RNA-Seq data analysis has become vital to understanding gene structure and expression patterns in transcriptomic studies. A typical reference genome guided RNA-Seq workflow...
Read More »How not to perform a differential expression analysis (or science)
By Lior Pachter – One of the maxims of computational biology is that “no two programs ever give the same result.” This is perhaps not so surprising; after all, most journals seek papers that report a significant improvement to an existing method. ...
Read More »Differential analysis of RNA-seq incorporating quantification uncertainty
Caltech researchers describe sleuth, a method for the differential analysis of gene expression data that utilizes bootstrapping in conjunction with response error linear modeling to decouple biological variance from inferential variance. sleuth is implemented in an interactive shiny app that ...
Read More »The Lair – A resource for exploratory analysis of published RNA-Seq data
Increased emphasis on reproducibility of published research in the last few years has led to the large-scale archiving of sequencing data. While this data can, in theory, be used to reproduce results in papers, it is typically not easily usable ...
Read More »IIHG Intro to Sleuth for RNA-Seq
A brief introduction to the Sleuth R Shiny app for doing exploratory data analysis of your RNA-Seq data. This tutorial assumes that the data have been already quantified with kallisto and processed into a sleuth object with the sleuth r ...
Read More »A sleuth for RNA-Seq
from Bits of DNA by Lior Pachter Today my student Harold Pimentel released the beta version of his new RNA-Seq analysis method and software program called sleuth. A sleuth for RNA-Seq begins with the quantification of samples with kallisto, and together a sleuth ...
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