msbwt2

Crates.iomsbwt2
lib.rsmsbwt2
version0.3.2
sourcesrc
created_at2021-09-09 16:10:39.912231
updated_at2023-02-01 13:53:23.252288
descriptionmsbwt2 - multi-string BWT query library
homepagehttps://github.com/HudsonAlpha/rust-msbwt
repositoryhttps://github.com/HudsonAlpha/rust-msbwt
max_upload_size
id448936
size198,752
Matt Holt (holtjma)

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README

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msbwt2

The intent of crate is to provide Rust functionality for querying a Multi-String BWT (MSBWT), and is mostly based on the same methodology used by the original msbwt.

NOTE: This is very much a work-in-progress and currently only being updated as a side project during spare time. If you have any feature requests, feel free to submit a new issue on GitHub. Here is a current list of planned additions:

  1. Incorporate the high-memory BWT implementation from fmlrc2
  2. Add some more query functionality
  3. Improve the performance of the built-in BWT construction tool (msbwt2-build)

Installation

All installation options assume you have installed Rust along with the cargo crate manager for Rust.

From Cargo

cargo install msbwt2
msbwt2-convert -h

From GitHub

git clone https://github.com/HudsonAlpha/rust-msbwt.git
cd rust-msbwt
#testing optional
cargo test --release
cargo build --release
./target/release/msbwt2-convert -h

Usage

MSBWT Building

The Multi-String Burrows Wheeler Transform (MSBWT or BWT) must be built prior to performing any queries. Currently, there are two ways to build the BWT with identical results:

  1. Using the built-in msbwt2-build tool. This approach will accept any combination of FASTQ or FASTA files that may be gzip-compressed.
    This method tends to be slower currently and is not parallelized (we hope to improve both of these over time). However, it is easier to use with different file types requires only msbwt2 to be installed:
msbwt2-build \
    -o comp_msbwt.npy \
    reads.fq.gz [reads2.fq.gz ...]
  1. Using an external tool and feeding that to msbwt2-convert. This approach tends to be faster currently. However, the following command is more complex, less flexible file typing (requiring FASTQ in this example), and requires the ropebwt2 executable (or a similar tool) to be installed:
gunzip -c reads.fq.gz [read2.fq.gz ...] | \
    awk 'NR % 4 == 2' | \
    sort | \
    tr NT TN | \
    ropebwt2 -LR | \
    tr NT TN | \
    msbwt2-convert comp_msbwt.npy

Queries

The general use case of the library is k-mer queries, which can be performed as follows:

use msbwt2::msbwt_core::BWT;
use msbwt2::rle_bwt::RleBWT;
use msbwt2::string_util;
let mut bwt = RleBWT::new();
let filename: String = "test_data/two_string.npy".to_string();
bwt.load_numpy_file(&filename);
assert_eq!(bwt.count_kmer(&string_util::convert_stoi(&"ACGT")), 1);

Reference

msbwt2 does not currently have a pre-print or paper. If you use msbwt2, please cite the one of the msbwt papers:

Holt, James, and Leonard McMillan. "Merging of multi-string BWTs with applications." Bioinformatics 30.24 (2014): 3524-3531.

Holt, James, and Leonard McMillan. "Constructing Burrows-Wheeler transforms of large string collections via merging." Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. 2014.

License

Licensed under either of

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.

Commit count: 96

cargo fmt