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. http://dx.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.

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). doi:10.1093/gigascience/gix045

Additional information:

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





File NameSample IDData TypeFile FormatSizeRelease Date 
GitHub archivezip1.3 MB2017-06-13
Sequence variantsVCF2.11 GB2017-06-13
Sequence variantsVCF266.08 MB2017-06-13
Sequence variantsVCF1.83 GB2017-06-13
Sequence variantsVCF1.13 GB2017-06-13
Sequence variantsVCF481.16 MB2017-06-13
AlignmentsBAM108.16 GB2017-06-13
AlignmentsUNKNOWN23.37 MB2017-06-13
Sequence variantsVCF312.09 MB2017-06-13
ReadmeTEXT1.51 KB2017-06-13
Displaying 1-10 of 12 File(s).

Code Ocean:

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