Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings - DCC 2017 |
| Untertitel | 2017 Data Compression Conference |
| Herausgeber/-innen | Ali Bilgin, Joan Serra-Sagrista, Michael W. Marcellin, James A. Storer |
| Herausgeber (Verlag) | Institute of Electrical and Electronics Engineers Inc. |
| Seiten | 444 |
| Seitenumfang | 1 |
| ISBN (elektronisch) | 9781509067213 |
| Publikationsstatus | Veröffentlicht - Mai 2017 |
| Veranstaltung | 2017 Data Compression Conference, DCC 2017 - Snowbird, USA / Vereinigte Staaten Dauer: 4 Apr. 2017 → 7 Apr. 2017 |
Publikationsreihe
| Name | Data Compression Conference Proceedings |
|---|---|
| Band | Part F127767 |
| ISSN (Print) | 1068-0314 |
Abstract
High-Throughput sequencing of RNA molecules has enabled the quantitative analysis of the expression of genes at the expense of storage space and processing power. To help alleviate these problems, lossy compression methods of the quality scores associated to RNA sequence data have recently been proposed, and the evaluation of their impact on downstream analysis is gaining attention. This work presents a first assessment of the impact of lossily compressed quality scores in RNA sequence data on the performance of some of the most recent tools used for differential gene expression.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Computernetzwerke und -kommunikation
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Proceedings - DCC 2017: 2017 Data Compression Conference. Hrsg. / Ali Bilgin; Joan Serra-Sagrista; Michael W. Marcellin; James A. Storer. Institute of Electrical and Electronics Engineers Inc., 2017. S. 444 7923727 (Data Compression Conference Proceedings; Band Part F127767).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Abstract in Konferenzband › Forschung › Peer-Review
}
TY - CHAP
T1 - Differential gene expression with lossy compression of quality scores in RNA-seq data
AU - Hernandez-Lopez, Ana A.
AU - Voges, Jan
AU - Alberti, Claudio
AU - Mattavelli, Marco
AU - Ostermann, Jörn
PY - 2017/5
Y1 - 2017/5
N2 - High-Throughput sequencing of RNA molecules has enabled the quantitative analysis of the expression of genes at the expense of storage space and processing power. To help alleviate these problems, lossy compression methods of the quality scores associated to RNA sequence data have recently been proposed, and the evaluation of their impact on downstream analysis is gaining attention. This work presents a first assessment of the impact of lossily compressed quality scores in RNA sequence data on the performance of some of the most recent tools used for differential gene expression.
AB - High-Throughput sequencing of RNA molecules has enabled the quantitative analysis of the expression of genes at the expense of storage space and processing power. To help alleviate these problems, lossy compression methods of the quality scores associated to RNA sequence data have recently been proposed, and the evaluation of their impact on downstream analysis is gaining attention. This work presents a first assessment of the impact of lossily compressed quality scores in RNA sequence data on the performance of some of the most recent tools used for differential gene expression.
KW - differential gene expression
KW - Lossy compression
KW - RNA-seq
UR - http://www.scopus.com/inward/record.url?scp=85019968467&partnerID=8YFLogxK
U2 - 10.1109/dcc.2017.75
DO - 10.1109/dcc.2017.75
M3 - Conference abstract
AN - SCOPUS:85019968467
T3 - Data Compression Conference Proceedings
SP - 444
BT - Proceedings - DCC 2017
A2 - Bilgin, Ali
A2 - Serra-Sagrista, Joan
A2 - Marcellin, Michael W.
A2 - Storer, James A.
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 Data Compression Conference, DCC 2017
Y2 - 4 April 2017 through 7 April 2017
ER -