<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Lou S</submitter><funding>National Institute of General Medical Sciences</funding><funding>NIGMS NIH HHS</funding><pagination>e0287521</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC10793909</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>19(1)</volume><pubmed_abstract>The ability to simulate high-throughput data with high fidelity to real experimental data is fundamental for benchmarking methods used to detect true long-range chromatin interactions mediated by a specific protein. Yet, such tools are not currently available. To fill this gap, we develop an in silico experimental procedure, ChIA-Sim, which imitates the experimental procedures that produce real ChIA-PET, Hi-ChIP, or PLAC-seq data. We show the fidelity of ChIA-Sim to real data by using guiding characteristics of several real datasets to generate data using the simulation procedure. We also used ChIA-Sim data to demonstrate the use of our in silico procedure in benchmarking methods for significant interactions analysis by evaluating four methods for significant interaction calling (SIC). In </pubmed_abstract><journal>PloS one</journal><pubmed_title>An in silico procedure for generating protein-mediated chromatin interaction data and comparison of significant interaction calling methods.</pubmed_title><pmcid>PMC10793909</pmcid><funding_grant_id>R01 GM114142</funding_grant_id><funding_grant_id>R01GM114142</funding_grant_id><pubmed_authors>Lin S</pubmed_authors><pubmed_authors>Lou S</pubmed_authors></additional><is_claimable>false</is_claimable><name>An in silico procedure for generating protein-mediated chromatin interaction data and comparison of significant interaction calling methods.</name><description>The ability to simulate high-throughput data with high fidelity to real experimental data is fundamental for benchmarking methods used to detect true long-range chromatin interactions mediated by a specific protein. Yet, such tools are not currently available. To fill this gap, we develop an in silico experimental procedure, ChIA-Sim, which imitates the experimental procedures that produce real ChIA-PET, Hi-ChIP, or PLAC-seq data. We show the fidelity of ChIA-Sim to real data by using guiding characteristics of several real datasets to generate data using the simulation procedure. We also used ChIA-Sim data to demonstrate the use of our in silico procedure in benchmarking methods for significant interactions analysis by evaluating four methods for significant interaction calling (SIC). In </description><dates><release>2024-01-01T00:00:00Z</release><publication>2024</publication><modification>2026-05-29T11:21:15.757Z</modification><creation>2025-04-06T12:18:43.395Z</creation></dates><accession>S-EPMC10793909</accession><cross_references><pubmed>38232107</pubmed><doi>10.1371/journal.pone.0287521</doi></cross_references></HashMap>