A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data
“A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data”, vol. 15, p. -, 2016.
, With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data.