• Transcriptome assembly and qua...

Treffer: Transcriptome assembly and quantification from Ion Torrent RNA-Seq data.

Title:
Transcriptome assembly and quantification from Ion Torrent RNA-Seq data.
Authors:
Mangul S, Caciula A, Al Seesi S, Brinza D, Mӑndoiu I, Zelikovsky A
Source:
BMC genomics [BMC Genomics] 2014; Vol. 15 Suppl 5, pp. S7. Date of Electronic Publication: 2014 Jul 14.
Publication Type:
Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.
Language:
English
Journal Info:
Publisher: BioMed Central Country of Publication: England NLM ID: 100965258 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1471-2164 (Electronic) Linking ISSN: 14712164 NLM ISO Abbreviation: BMC Genomics Subsets: MEDLINE
Imprint Name(s):
Original Publication: London : BioMed Central, [2000-
MeSH Terms:
Transcriptome*, High-Throughput Nucleotide Sequencing/*methods , Sequence Analysis, RNA/*methods, Algorithms ; Alternative Splicing ; Humans ; Likelihood Functions ; Sequence Alignment ; Software
References:
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Grant Information:
R01-GM083198 United States GM NIGMS NIH HHS; U01-DA024417 United States DA NIDA NIH HHS; R01-ES022282 United States ES NIEHS NIH HHS; P01-HL28481 United States HL NHLBI NIH HHS; R01-MH101782 United States MH NIMH NIH HHS; K25-HL080079 United States HL NHLBI NIH HHS; P01-HL30568 United States HL NHLBI NIH HHS
Entry Date(s):
Date Created: 20140802 Date Completed: 20141121 Latest Revision: 20240321
Update Code:
20260130
PubMed Central ID:
PMC4120146
DOI:
10.1186/1471-2164-15-S5-S7
PMID:
25082147
Database:
MEDLINE

Weitere Informationen

Background: High throughput RNA sequencing (RNA-Seq) can generate whole transcriptome information at the single transcript level providing a powerful tool with multiple interrelated applications including transcriptome reconstruction and quantification. The sequences of novel transcripts can be reconstructed from deep RNA-Seq data, but this is computationally challenging due to sequencing errors, uneven coverage of expressed transcripts, and the need to distinguish between highly similar transcripts produced by alternative splicing. Another challenge in transcriptomic analysis comes from the ambiguities in mapping reads to transcripts.
Results: We present MaLTA, a method for simultaneous transcriptome assembly and quantification from Ion Torrent RNA-Seq data. Our approach explores transcriptome structure and incorporates a maximum likelihood model into the assembly and quantification procedure. A new version of the IsoEM algorithm suitable for Ion Torrent RNA-Seq reads is used to accurately estimate transcript expression levels. The MaLTA-IsoEM tool is publicly available at: http://alan.cs.gsu.edu/NGS/?q=malta
Conclusions: Experimental results on both synthetic and real datasets show that Ion Torrent RNA-Seq data can be successfully used for transcriptome analyses. Experimental results suggest increased transcriptome assembly and quantification accuracy of MaLTA-IsoEM solution compared to existing state-of-the-art approaches.