DESeq2

<p>DESeq2 is a software <a href="/facts/R_package/etUNSDLc">package</a> in the field of <a href="/facts/Bioinformatics/D5x2L8ee">bioinformatics</a> and <a href="/facts/Computational_biology/GxgNfwcX">computational biology</a> for the <a href="/facts/Computational_statistics/noW2SBX8">statistical programming</a> language <a href="/facts/R_/LSrkr8K8">R</a>. It is primarily employed for the analysis of high-throughput <a href="/facts/RNA-Seq/dIRwBuAa">RNA sequencing (RNA-seq)</a> data to identify differentially expressed genes between different experimental conditions. DESeq2 employs statistical methods to <a href="/facts/Normalization_(statistics)/734U3VFY">normalize</a> and analyze RNA-seq data, making it a valuable tool for researchers studying <a href="/facts/Gene_expression/alCPohLR">gene expression</a> patterns and <a href="/facts/Regulation_of_gene_expression/9N4G341I">regulation</a>. It is available through the <a href="/facts/Bioconductor/SQyvk4TM">Bioconductor</a> repository.
</p><p>It was first presented in 2014. As of September 2023, its use has been cited over 30,000 times.
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DESeq2 open-in-new

DESeq2