LocExpress: a web server for efficiently estimating expression of novel transcriptsReport as inadecuate




LocExpress: a web server for efficiently estimating expression of novel transcripts - Download this document for free, or read online. Document in PDF available to download.

BMC Genomics

, 17:1023

First Online: 22 December 2016DOI: 10.1186-s12864-016-3329-3

Cite this article as: Hou, M., Tian, F., Jiang, S. et al. BMC Genomics 2016 17Suppl 13: 1023. doi:10.1186-s12864-016-3329-3

Abstract

BackgroundThe temporal and spatial-specific expression pattern of a transcript in multiple tissues and cell types can indicate key clues about its function. While several gene atlas available online as pre-computed databases for known gene models, it’s still challenging to get expression profile for previously uncharacterized i.e. novel transcripts efficiently.

ResultsHere we developed LocExpress, a web server for efficiently estimating expression of novel transcripts across multiple tissues and cell types in human 20 normal tissues-cells types and 14 cell lines as well as in mouse 24 normal tissues-cell types and nine cell lines. As a wrapper to RNA-Seq quantification algorithm, LocExpress efficiently reduces the time cost by making abundance estimation calls increasingly within the minimum spanning bundle region of input transcripts. For a given novel gene model, such local context-oriented strategy allows LocExpress to estimate its FPKMs in hundreds of samples within minutes on a standard Linux box, making an online web server possible.

ConclusionsTo the best of our knowledge, LocExpress is the only web server to provide nearly real-time expression estimation for novel transcripts in common tissues and cell types. The server is publicly available at http:-loc-express.cbi.pku.edu.cn.

KeywordsExpression estimation Transcriptome RNA-Seq Web server AbbreviationsFPKMFragments per kilobase of exon per million fragments mapped

MSBMinimum spanning bundle

Electronic supplementary materialThe online version of this article doi:10.1186-s12864-016-3329-3 contains supplementary material, which is available to authorized users.

Download fulltext PDF



Author: Mei Hou - Feng Tian - Shuai Jiang - Lei Kong - Dechang Yang - Ge Gao

Source: https://link.springer.com/







Related documents