HPTAD: A computational method to identify topologically associating domains from HiChIP and PLAC-seq datasets.
HPTAD: A computational method to identify topologically associating domains from HiChIP and PLAC-seq datasets.
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DOI:
10.1016/j.csbj.2023.01.003
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发表时间:
2023
影响因子:
6
通讯作者:
Li, Yun
中科院分区:
文献类型:
--
作者:
Rosen, Jonathan;Lee, Lindsay;Abnousi, Armen;Chen, Jiawen;Wen, Jia;Hu, Ming;Li, Yun
High-throughput chromatin conformation capture technologies, such as Hi-C and Micro-C, have enabled genome-wide view of chromatin spatial organization. Most recently, Hi-C-derived enrichment-based technologies, including HiChIP and PLAC-seq, offer attractive alternatives due to their high signal-to-noise ratio and low cost. While a series of computational tools have been developed for Hi-C data, methods tailored for HiChIP and PLAC-seq data are still under development. Here we present HPTAD, a computational method to identify topologically associating domains (TADs) from HiChIP and PLAC-seq data. We performed comprehensive benchmark analysis to demonstrate its superior performance over existing TAD callers designed for Hi-C data. HPTAD is freely available at https://github.com/yunliUNC/HPTAD.
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DOI:
10.1093/bioinformatics/btu443
发表时间:
2014-09-01
期刊:
Bioinformatics (Oxford, England)
影响因子:
--
作者:
Lévy-Leduc C;Delattre M;Mary-Huard T;Robin S
通讯作者:
Robin S
影响因子:
48
作者:
Norton HK;Emerson DJ;Huang H;Kim J;Titus KR;Gu S;Bassett DS;Phillips-Cremins JE
通讯作者:
Phillips-Cremins JE
DOI:
10.1186/1748-7188-9-14
发表时间:
2014
期刊:
Algorithms for molecular biology : AMB
影响因子:
--
作者:
Filippova D;Patro R;Duggal G;Kingsford C
通讯作者:
Kingsford C
DOI:
10.1038/nrg3454
发表时间:
2013-06
期刊:
Nature reviews. Genetics
影响因子:
--
作者:
通讯作者:
--
影响因子:
64.8
作者:
Dixon JR;Jung I;Selvaraj S;Shen Y;Antosiewicz-Bourget JE;Lee AY;Ye Z;Kim A;Rajagopal N;Xie W;Diao Y;Liang J;Zhao H;Lobanenkov VV;Ecker JR;Thomson JA;Ren B
通讯作者:
Ren B