Computational Considerations in Transcriptome Assemblies and Their Evaluation, using High Quality Human RNA-Seq data

被引：0

作者：

Ghaffari, Noushin ^{[1
]}

Abante, Jordi ^{[1
]}

Singh, Raminder ^{[2
]}

Blood, Philip D. ^{[3
]}

Johnson, Charles D. ^{[1
]}

机构：

[1] Texas A&M AgriLife Res, CBGSE, AgriLife Genom & Bioinformat, 101 Gateway Blv, College Stn, TX 77845 USA

[2] Indiana Univ Res Technol, 2709 East 10th St, Bloomington, IN 47408 USA

[3] Pittsburgh Supercomp Ctr, 300 S Craig St, Pittsburgh, PA 15213 USA

来源：

PROCEEDINGS OF XSEDE16: DIVERSITY, BIG DATA, AND SCIENCE AT SCALE | 2016年

基金：

美国国家科学基金会;

关键词：

RNA-Seq; Next-generation sequencing; Transcriptome assembly; Quality control; High performance computing; Data management challenges; ALIGNMENT;

D O I：

10.1145/2949550.2949572

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

It is crucial to understand the performance of transcriptome assemblies to improve current practices. Investigating the factors that affect a transcriptome assembly is very important and is the primary goal of our project. To that end, we designed a multi-step pipeline consisting of variety of pre-processing and quality control steps. XSEDE allocations enabled us to achieve the computational demands of the project. The high memory Blacklight and Green field systems at Pittsburgh Supercomputing Center were essential to accomplish multiple steps of this project. This paper presents the computational aspects of our comprehensive transcriptome assembly and validation study.

引用

页数：4

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