Details
Original language | English |
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Title of host publication | Proceedings - DCC 2018 |
Subtitle of host publication | 2018 Data Compression Conference |
Editors | Ali Bilgin, James A. Storer, Joan Serra-Sagrista, Michael W. Marcellin |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 167-176 |
Number of pages | 10 |
ISBN (electronic) | 9781538648834 |
Publication status | Published - Jul 2018 |
Event | 2018 Data Compression Conference, DCC 2018 - Snowbird, United States Duration: 27 Mar 2018 → 30 Mar 2018 |
Publication series
Name | Data Compression Conference Proceedings |
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Volume | 2018-March |
ISSN (Print) | 1068-0314 |
Abstract
High-throughput sequencing of RNA molecules has enabled the quantitative analysis of gene expression at the expense of storage space and processing power. To alleviate these problems, lossy compression methods of the quality scores associated to RNA sequencing data have recently been proposed, and the evaluation of their impact on downstream analyses is gaining attention. In this context, this work presents a first assessment of the impact of lossily compressed quality scores in RNA sequencing data on the performance of some of the most recent tools used for differential gene expression.
Keywords
- Gene expression, Lossy compression, Quality scores, RNA seq
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
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Proceedings - DCC 2018: 2018 Data Compression Conference. ed. / Ali Bilgin; James A. Storer; Joan Serra-Sagrista; Michael W. Marcellin. Institute of Electrical and Electronics Engineers Inc., 2018. p. 167-176 (Data Compression Conference Proceedings; Vol. 2018-March).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Lossy compression of quality scores in differential gene expression
T2 - 2018 Data Compression Conference, DCC 2018
AU - Hernandez-Lopez, Ana A.
AU - Voges, Jan
AU - Alberti, Claudio
AU - Mattavelli, Marco
AU - Ostermann, Jörn
PY - 2018/7
Y1 - 2018/7
N2 - High-throughput sequencing of RNA molecules has enabled the quantitative analysis of gene expression at the expense of storage space and processing power. To alleviate these problems, lossy compression methods of the quality scores associated to RNA sequencing data have recently been proposed, and the evaluation of their impact on downstream analyses is gaining attention. In this context, this work presents a first assessment of the impact of lossily compressed quality scores in RNA sequencing 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 gene expression at the expense of storage space and processing power. To alleviate these problems, lossy compression methods of the quality scores associated to RNA sequencing data have recently been proposed, and the evaluation of their impact on downstream analyses is gaining attention. In this context, this work presents a first assessment of the impact of lossily compressed quality scores in RNA sequencing data on the performance of some of the most recent tools used for differential gene expression.
KW - Gene expression
KW - Lossy compression
KW - Quality scores
KW - RNA seq
UR - http://www.scopus.com/inward/record.url?scp=85050981624&partnerID=8YFLogxK
U2 - 10.1109/DCC.2018.00025
DO - 10.1109/DCC.2018.00025
M3 - Conference contribution
AN - SCOPUS:85050981624
T3 - Data Compression Conference Proceedings
SP - 167
EP - 176
BT - Proceedings - DCC 2018
A2 - Bilgin, Ali
A2 - Storer, James A.
A2 - Serra-Sagrista, Joan
A2 - Marcellin, Michael W.
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 March 2018 through 30 March 2018
ER -