EDASeq specifications

Information


Unique identifier OMICS_01231
Name EDASeq
Alternative name Exploratory Data Analysis and Normalization for RNA-Seq
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data RNA-Seq read data
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License Artistic License version 2.0
Computer skills Advanced
Version 2.8
Stability Stable
Requirements Biobase, ShortRead
Maintained Yes

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EDASeq citations

 (3)
2017
PMCID: 5264326

[…] of 28% and the vast majority of measurements under 40% for all ranges of log2cpm., the quality of the raw data was assessed by principle component analysis using the software r/bioconductor software edaseq [20]. principle component analysis shows that the data is well separated on principle component axis 1 (80%) and fairly well on axis 2., gene set enrichment was performed using […]

2016
PMCID: 5048756

[…] analysis: to determine gene expression levels, we counted the number of reads for 38,293 mouse genes using htseq version 0.5.3 based on the ensembl gene annotation version 71. we then used edaseq (version 1.4.0) to correct for gc-content bias and tested for differential gene expression using deseq (version 1.10.1)., heatmaps and pca clustering: plots have been generated based […]

2016
PMCID: 4859066

[…] separately (data not shown). rna-seq tags were aligned using tophat software package with default parameters42. rna-seq tag frequencies were normalized for gc content using bioconductor package edaseq and then the expression estimates for each gene were obtained using bioconductor package deseq4344. assessment of statistical significance, k-means clustering, hhm generation […]

EDASeq institution(s)
Department of Statistical Sciences, University of Padua, Italy; Department of Genetics, Stanford University, Standford, CA, USA; Division of Biostatistics and Department of Statistics, University of California, Berkeley, CA, USA
EDASeq funding source(s)
This work was funded by grant R01 HG03468 from the NHGRI at the NIH and grant CPDA094285 from the University of Padua.

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