本文關(guān)鍵詞：改進(jìn)的RNA-Seq數(shù)據(jù)轉(zhuǎn)錄組表達(dá)分析研究，由筆耕文化傳播整理發(fā)布。

改進(jìn)的RNA-Seq數(shù)據(jù)轉(zhuǎn)錄組表達(dá)分析研究

Improved Trancriptome Expression Analysis for RNA-Seq Data

[1] [2] [3]

Shi Xinxin, Liu Xuejun, Zhang Li （College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 210016, China）

南京航空航天大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)學(xué)院,南京210016

文章摘要：基于高通量測(cè)序的RNA-Seq（RNA-sequencing）是用于轉(zhuǎn)錄組研究的一種新技術(shù),針對(duì)該技術(shù)在轉(zhuǎn)錄組表達(dá)分析研究中存在的讀段多源映射和讀段非均勻分布等難點(diǎn),提出一個(gè)改進(jìn)的轉(zhuǎn)錄組表達(dá)研究方法 LDASeqII（Improvement of latent Dirichlet allocation for sequencing data）。模型利用剪接異構(gòu)體結(jié)構(gòu)信息對(duì)參數(shù)進(jìn)行約束并進(jìn)行外顯子讀段數(shù)目歸一化處理,解決了讀段非均勻分布下的多源映射問(wèn)題。通過(guò)引入＂偽外顯子＂和＂偽轉(zhuǎn)錄本＂分別處理接合區(qū)讀段和噪聲讀段。將模型應(yīng)用到真實(shí)數(shù)據(jù)集上,并與原LDASeq（Latent Dirichlet allocation for sequencing data）模型和目前流行的Cufflinks與RSEM（RNA-Seq by expectation maximization）方法進(jìn)行對(duì)比。結(jié)果顯示,改進(jìn)方法獲得了更為準(zhǔn)確的轉(zhuǎn)錄本及基因表達(dá)水平計(jì)算結(jié)果。

Abstr：RNA-Seq（RNA-sequencing）,based on high-throughput sequencing,is a new technique for transcriptome research.Considering the difficulties in the analysis of transcript expression using RNA-Seq data,an improved method,improvement of latent dirichlet allocation for sequencing data（LDASeqⅡ）is proposed to calculate the transcript expression.To deal with multi-mappings between reads and isoforms and non-uniform distribution of reads along reference,LDASeqⅡ utilizes the known gene-isoform annotation to constrain the hyperparameters and normalizes the read counts by exon length for each individual exon.By introducing″pseudo-exon″and″pseudo-transcript″,the conjunction reads and noise reads gain proper treatments.LDASeqⅡis validated using two real datasets on gene and transcript expression calculation and compared with latent dirichlet allocation for sequencing data（LDASeq）and other two popular methods Cufflinks and RNA-Seq by expectation maximization（RSEM）.The results show that LDASeqⅡobtains more accurate transcript and gene expression measurements than other approaches.

文章關(guān)鍵詞：

Keyword：:gene expression RNA-Seq transcript expression multi-mapping non-uniformity

課題項(xiàng)目：國(guó)家自然科學(xué)基金（61170152）資助項(xiàng)目; 中央高�；究蒲袠I(yè)務(wù)費(fèi)專項(xiàng)（CXZZ11_0217）資助項(xiàng)目

  本文關(guān)鍵詞：改進(jìn)的RNA-Seq數(shù)據(jù)轉(zhuǎn)錄組表達(dá)分析研究，由筆耕文化傳播整理發(fā)布。