Dataset Information

IDBA-tran: a more robust de novo de Bruijn graph assembler for transcriptomes with uneven expression levels.

ABSTRACT:

Motivation

RNA sequencing based on next-generation sequencing technology is effective for analyzing transcriptomes. Like de novo genome assembly, de novo transcriptome assembly does not rely on any reference genome or additional annotation information, but is more difficult. In particular, isoforms can have very uneven expression levels (e.g. 1:100), which make it very difficult to identify low-expressed isoforms. One challenge is to remove erroneous vertices/edges with high multiplicity (produced by high-expressed isoforms) in the de Bruijn graph without removing correct ones with not-so-high multiplicity from low-expressed isoforms. Failing to do so will result in the loss of low-expressed isoforms or having complicated subgraphs with transcripts of different genes mixed together due to erroneous vertices/edges. Contributions: Unlike existing tools, which remove erroneous vertices/edges with multiplicities lower than a global threshold, we use a probabilistic progressive approach to iteratively remove them with local thresholds. This enables us to decompose the graph into disconnected components, each containing a few genes, if not a single gene, while retaining many correct vertices/edges of low-expressed isoforms. Combined with existing techniques, IDBA-Tran is able to assemble both high-expressed and low-expressed transcripts and outperform existing assemblers in terms of sensitivity and specificity for both simulated and real data.

Availability

http://www.cs.hku.hk/~alse/idba_tran.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Peng Y

PROVIDER: S-EPMC3694675 | biostudies-literature | 2013 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

IDBA-tran: a more robust de novo de Bruijn graph assembler for transcriptomes with uneven expression levels.

Peng Yu Y Leung Henry C M HC Yiu Siu-Ming SM Lv Ming-Ju MJ Zhu Xin-Guang XG Chin Francis Y L FY

Bioinformatics (Oxford, England) 20130701 13

<h4>Motivation</h4>RNA sequencing based on next-generation sequencing technology is effective for analyzing transcriptomes. Like de novo genome assembly, de novo transcriptome assembly does not rely on any reference genome or additional annotation information, but is more difficult. In particular, isoforms can have very uneven expression levels (e.g. 1:100), which make it very difficult to identify low-expressed isoforms. One challenge is to remove erroneous vertices/edges with high multiplicity ...[more]

PMID: 23813001

Similar Datasets

Project description:With the exponential growth of sequence information stored over the last decade, including that of de novo assembled contigs from RNA-Seq experiments, quantification of chimeric sequences has become essential when assembling read data. In transcriptomics, de novo assembled chimeras can closely resemble underlying transcripts, but patterns such as those seen between co-evolving sites, or mapped read counts, become obscured. We have created a de Bruijn based de novo assembler for RNA-Seq data that utilizes a classification system to describe the complexity of underlying graphs from which contigs are created. Each contig is labelled with one of three levels, indicating whether or not ambiguous paths exist. A by-product of this is information on the range of complexity of the underlying gene families present. As a demonstration of CStones ability to assemble high-quality contigs, and to label them in this manner, both simulated and real data were used. For simulated data, ten million read pairs were generated from cDNA libraries representing four species, Drosophila melanogaster, Panthera pardus, Rattus norvegicus and Serinus canaria. These were assembled using CStone, Trinity and rnaSPAdes; the latter two being high-quality, well established, de novo assembers. For real data, two RNA-Seq datasets, each consisting of ≈30 million read pairs, representing two adult D. melanogaster whole-body samples were used. The contigs that CStone produced were comparable in quality to those of Trinity and rnaSPAdes in terms of length, sequence identity of aligned regions and the range of cDNA transcripts represented, whilst providing additional information on chimerism. Here we describe the details of CStones assembly and classification process, and propose that similar classification systems can be incorporated into other de novo assembly tools. Within a related side study, we explore the effects that chimera's within reference sets have on the identification of differentially expression genes. CStone is available at: https://sourceforge.net/projects/cstone/.

Dataset Information

IDBA-tran: a more robust de novo de Bruijn graph assembler for transcriptomes with uneven expression levels.

Motivation

Availability

Supplementary information

Publications

IDBA-tran: a more robust de novo de Bruijn graph assembler for transcriptomes with uneven expression levels.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets