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Dataset . 2020
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Dataset . 2020
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https://doi.org/10.5281/zenodo...
Dataset . 2020
License: CC BY
Data sources: Sygma
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Chromosight benchmarks and processed data

Authors: Matthey-Doret, Cyril; Montagne, Rémi; Baudry, Lyam; Cournac, Axel;

Chromosight benchmarks and processed data

Abstract

Input data and scripts required to rerun chromosight's benchmarks and associated figures from the manuscript, as well as output results in text format. The record contains 3 tarballs corresponding to two different benchmarks and various processed files. Each tarball contains the scripts, input and output data of its benchmark: Performance benchmark: This benchmark is contained in "20200406_benchmark_chromosight_performance.tar.gz" and compares chromosight running time and RAM use with 2 other softwares. This benchmark is run on a real high resolution human Hi-C matrix with different subsampling values. Benchmark scripts are expected to be run on a regular laptop or desktop. Results benchmark: This benchmark is contained in "20200406_benchmark_chromosight_results.tar.gz" and assess chromosight's ability to detect chromatin loop patterns on Hi-C contact maps. Chromosight is compared to 4 other softwares. For each software, precision, recall (=sensitivity) and F1 scores are measured using 2000 small synthetic Hi-C matrices with known loop coordinates. Each software is run with a range of 50-200 parameter combinations for all data. Scripts to run this benchmark are written to run as a job array on a SLURM computing cluster to reduce compute time. Processed data files Intermediate and output files used throughout the manuscript. This includes contact matrices in cool format, genomic intervals in BED or BED2D format and loop calls from public data for different softwares.

Related Organizations
Keywords

benchmark, Hi-C, Loop detection

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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