by Stefano Mangiola. Last updated 5 months ago.
rnaseqdifferentialexpressiongeneexpressionnormalizationclusteringqualitycontrolsequencingtranscriptiontranscriptomicsbayesian-inferencedeseq2edgernegative-binomialoutlierstancpp
8 stars 5.71 score 16 scripts
tinnlab
RCPA:Consensus Pathway Analysis
Provides a set of functions to perform pathway analysis and meta-analysis from multiple gene expression datasets, as well as visualization of the results. This package wraps functionality from the following packages: Ritchie et al. (2015) <doi:10.1093/nar/gkv007>, Love et al. (2014) <doi:10.1186/s13059-014-0550-8>, Robinson et al. (2010) <doi:10.1093/bioinformatics/btp616>, Korotkevich et al. (2016) <arxiv:10.1101/060012>, Efron et al. (2015) <https://CRAN.R-project.org/package=GSA>, and Gu et al. (2012) <https://CRAN.R-project.org/package=CePa>.
Maintained by Ha Nguyen. Last updated 5 months ago.
biobasedeseq2geoqueryedgerlimmarcyjsfgseabrowservizsummarizedexperimentannotationdbirontotools
1 stars 5.50 score 70 scripts