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v1.10.0-beta source code.tar.gz (110.8 MB)
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| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| Parent folder | |||
| DeepVariant 1.6.0 source code.tar.gz | 2023-10-23 | 102.0 MB | |
| DeepVariant 1.6.0 source code.zip | 2023-10-23 | 102.5 MB | |
| README.md | 2023-10-23 | 1.6 kB | |
| Totals: 3 Items | 204.5 MB | 0 | |
- Improved support for haploid regions, chrX and chY. Users can specify haploid regions with a flag. Updated case studies show usage and metrics.
- Added pangenome workflow (FASTQ-to-VCF mapping with VG and DeepVariant calling). Case study demonstrates improved accuracy
- Substantial improvements to DeepTrio de novo accuracy by specifically training DeepTrio for this use case (for chr20 at 30x HG002-HG003-HG004, false negatives reduced from 8 to 0 with DeepTrio v1.4, false positives reduced from 5 to 0).
- We have added multi-processing ability in
postprocess_variantswhich reduces 48 minutes to 30 minutes for Illumina WGS and 56 minutes to 33 minutes with PacBio. - We have added new models trained with Complete genomics data, and added case studies.
- We have added NovaSeqX to the training data for the WGS model.
- We have migrated our training and inference platform from Slim to Keras.
- Force calling with approximate phasing is now available.
We are sincerely grateful to
* @wkwan and @paulinesho for the contribution to helping in Keras move.
* @lucasbrambrink for enabling multiprocessing in postprocess_variants.
* @msamman, @akiraly1 for their contributions.
* PacBio: William Rowell (@williamrowell), Nathaniel Echols for their feedback and testing.
* UCSC: Benedict Paten(benedictpaten), Shloka Negi (@shlokanegi), Jimin Park (@jimin001), Mobin Asri (@mobinasri) for the feedback.
