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README.md

mlstverse

mlstverse is a general purpose identification software. Currently database for Mycobacterium species (consists of MTB complex and nontuberculous mycobacteria) is available.

Installation

Get source codes

> git clone https://github.com/ymatsumoto/mlstverse
> git clone https://github.com/ymatsumoto/mlstverse.Mycobacterium.db

Install software and dependencies

> R
>>> if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
>>> BiocManager::install("Rsamtools", version = "3.8")
>>> install.packages("devtools")
>>> devtools::install("mlstverse")
>>> devtools::install("mlstverse.Mycobacterium.db")

Prepare Loci sequences

Downloads Loci.fasta to your local strage. Loci.fasta is also included in mlstverse repository.

Usage

Preparing bam Files

Before identifying isolates using R scripts, prepare bam files. Mapping shotgun sequence reads should be mapped to Loci.fasta using any mapping software and indexed.

> bwa mem Loci.fasta input.fastq | samtools sort - -o out.bam
> samtools index out.bam

Identify example (R script)

library(mlstverse)
library(mlstverse.Mycobacterium.db)
filenames <- c("out.bam")
result <- mlstverse(filenames, threads=16)
print(result$score)

Options for mlstverse()

option default description
filenames (required) Character, locations of input bam files
mlstdb mlstverse.Mycobacterium.db (optional) MLST database
min_depth 0 (optional) Numeric, only use genes larger than the minimum reads depth
min_ratio 0.1 (optional) Numeric, only use genes larger than the ratio to maximum reads depth
th.pvalue 0.05 (optional) Numeric, filter by threshold value in Kolmogorov–Smirnov test
th.score 0.1 (optional) Numeric, filter by threshold value in MLST score
threads 1 (optional) Numeric, number of threads
normalize TRUE (optional) Boolean, if TRUE, normalize coverage
samfile NULL (optional) BamFile object in RSamtools package, input bam file. Excluive with filenames option.
method "default" (optional) Character, scoring methods. "default" and "sensitive" are available.

Other

MLST database used in the mlstverse is compatible with other MLST methodologies. We are currently preparing to be also available pubmlst database from mlstverse.

Citation

Not published yet.

Licence

Released under MIT + file LICENCE.

Contact

If you find some problem, please contact matsumoto@gen-info.osaka-u.ac.jp

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