Open-Omics-Acceleration-Framework-2.2

v2.2 release adds and updates to docker files of major pipelines

• Adds a docker file for the fq2sortedbam pipeline
• Adds support for minimap2 and extends fq2sortedbam pipeline for long reads analysis
• Provides standalone dockers for the pre-processing and inference stages of the AlphaFold2 pipeline
• Provides standalone dockers for fq2sortedbam and Deepvariant-based inference stages of the DeepVariant-based germline fq2vcf pipeline

Open-Omics-Acceleration-Framework-2.1

v2.1 release updates and adds fixes to AlphaFold2 pipeline and DeepVariant-based germline fq2vcf pipeline.

• AlphaFold2-based protein folding pipeline:

  • Enabled inference using different models
  • Bug fixes for running Model 3, 4, & 5.
  • Removed unnecessary paths from run script.
  • Enabled use of contiguous tensor inside TPP PyTorch extension

• DeepVariant-based germline variant calling (fq2vcf) pipeline :

  • Enabled support for gzipped reference sequence file as input
  • Enabled support for reads and reference sequence data files to be in different folders
  • Enabled cleanup of all intermediate data generated during the pipeline's run
  • Provided an option to keep the intermediate SAM files out of bwa-mem2
  • Fixed the messaging to the user in case of a failed run
  • Updated README with precise instructions to run on various types of compute environments
  • In AWS parallel cluster environment: enabled index creation on a compute node instead of the master node
  • Added details in README about memory and disk requirements for a run using a Human WGS dataset

Open-Omics-Acceleration-Framework-2.0

This v2.0 release adds the accelerated version of following new pipelines and corresponding tools.

• Containerized AlphaFold2-based pipeline for protein folding that takes protein sequences as input and outputs predicted protein structures. It consists of

  • Open-Omics-AlphaFold: a PyTorch implementation of AlphaFold2 (v.2.2.2) monomer accelerated using 4th generation Intel® Xeon® CPU.
  • Hmmer and HH-suite accelerated through 256- and 512-bit SIMD instructions (AVX2, AVX512) available on modern x86 CPUs.
  • Efficient load balanced folding of multiple proteins in parallel on a dual-socket CPU.
  • A docker file for seamless installation and execution.
  • Can perform folding on proteins of length up to ~9k residues on a 1 TB memory machine.
  • To the best of our knowledge, faster than any prior CPU/GPU implementation for folding a set of proteins.

• Containerized DeepVariant-based variant calling (fq2vcf) pipeline that takes paired fastq.gz files as input and outputs vcf file. It achieves efficient performance across multiple CPU nodes and consists of

  • BWA-MEM2: an architecture-efficient version of BWA-MEM that is 1.8-3.0 times faster.
  • SAMtools sort utility for sorting SAM/BAM files.
  • Open-Omics-DeepVariant: A new version of DeepVariant v1.5.0 accelerated using 4th generation Intel® Xeon® CPU.
  • A distributed memory framework that achieves excellent scaling for this pipeline across several CPU nodes.
  • To the best of our knowledge, faster than any prior CPU/GPU implementation for 30x WGS dataset.

• A fq2sortedbam pipeline accelerated using modern CPUs that takes read fastq files as input and outputs a sorted BAM file. It consists of

  • BWA-MEM2: an architecture-efficient version of BWA-MEM that is 1.8-3.0 times faster.
  • SAMtools sort utility for sorting SAM/BAM files.

v1.0

First version of Open Omics Acceleration Framework containing the accelerated versions of the following tools and pipelines of digital biology.

Tools:

• BWA-MEM2: accelerated version of BWA-MEM
• MM2-Fast: accelerated version of minimap2
• UMAP_fast: accelerated version of UMAP algorithm used for visualization
• Accelerated version of AtacWorks that performs denoising of ATAC-Seq data

Pipelines

• A Single cell RNA-Seq analysis pipeline for clustering cells starting with a cell-by-gene matrix.