Abstract
RNA-seq reads are sampled from the underlying human transcriptome sequence, consisting of hundreds of thousands of mRNA transcripts. De novo transcriptome reconstruction from RNA-seq reads is a promising approach but facing algorithmic and computational challenges derived from nonlinear transcript structures and ultra high-throughput read counts. To tackle this issue, we designed a divide-and-conquer strategy to perform reads localization followed by a novel algorithm to assemble reads de novo. Using simulation studies, we have demonstrated a high accuracy in transcriptome structures reconstruction.
| Original language | English (US) |
|---|---|
| Title of host publication | 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011 |
| Pages | 26-33 |
| Number of pages | 8 |
| DOIs | |
| State | Published - 2011 |
| Event | 2011 IEEE International Conference onBioinformatics and Biomedicine Workshops, BIBMW 2011 - Atlanta, GA, United States Duration: Nov 12 2011 → Nov 15 2011 |
Other
| Other | 2011 IEEE International Conference onBioinformatics and Biomedicine Workshops, BIBMW 2011 |
|---|---|
| Country | United States |
| City | Atlanta, GA |
| Period | 11/12/11 → 11/15/11 |
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Keywords
- de novo assembly
- read mapping
- RNA-seq
- transcriptome
ASJC Scopus subject areas
- Biomedical Engineering
- Health Informatics
- Health Information Management
Cite this
SPATA : A seeding and patching algorithm for de novo transcriptome assembly. / Zhao, Zhiyu; Nguyen, Tin Chi; Deng, Nan; Johnson, Kristen Marie; Zhu, Dongxiao.
2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011. 2011. p. 26-33 6112351.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - SPATA
T2 - A seeding and patching algorithm for de novo transcriptome assembly
AU - Zhao, Zhiyu
AU - Nguyen, Tin Chi
AU - Deng, Nan
AU - Johnson, Kristen Marie
AU - Zhu, Dongxiao
PY - 2011
Y1 - 2011
N2 - RNA-seq reads are sampled from the underlying human transcriptome sequence, consisting of hundreds of thousands of mRNA transcripts. De novo transcriptome reconstruction from RNA-seq reads is a promising approach but facing algorithmic and computational challenges derived from nonlinear transcript structures and ultra high-throughput read counts. To tackle this issue, we designed a divide-and-conquer strategy to perform reads localization followed by a novel algorithm to assemble reads de novo. Using simulation studies, we have demonstrated a high accuracy in transcriptome structures reconstruction.
AB - RNA-seq reads are sampled from the underlying human transcriptome sequence, consisting of hundreds of thousands of mRNA transcripts. De novo transcriptome reconstruction from RNA-seq reads is a promising approach but facing algorithmic and computational challenges derived from nonlinear transcript structures and ultra high-throughput read counts. To tackle this issue, we designed a divide-and-conquer strategy to perform reads localization followed by a novel algorithm to assemble reads de novo. Using simulation studies, we have demonstrated a high accuracy in transcriptome structures reconstruction.
KW - de novo assembly
KW - read mapping
KW - RNA-seq
KW - transcriptome
UR - http://www.scopus.com/inward/record.url?scp=84855992328&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84855992328&partnerID=8YFLogxK
U2 - 10.1109/BIBMW.2011.6112351
DO - 10.1109/BIBMW.2011.6112351
M3 - Conference contribution
SN - 9781457716133
SP - 26
EP - 33
BT - 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops, BIBMW 2011
ER -