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Algorithms and Software for Provably Accurate De Novo RNA-Seq Assembly

用于可证明准确的 De Novo RNA-Seq 组装的算法和软件

基本信息

批准号：
9624586
负责人：
Sreeram Kannan
金额：
$ 29.9万
依托单位：
CALIFORNIA INSTITUTE OF TECHNOLOGY
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-16 至 2019-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9624586
关键词：
Algorithms Software Provably Accurate De

项目摘要

DESCRIPTION (provided by applicant): RNA-Seq has revolutionized transcriptomics and is one of the most important high-throughput sequencing assays invented in recent years. The key computational problem is that of de novo assembly: the reconstruction of the transcripts and their abundances from tens to hundreds of millions of short reads. The problem is challenging due to a confluence of several factors: large number of different transcripts (tens of thousands), long repeat across transcripts due to alternative splicing, widely varying abundances across transcripts, and the presence of read errors. Existing assemblers are mostly designed based on heuristic considerations and implement ad hoc methods that lead to unreliable transcriptome reconstructions. An accurate RNA-Seq assembler would enable more accurate identification of fusions in cancer transcriptomes, better gene annotations in model and non-model organisms, and more complete analyses of the dynamics of alternative splicing driving developmental and regulatory programs. In this proposal, we offer a systematic approach to the design of RNA-Seq assemblers based on information theoretic principles. We start by determining conditions data that guarantee that there enough information to reconstruct the transcriptome, and then propose an assembly algorithm that can reconstruct with the minimal information. This algorithm optimally uses the available read information to resolve repeats and disambiguate isoforms. A key insight derived from the information theoretic approach is that widely varying abundances across transcripts, rather than a complication, can actually be exploited as signatures of different transcripts to disambiguate among them. Based on our initial ideas, we have built, evaluated and compared an initial prototype with several existing software, on both real and simulated data. The encouraging results provide evidence that our approach, which we will fully develop, implement and evaluated during the funded period, can significantly outperform existing software. Additional functionalities such as mixed short/long read assembly, genome-assisted assembly and joint processing of multiple RNA samples, will be designed and incorporated into the software as part of the proposed project.

项目成果

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

An interpretable framework for clustering single-cell RNA-Seq datasets.

DOI：
10.1186/s12859-018-2092-7
发表时间：
2018-03-09
期刊：
BMC bioinformatics
影响因子：
3
作者：
Zhang JM;Fan J;Fan HC;Rosenfeld D;Tse DN
通讯作者：
Tse DN

Somatic mutations render human exome and pathogen DNA more similar.

体细胞突变使人类外显子组和病原体 DNA 更加相似。

DOI：
10.1371/journal.pone.0197949
发表时间：
2019
期刊：
PloS one
影响因子：
3.7
作者：
Ebrahimzadeh,Ehsan;Engler,Maggie;Tse,David;Cristescu,Razvan;Tchamkerten,Aslan
通讯作者：
Tchamkerten,Aslan

QAlign: aligning nanopore reads accurately using current-level modeling.

QAlign：使用电流水平建模准确对齐纳米孔读数。