Benchmarking alignment strategies for Hi-C reads in metagenomic Hi-C data.

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Bibliographic Details
Title: Benchmarking alignment strategies for Hi-C reads in metagenomic Hi-C data.
Authors: Wang Y; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, 90089, CA, USA., Zuo W; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, 90089, CA, USA., Huang J; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, 90089, CA, USA., Sun F; Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, 90089, CA, USA. fsun@usc.edu., Du Y; Department of Electrical Engineering, The University of Texas at San Antonio, San Antonio, 78249, TX, USA. yuxuan.du@utsa.edu.
Source: Genome biology [Genome Biol] 2026 Jan 30; Vol. 27 (1). Date of Electronic Publication: 2026 Jan 30.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Ltd Country of Publication: England NLM ID: 100960660 Publication Model: Electronic Cited Medium: Internet ISSN: 1474-760X (Electronic) Linking ISSN: 14747596 NLM ISO Abbreviation: Genome Biol Subsets: MEDLINE
Database: MEDLINE Ultimate
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