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16GT

Supporting data for "16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model"

Dataset type: Software
Data released on June 16, 2017

Luo R; Schatz MC; Salzberg SL (2017): Supporting data for "16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model" GigaScience Database. https://doi.org/10.5524/100316

DOI10.5524/100316

16GT is a variant caller for Illumina whole-genome and whole-exome sequencing data. It uses a new 16-genotype probabilistic model to unify SNP and indel calling in a single variant calling algorithm. In benchmark comparisons with five other widely used variant callers on a modern 36-core server, 16GT demonstrated improved sensitivity in calling SNPs, and it provided comparable sensitivity and accuracy for calling indels as compared to the GATK HaplotypeCaller. 16GT is available at https://github.com/aquaskyline/16GT.

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Additional details

Read the peer-reviewed publication(s):

  • Luo, R., Schatz, M. C., & Salzberg, S. L. (2017). 16GT: a fast and sensitive variant caller using a 16-genotype probabilistic model. GigaScience, 6(7). https://doi.org/10.1093/gigascience/gix045 (PubMed:28637275)

Additional information:

https://github.com/aquaskyline/16GT

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File Name Description Sample ID Data Type File Format Size Release Date File Attributes Download
Readme TEXT 1.55 kB 2017-06-13 MD5 checksum: bcdfaf881fa591b3f73eae89814be06b
Archival copy of the 16GT software, downloaded 10-Jun-2017, from Github Repo https://github.com/aquaskyline/16GT please visit GitHub for most recent updates. GitHub archive zip 1.36 MB 2017-06-13
NA12878 BWA-MEM alignment Alignments BAM 116.14 GB 2017-06-13 MD5 checksum: fbd3764bc51f271b885df8fe38647d22
NA12878 GIAB-2.18 truth dataset Alignments UNKNOWN 24.50 MB 2017-06-13
NA12878 GIAB-2.18 truth dataset Sequence variants VCF 327.25 MB 2017-06-13
Variant identified using 16GT Sequence variants VCF 2.26 GB 2017-06-13 MD5 checksum: 0f30ad82d4957e32249120dc3c27ff74
Variant identified using GATK UnifiedGenotyper Sequence variants VCF 1.35 GB 2017-06-13 MD5 checksum: 0dd0707728e5a7737a5ef8b0f7396c1d
Variant identified using GATK HaplotypeCaller Sequence variants VCF 1.22 GB 2017-06-13 MD5 checksum: e7e1fd9e26edc9096d65b59292001063
Variant identified using Freebayes Sequence variants VCF 1.97 GB 2017-06-13 MD5 checksum: c636b74a5c3a425da8074fcd147e50fe
Variant identified using Fermikit Sequence variants VCF 279.01 MB 2017-06-13 MD5 checksum: b65e1144ad9bb0158847471094111558
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Code Ocean:

Date Action
June 14, 2017 Dataset publish
October 2, 2017 Manuscript Link added : 10.1093/gigascience/gix045
November 9, 2022 Manuscript Link updated : 10.1093/gigascience/gix045