关键词: RNA-Seq, 基因转录本表达水平, 平滑LDA, 结合区, 多源映射, 非均匀性

Abstract: RNA-Seq is an important technique for transcriptome research. Considering the multi-mappings between reads and isoforms, non-uniform distribution of reads along the reference sequence, conjunction reads and the sparsity caused by the large exon size, this paper proposes a new method, sLDASeq, to calculate the gene and transcript expression. To solve the problems of multi-mappings, non-uniform distribution of reads and conjunction reads, the model utilizes the known gene-isoform annotation to constrain the hyper-parameters and allocate the read counts according to exon length. By adding a hyper-parameter, the model solves the problem of sparsity in the exons. sLDASeq is validated by using three real datasets on the gene and transcript expression calculation and compared with LDASeq and other popular methods. Results show that sLDASeq obtains more accurate transcript and gene expression measurements than other methods.

Key words: RNA-Seq, gene and transcript expression, smoothed LDA, exon-junction, multi-mapping, non-uniformity