Comprehensive evaluation of RNA-seq quantification methods for linearity.

ABSTRACT:

Background

Deconvolution is a mathematical process of resolving an observed function into its constituent elements. In the field of biomedical research, deconvolution analysis is applied to obtain single cell-type or tissue specific signatures from a mixed signal and most of them follow the linearity assumption. Although recent development of next generation sequencing technology suggests RNA-seq as a fast and accurate method for obtaining transcriptomic profiles, few studies have been conducted to investigate best RNA-seq quantification methods that yield the optimum linear space for deconvolution analysis.

Results

Using a benchmark RNA-seq dataset, we investigated the linearity of abundance estimated from seven most popular RNA-seq quantification methods both at the gene a

SUBMITTER: Jin H 

PROVIDER: S-EPMC5374695 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature