EBSeq: An R package for differential expression analysis using RNA-seq data
نویسندگان
چکیده
4 Quick Start 6 4.1 Gene level DE analysis (two conditions) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 4.1.1 Required input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 4.1.2 Library size factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 4.1.3 Running EBSeq on gene expression estimates . . . . . . . . . . . . . . . . . . . . . . . 6 4.2 Isoform level DE analysis (two conditions) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 4.2.1 Required inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 4.2.2 Library size factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 4.2.3 The Ig vector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 4.2.4 Running EBSeq on isoform expression estimates . . . . . . . . . . . . . . . . . . . . . 8 4.3 Gene level DE analysis (more than two conditions) . . . . . . . . . . . . . . . . . . . . . . . . 9 4.4 Isoform level DE analysis (more than two conditions) . . . . . . . . . . . . . . . . . . . . . . . 11
منابع مشابه
A Comparison of Methods for RNA-Seq Differential Expression Analysis and a New Empirical Bayes Approach
Transcriptome-based biosensors are expected to have a large impact on the future of biotechnology. However, a central aspect of transcriptomics is differential expression analysis, where, currently, deep RNA sequencing (RNA-seq) has the potential to replace the microarray as the standard assay for RNA quantification. Our contributions here to RNA-seq differential expression analysis are two-fol...
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