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ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Claim

Benchmarking of sequencing technologies defines optimal strategies for genetic variants detection in a human genome

Research datakeyboard_double_arrow_right Dataset 04 Mar 2026Publisher:Zenodo
Authors: Eveleigh, Robert; Galvez, Jose Hector; Reiling, Sarah; Bourgey, Mathieu; Bourque, Guillaume; Ragoussis, Ioannis;

doi: 10.5281/zenodo.18868531 , 10.5281/zenodo.18868532

Benchmarking of sequencing technologies defines optimal strategies for genetic variants detection in a human genome

Abstract

This dataset includes processed benchmarking data for different sequencing technologies using the GIAB GM24385 (H0002) cell line. Files include: Single nucleotide variant (SNV) calls from several callers and different sequencing technologies. Callers include: Clair3, DeepVariant, Dragen, and GATK. Structural variant (SV) calls from several callers and different sequencing technologies. Callers include: Dragen, Sniffles2, CuteSV, SVIM, and others. Quality assesment metrics as tab delimited files (TSV). Benchmarking results using Truvari and HapPy. 

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citations
The total number of citations received by all articles of the researcher of interest.
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!
0
Average
Average
Average
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