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RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR

RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR

The ability to easily and efficiently analyse RNA-sequencing data is a key strength of the Bioconductor project. Starting with counts summarised at the gene-level, a typical analysis involves pre-processing, exploratory data analysis, differential expression testing and pathway analysis with the ...

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Power analysis and sample size estimation for RNA-Seq differential expression

Power analysis and sample size estimation for RNA-Seq differential expression

It is crucial for researchers to optimize RNA-seq experimental designs for differential expression detection. Currently, the field lacks general methods to estimate power and sample size for RNA-Seq in complex experimental designs, under the assumption of the negative binomial distribution. ...

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shRNA-seq data analysis with edgeR

shRNA-seq data analysis with edgeR

Pooled short hairpin RNA sequencing (shRNA-seq) screens are becoming increasingly popular in functional genomics research, and there is a need to establish optimal analysis tools to handle such data. This open-source shRNA processing pipeline in edgeR provides a complete analysis ...

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