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@inproceedings{2342098,
author = {Lexa, Matej and Hegyi, Hedvig},
address = {Bratislava},
booktitle = {Workshop on Bioinformatics and Computational Biology (WBCB 2023)},
editor = {Bronislava Brejova, Matej Lexa},
keywords = {HiC analysis},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Bratislava},
isbn = {978-80-8147-132-2},
pages = {14-14},
publisher = {Knižniˇcné a ediˇcné centrum, Fakulta matematiky, fyziky a informatiky, Univerzita Komenského},
title = {Alternatives to classical HiC data analysis},
url = {https://compbio.fmph.uniba.sk/epubs/proceedingsWBCB2023.pdf},
year = {2023}
}
TY - JOUR
ID - 2342098
AU - Lexa, Matej - Hegyi, Hedvig
PY - 2023
TI - Alternatives to classical HiC data analysis
PB - Knižniˇcné a ediˇcné centrum, Fakulta matematiky, fyziky a informatiky, Univerzita Komenského
CY - Bratislava
SN - 9788081471322
KW - HiC analysis
UR - https://compbio.fmph.uniba.sk/epubs/proceedingsWBCB2023.pdf
N2 - HiC is a variant of DNA library preparation and sequencing that can provide information about 3D arrangement patterns in chromatin. A typical HiC experiment involves cross-linking chromatin in vivo, fragmenting it in vitro, ligating the fragments in a proximity-dependent manner. Finally a library for paired-end sequencing is created and sequenced by short read sequencing technology [3]. The typical HiC data analysis today is to preprocess HiC sequencing reads, map them to the closest reference genome, and bin mapped pairs by genomic location to obtain a contact matrix that can be visualized. Reliable tools and pipelines exist to carry out such analyses.
ER -
LEXA, Matej a Hedvig HEGYI. Alternatives to classical HiC data analysis. Online. In Bronislava Brejova, Matej Lexa. \textit{Workshop on Bioinformatics and Computational Biology (WBCB 2023)}. Bratislava: Knižniˇcné a ediˇcné centrum, Fakulta matematiky, fyziky a informatiky, Univerzita Komenského, 2023, s.~14-14. ISBN~978-80-8147-132-2.
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