Meta-analysis of ChIP-seq Datasets through the Rank Aggregation Approach. / Kolmykov, Semyon K.; Kondrakhin, Yury V.; Sharipov, Ruslan N. et al.
Proceedings - 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 180-184 9214614 (Proceedings - 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
}
TY - GEN
T1 - Meta-analysis of ChIP-seq Datasets through the Rank Aggregation Approach
AU - Kolmykov, Semyon K.
AU - Kondrakhin, Yury V.
AU - Sharipov, Ruslan N.
AU - Yevshi, Ivan S.
AU - Ryabova, Anna S.
AU - Kolpakov, Fedor A.
N1 - Funding Information: ACKNOWLEDGMENT This study was supported by the Russian Science Foundation, grant № 19-14-00295. Publisher Copyright: © 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/7
Y1 - 2020/7
N2 - Understanding the basic mechanisms of transcription regulation is a major challenge in modern biology. Regulation of transcription is a complex process in which transcription factors (TFs) play a key role. Chromatin immunoprecipitation followed by high throughput sequencing is a widely and intensively used experimental technology for the identification of TF binding sites (TFBSs). Nowadays, there are tens or hundreds of ChIP-seq datasets measured for the same transcription factor. Meta-processing of such datasets into an integrated dataset is relevant. We have developed a novel method for creating these integrated datasets of TFBSs. This method consists of a three-stage application of the Rank Aggregation approach. The identified TFBSs can be sorted to further select the most reliable TFBSs. We have found a high saturation of site motifs in the most reliable TFBSs. We have also demonstrated that the most reliable TFBSs prefer to be located in open chromatin regions.
AB - Understanding the basic mechanisms of transcription regulation is a major challenge in modern biology. Regulation of transcription is a complex process in which transcription factors (TFs) play a key role. Chromatin immunoprecipitation followed by high throughput sequencing is a widely and intensively used experimental technology for the identification of TF binding sites (TFBSs). Nowadays, there are tens or hundreds of ChIP-seq datasets measured for the same transcription factor. Meta-processing of such datasets into an integrated dataset is relevant. We have developed a novel method for creating these integrated datasets of TFBSs. This method consists of a three-stage application of the Rank Aggregation approach. The identified TFBSs can be sorted to further select the most reliable TFBSs. We have found a high saturation of site motifs in the most reliable TFBSs. We have also demonstrated that the most reliable TFBSs prefer to be located in open chromatin regions.
KW - ChIP-seq
KW - GTRD database
KW - Meta-analysis
KW - normal mixture
KW - rank aggregation approach
KW - transcription factor binding sites
UR - http://www.scopus.com/inward/record.url?scp=85094822537&partnerID=8YFLogxK
UR - https://elibrary.ru/item.asp?id=45218605
UR - https://www.mendeley.com/catalogue/b5b0f4eb-3e39-396b-ba3b-aa9c7c094511/
U2 - 10.1109/CSGB51356.2020.9214614
DO - 10.1109/CSGB51356.2020.9214614
M3 - Conference contribution
AN - SCOPUS:85094822537
SN - 9781728195971
T3 - Proceedings - 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020
SP - 180
EP - 184
BT - Proceedings - 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Cognitive Sciences, Genomics and Bioinformatics, CSGB 2020
Y2 - 6 July 2020 through 10 July 2020
ER -
ID: 25999554