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nvidia / fq2bam

Algorithm Overview

Description

The Parabricks fq2bam tool is used to generate Binary Alignment Map (BAM)/Compressed Reference Oriented Alignment Map (CRAM) output using BWA-MEM and GATK best practices given pairs of pair-ended FASTQ files as input.
This algorithm is ready for commercial use.

fq2bam performs the following steps:

  • BWA-MEM alignment
  • Co-ordinate sorting
  • Mark duplicates
  • BQSR

BWA-MEM is a fast, accurate algorithm for mapping DNA sequence reads to a reference genome, performing local alignment and producing alignment for different parts of the query sequence. It is the default algorithm in Burrows-Wheeler Aligner (BWA) for reads that are longer than 70bp and is designed for high-throughput sequencing technologies such as Illumina and Pacific Biosciences.

Note that this is currently a minimal implementation of the full fq2bam tool. It accepts multiple pairs of FASTQ files but does not accept single-ended FASTQ files, nor does it accept known sites files or interval files. It does not currently produce a BQSR report, a duplicate metrics report or QC metrics.

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Note

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Terms of use

By using this software or model, you are agreeing to the NVIDIA Parabricks Terms of Use

References(s)

See the documentation for the Parabricks fq2bam tool.

Input

Input Type(s): Indices (Text, Binary)

Input Format(s): Tarball

Input Parameters: One Dimensional (1D)

Other Properties Related to Input: Text for FASTA file and associated indices; Binary for GZIP compressed FASTQ

Output

Output Type(s): Binary (Alignment, Index of the Alignment), Text (File Locations & Signing Identifiers, Chromosomes)

Output Format: BAM, BAM Index (BAI), .Txt, .Txt

Output Parameters: 1D

Other Properties Related to Output: BAM: file location

Software Integration

Supported Hardware Microarchitecture Platform(s):
Any NVIDIA GPU that supports CUDA architecture 70, 75, 80, 86, 89 or 90 and
has at least 24GB of GPU RAM.

  • Ampere
  • Hopper
  • Lovelace
  • Turing
  • Volta

Supported Operating System(s):

fq2bam runs inside a Docker container and is compatible with any operating system that supports Docker containers.

Model Version:

  • V4.2.1-1

Engine: Triton and PyTriton

Ethical Considerations:

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