The Rbwa package provides an R wrapper around the two popular
BWA aligners BWA-backtrack
(Li and Durbin 2009) and BWA-MEM
(Li 2013).
As mentioned in the BWA manual (see http://bio-bwa.sourceforge.net/bwa.shtml), BWA-backtrack is designed for short Illumina reads (up to 100bp), while BWA-MEM is more suitable for longer sequences (70bp to 1Mbp) and supports split alignment.
Rbwa
can be installed from Bioconductor using the following
commands in a fresh R session:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("Rbwa")
The two main alignment functions are:
bwa_aln
bwa_mem
The package also includes the following convenience functions:
bwa_build_index
bwa_aln
output into SAM output: bwa_sam
xa2multi
bwa_build_index
Both bwa_aln
and bwa_mem
require first to create a genome index from a
FASTA file. This is done only once for a given genome.
This can be done using the function
bwa_build_index
.
First, we load Rbwa
:
library(Rbwa)
In the following example code, we build a BWA index for a small portion
of human chr12 that we stored in a FASTA file located within the
Rbwa
package. We store the index files in a temporary directory.
dir <- tempdir()
fasta <- system.file(package="Rbwa",
"fasta/chr12.fa")
index_prefix <- file.path(dir, "chr12")
bwa_build_index(fasta,
index_prefix=index_prefix)
list.files(dir)
## [1] "BiocStyle" "chr12.amb" "chr12.ann" "chr12.bwt" "chr12.pac" "chr12.sa"
bwa_aln
We now align read sequences stored in the toy example FASTQ file
fastq/sequences.fastq
, provided in the Rbwa
package,
to our indexed genome:
fastq <- system.file(package="Rbwa",
"fastq/sequences.fastq")
bwa_aln(index_prefix=index_prefix,
fastq_files=fastq,
sai_files=file.path(dir, "output.sai"))
Any valid BWA arguments can be passed to the bwa_aln
function.
To see the complete list of valid arguments, please visit the BWA reference
manual: http://bio-bwa.sourceforge.net/bwa.shtml.
For instance, we can specify the maximal edit distance between the query
sequence and the reference genome to be 3 using n
, as well as the maximal edit
distance in the seed sequence k
to be 3,
where we specify that the length of the seed sequence is 13 using
the argument l
:
bwa_aln(index_prefix=index_prefix,
fastq_files=fastq,
sai_files=file.path(dir, "output.sai"),
n=3, k=3, l=13)
The output of bwa_aln
is an intermediate sai
file that should be
converted into a sam
file using the bwa_sam
function as follows:
bwa_sam(index_prefix=index_prefix,
fastq_files=fastq,
sai_files=file.path(dir, "output.sai"),
sam_file=file.path(dir, "output.sam"))
Let’s read the first few lines of the SAM file:
strtrim(readLines(file.path(dir, "output.sam")), 65)
## [1] "@SQ\tSN:chr12\tLN:171330"
## [2] "@PG\tID:bwa\tPN:bwa\tVN:0.7.17-r1198-dirty\tCL:/tmp/RtmphG3gR9/Rinst244be"
## [3] "ACATCAGAAAGAGCGGCAG\t0\tchr12\t170881\t37\t19M\t*\t0\t0\tACATCAGAAAGAGCGGCAG\t~~~~~~~"
## [4] "CAACCCAGCCCCCCTCCAA\t0\tchr12\t170801\t37\t19M\t*\t0\t0\tCAACCCAGCCCCCCTCCAA\t~~~~~~~"
## [5] "CCTGTGATCCACGGAGGCT\t0\tchr12\t170765\t37\t19M\t*\t0\t0\tCCTGTGATCCACGGAGGCT\t~~~~~~~"
## [6] "GCACTGCGGTGAGTGCTGT\t0\tchr12\t170665\t37\t19M\t*\t0\t0\tGCACTGCGGTGAGTGCTGT\t~~~~~~~"
## [7] "GCCTTTTACAGTTCGTACT\t0\tchr12\t170820\t37\t19M\t*\t0\t0\tGCCTTTTACAGTTCGTACT\t~~~~~~~"
## [8] "GTCATGCCCCCTCAGCCAG\t0\tchr12\t170703\t37\t19M\t*\t0\t0\tGTCATGCCCCCTCAGCCAG\t~~~~~~~"
## [9] "TCGGCTCTCACCGTGTCCG\t0\tchr12\t170646\t37\t19M\t*\t0\t0\tTCGGCTCTCACCGTGTCCG\t~~~~~~~"
By default, each row of the SAM output corresponds to the best alignment hit for a given input query sequence. Other alignments (secondary alignments, or other loci in case of multiple alignments) are stored in the XA tag.
The function xa2multi
conveniently extracts the alignments from the XA
tags and represent them as additional rows in the SAM format.
