BMC GenomicsBioinformaticsPeer-reviewed journal article
TraRECo: A Greedy Approach based de novo Transcriptome Assembler with Read Error Correction using Consensus Matrix
Seokhyun YooniD, Daeseung KimiD, Keunsoo KangiD, Woong June ParkiD
Abstract
BackgroundChallenges in developing a good de novo transcriptome assembler include how to deal with read errors and sequence repeats. Almost all de novo assemblers utilize de Bruijn graph, which has a complexity linearly growing with data size while suffers from errors and repeat. Although one can correct errors by inspecting topological structure of the graph, it is an uneasy task when there are too many branches. There are two research directions: improving either graph reliability or path search precision. We focused on improving the reliability.\n\nResultsWe present TraRECo, a greedy approach to de novo assembly employing error-aware graph construction. The idea is similar to overlap-layout-consensus approach used for genome assembly, but is different in that consensus is made through the entire graph construction step. Basically, we built contigs by direct read alignment within a distance margin and performed junction search to construct splicing graphs. While doing so, however, a contig of length l was represented by 4x1 matrix (called consensus matrix), of which each element was the base count of aligned reads so far. A representative sequence is obtained, by taking majority in each column of the consensus matrix, to be used for further read alignment. Once splicing graphs were obtained, we used IsoLasso to find paths with noticeable read depth. The experiments using real and simulated reads showed that the method provides considerable improvements in sensitivity and reasonably better performances when comparing both sensitivity and precision. This could be achieved by making more erroneous reads to be participated in graph construction, which, in turn, improved the depth information quality used for the subsequent path search step. The results for simulated reads showed also challenges are still remaining since non-negligible percentage of transcripts with high abundance were not recovered by the assemblers we considered.\n\nConclusionde novo assembly is mainly to explore not-yet-discovered isoforms and must be able to represent as much reads as possible in an efficient way. In this sense, TraRECo provides us a potential alternative to improve graph reliability, even though the computational burden can be much higher than single k-mer de Bruijn graph approach.
- assay: long-read sequencing
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: variant calling
- approach: statistical model
- Citations
- 4
- FWCI
- 0.18
- Field percentile
- 48th percentile
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