DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

Genome modeling and design across all domains of life

Biological foundation modeling from molecular to genome scale

Scalable gVCF merging and joint variant calling

Transformer-based sequence correction method for genome assembly polishing

DeepSomatic is an analysis pipeline that uses a deep neural network to call somatic variants from tumor-normal and tumor-only sequencing data.

PEPPER-Margin-DeepVariant

DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.

Location of public benchmarking; primarily final results

minimizer-space de Bruijn graphs (mdBG) for whole genome assembly

The DevNet project on github stores the PacBio DevNet website.

GIAB pipeline for benchmarking genome assemblies

Wavefront alignment algorithm (WFA): Fast and exact gap-affine pairwise alignment

Genomics Extension for SQLite

Code examples of fast and simple k-mer counters for tutorial purposes

Hifiasm: a haplotype-resolved assembler for accurate Hifi reads

Segmental Duplication Assembler (SDA).

Implicit Interval Tree with Interpolation Index

The next version of bwa-mem

Public Benchmark of Long-Read Structural Variant Caller on PacBio CCS HG002 Data

Calling deletions using deep convolutional neural

Runs a combination of tools to generate structural variant calls on whole-genome sequencing data

Clairvoyante: a multi-task convolutional deep neural network for variant calling in Single Molecule Sequencing

Python and C++ code for reading and writing genomics data.

DCNet — Denoising (DNA) Sequence With a LSTM-RNN and PyTorch & Neural DBG

Validation runs using bcbio: germline, somatic, structural variant calling and RNA-seq analyses

An ultra-fast all-in-one FASTQ preprocessor (QC/adapters/trimming/filtering/splitting/merging...)