This can be executed as follows:
xa2multi(file.path(dir, "output.sam"),
file.path(dir, "output.multi.sam"))
strtrim(readLines(file.path(dir, "output.multi.sam")), 65)
## [1] "@SQ\tSN:chr12\tLN:171330"
## [2] "@PG\tID:bwa\tPN:bwa\tVN:0.7.17-r1198-dirty\tCL:/tmp/RtmphG3gR9/Rinst244be"
## [3] "ACATCAGAAAGAGCGGCAG\t0\tchr12\t170881\t37\t19M\t*\t0\t0\tACATCAGAAAGAGCGGCAG\t~~~~~~~"
## [4] "CAACCCAGCCCCCCTCCAA\t0\tchr12\t170801\t37\t19M\t*\t0\t0\tCAACCCAGCCCCCCTCCAA\t~~~~~~~"
## [5] "CCTGTGATCCACGGAGGCT\t0\tchr12\t170765\t37\t19M\t*\t0\t0\tCCTGTGATCCACGGAGGCT\t~~~~~~~"
## [6] "GCACTGCGGTGAGTGCTGT\t0\tchr12\t170665\t37\t19M\t*\t0\t0\tGCACTGCGGTGAGTGCTGT\t~~~~~~~"
## [7] "GCCTTTTACAGTTCGTACT\t0\tchr12\t170820\t37\t19M\t*\t0\t0\tGCCTTTTACAGTTCGTACT\t~~~~~~~"
## [8] "GTCATGCCCCCTCAGCCAG\t0\tchr12\t170703\t37\t19M\t*\t0\t0\tGTCATGCCCCCTCAGCCAG\t~~~~~~~"
## [9] "TCGGCTCTCACCGTGTCCG\t0\tchr12\t170646\t37\t19M\t*\t0\t0\tTCGGCTCTCACCGTGTCCG\t~~~~~~~"
bwa_mem
The bwa_mem
function works similar to the bwa_aln
function, except
that it does not produce intermediate .sai
files; it outputs a SAM file
directly:
fastq <- system.file(package="Rbwa",
"fastq/sequences.fastq")
bwa_mem(index_prefix=index_prefix,
fastq_files=fastq,
sam_file=file.path(dir, "output.sam"))
strtrim(readLines(file.path(dir, "output.sam")), 65)
## [1] "@SQ\tSN:chr12\tLN:171330"
## [2] "@PG\tID:bwa\tPN:bwa\tVN:0.7.17-r1198-dirty\tCL:/tmp/RtmphG3gR9/Rinst244be"
## [3] "ACATCAGAAAGAGCGGCAG\t4\t*\t0\t0\t*\t*\t0\t0\tACATCAGAAAGAGCGGCAG\t~~~~~~~~~~~~~~~~~~~\t"
## [4] "CAACCCAGCCCCCCTCCAA\t4\t*\t0\t0\t*\t*\t0\t0\tCAACCCAGCCCCCCTCCAA\t~~~~~~~~~~~~~~~~~~~\t"
## [5] "CCTGTGATCCACGGAGGCT\t4\t*\t0\t0\t*\t*\t0\t0\tCCTGTGATCCACGGAGGCT\t~~~~~~~~~~~~~~~~~~~\t"
## [6] "GCACTGCGGTGAGTGCTGT\t4\t*\t0\t0\t*\t*\t0\t0\tGCACTGCGGTGAGTGCTGT\t~~~~~~~~~~~~~~~~~~~\t"
## [7] "GCCTTTTACAGTTCGTACT\t4\t*\t0\t0\t*\t*\t0\t0\tGCCTTTTACAGTTCGTACT\t~~~~~~~~~~~~~~~~~~~\t"
## [8] "GTCATGCCCCCTCAGCCAG\t4\t*\t0\t0\t*\t*\t0\t0\tGTCATGCCCCCTCAGCCAG\t~~~~~~~~~~~~~~~~~~~\t"
## [9] "TCGGCTCTCACCGTGTCCG\t4\t*\t0\t0\t*\t*\t0\t0\tTCGGCTCTCACCGTGTCCG\t~~~~~~~~~~~~~~~~~~~\t"
sessionInfo()
## R version 4.2.1 (2022-06-23)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.5 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.16-bioc/R/lib/libRblas.so
## LAPACK: /home/biocbuild/bbs-3.16-bioc/R/lib/libRlapack.so
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB LC_COLLATE=C
## [5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
## [7] LC_PAPER=en_US.UTF-8 LC_NAME=C
## [9] LC_ADDRESS=C LC_TELEPHONE=C
## [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] Rbwa_1.2.0 BiocStyle_2.26.0
##
## loaded via a namespace (and not attached):
## [1] bookdown_0.29 digest_0.6.30 R6_2.5.1
## [4] jsonlite_1.8.3 magrittr_2.0.3 evaluate_0.17
## [7] stringi_1.7.8 cachem_1.0.6 rlang_1.0.6
## [10] cli_3.4.1 jquerylib_0.1.4 bslib_0.4.0
## [13] rmarkdown_2.17 tools_4.2.1 stringr_1.4.1
## [16] xfun_0.34 yaml_2.3.6 fastmap_1.1.0
## [19] compiler_4.2.1 BiocManager_1.30.19 htmltools_0.5.3
## [22] knitr_1.40 sass_0.4.2
Li, Heng. 2013. “Aligning Sequence Reads, Clone Sequences and Assembly Contigs with Bwa-Mem.” arXiv Preprint arXiv:1303.3997.
Li, Heng, and Richard Durbin. 2009. “Fast and Accurate Short Read Alignment with Burrows–Wheeler Transform.” Bioinformatics 25 (14): 1754–60.