edgeR-robust statistics

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edgeR-robust specifications


Unique identifier OMICS_03825
Name edgeR-robust
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Version 3.0
Stability Stable
Maintained Yes



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  • person_outline Mark Robinson <>

Publication for edgeR-robust

edgeR-robust in publications

PMCID: 5804098
PMID: 29412741
DOI: 10.1089/cell.2017.0040

[…] sample. the differentially expressed (de) genes between sample groups, representing the culture treatment, were determined by fitting the read counts to a generalized linear model implemented in edger-robust (zhou et al., ). the false discovery rate (fdr) <0.05 was used as threshold for statistically significant differential expression of genes., without daily media changes, proliferation […]

PMCID: 5783352
PMID: 29364883
DOI: 10.1371/journal.pntd.0006186

[…] of trfs was then used to quantify the number of reads mapped to each trf in a genome-wide manner by stringtie []. to compare trf expression between different sample groups, we used the r package edger-robust [] which normalizes the read count data by using trimmed mean of m-values method (tmm), and performs statistical inference of differential expression of trfs by fitting the normalized […]

PMCID: 5653985
PMID: 29061120
DOI: 10.1186/s12864-017-4161-0

[…] to the analysis of differential expression. differential expression of transcripts was evaluated using a negative binomial general linearized model (glm) as integrated in the bioconductor r package edger-robust []. within edger, we defined up-regulated transcripts as having a log10 fold change ≥1, and down-regulated transcripts as having a log10 fold change ≤ −1 with a false discovery rate […]

PMCID: 5409122
PMID: 28096185
DOI: 10.1093/hmg/ddw412

[…] from the joint distribution of estimates from observed counts. we performed these simulations by using the r framework nbsim developed by zhou et al. (), http://imlspenticton.uzh.ch/robinson_lab/edger_robust) et al. with following options:folddiff = 3ntags = 1000000add.outlier = trueoutliermech = “s”poutlier = 0.01drop.extreme.dispersion = 0.1, folddiff = 3, ntags = 1000000, add.outlier = […]

PMCID: 5131473
PMID: 27905495
DOI: 10.1038/srep38078

[…] in the gene expression omnibus database (geo, in process)., differential expression analyses between sample groups were performed by fitting the expression data to a generalized linear model using edger-robust. differentially expressed genes (fdr p < 0.10) were further subjected to weighted correlation network analysis (using r package wgcna) to identify changes in expression modules […]

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edgeR-robust institution(s)
Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland; SIB Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
edgeR-robust funding source(s)
Supported by SNSF Project Grant [143883] and European Commission through the 7th Framework Collaborative Project RADIANT [305626].

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