Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences
SIB Swiss Institute of Bioinformatics · University of Zurich · +2 more institutions
Abstract
High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomic studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Several different quantification approaches have been proposed, ranging from simple counting of reads that overlap given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over…
Citation impact
- FWCI
- 37.34
- Percentile
- 100%
- References
- 38
Authors
3Topics & keywords
- Biology
- Transcriptome
- Computational biology
- RNA-Seq
- Abundance (ecology)
- Inference
- Gene
- Interpretability