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DEGseq: an R package for identifying differentially expressed genes from RNA-seq data

Bioinformatics · 2009 · Vol. 26(1) · pp. 136–138

Likun Wang✉(Tsinghua University)Zhixing Feng(Tsinghua University)Xi Wang(Jilin University)Xiaowo Wang(Tsinghua University)Xuegong Zhang(Tsinghua University)

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Abstract

The R package and a quick-start vignette is available at http://bioinfo.au.tsinghua.edu.cn/software/degseq

Gene expression and cancer classification Bioinformatics and Genomic Networks Molecular Biology Techniques and ApplicationsRNA-SeqR packageTranscriptomeSoftware packageComputational biologyGene expression profilingGeneRNAProfiling (computer programming)Software

MeSH terms

AlgorithmsBase SequenceMolecular Sequence DataProgramming LanguagesRNASoftwareSequence Analysis, RNAOligonucleotide Array Sequence AnalysisGene Expression Profiling

Funding

National Natural Science Foundation of China
Southeast University
State Key Laboratory of Bioelectronics
National Key Research and Development Program of China
Open Research Fund of State Key Laboratory of Bioelectronics

Citations

4,836

FWCI

22.86

field-weighted impact

References

13

Percentile

100%

vs. same field & year

Citations per year

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References

Statistical significance for genomewide studies

Proceedings of the National Academy of Sciences · 2003 · 10,009 citations

RNA-Seq: a revolutionary tool for transcriptomics

Nature Reviews Genetics · 2008 · 13,223 citations

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1995 · 106,483 citations

RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays

Genome Research · 2008 · 2,821 citations

mRNA-Seq whole-transcriptome analysis of a single cell

Nature Methods · 2009 · 3,942 citations

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Significance analysis of microarrays applied to the ionizing radiation response

Proceedings of the National Academy of Sciences · 2001 · 10,653 citations

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