nvBowtie align function — nvBowtie • RbowtieCuda
Description: nvBowtie is a GPU-accelerated re-engineering of Bowtie2, a very widely used short-read aligner.

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# nvBowtie align function

Source: `R/bowtieCuda.R`
`nvBowtie.Rd`

nvBowtie is a GPU-accelerated re-engineering of Bowtie2, a very widely used short-read aligner.

## Usage

    nvBowtie(index, output_file, options, seq1, seq2 = NULL)

## Arguments

index

  `Character` vector. Index file created by nvBWT.

output_file

  `Character` vector. The alignment output file (.sam o .bam)

options

  `Character` vector. Specify additional options here to customize the processing. For a complete list of available options, type `nvBowtie_usage()`.

seq1

  `Character` vector. For single-end sequencing, it contains sequence file paths. For paired-end sequencing, it can be file path with #1 mates paired with file paths in seq2.

seq2

  `Character` vector. It contains file paths with #2 mates paired with file path in seq1. For single-end sequencoing files, it must be `NULL`.

## Value

An invisible `Integer` of call status. The value is 0 when there is not any mistakes Otherwise the value is non-zero.

## Details

We’ve introduced several new features to nvBowtie. You can now perform alignments using the WFA method by including the `--wfa (or --scoring wfa)` parameter. The WFA method requires a large amount of RAM on the graphics card. We therefore recommend using an Nvidia card with 8GB or more. Please note that this feature is still experimental; it currently supports only end-to-end alignments and does not yet allow customization of scoring parameters. By default, it uses the following scoring: `match:0, mismatch:1, gap_open:1 and gap_ext:1`. Additionally, the `--cache-writes` parameter optimizes disk write operations, resulting in faster alignments. This functionality requires 4GB of RAM and is limited to paired-end alignments.

## References

Langmead, B., & Salzberg, S. L. (2012). Fast gapped-read alignment with Bowtie 2. Nature methods, 9(4), 357-359.

## Examples

    td <- tempdir()

    ## Building index
    fa_file <- system.file(package='RbowtieCuda', 'extdata', 'bt2', 'refs', 'lambda_virus.fa')
    nvBWT(myinput=fa_file, output=file.path(td, 'index'), options='')
    #> [1] 0

    ## Alignments
    read_1 <- system.file(package='RbowtieCuda', 'extdata', 'bt2', 'reads', 'reads_1.fastq')
    read_2 <- system.file(package='RbowtieCuda', 'extdata', 'bt2', 'reads', 'reads_2.fastq')

    ## Sam file created with paired-end files (paired mates are here reverse-forward)
    nvBowtie(file.path(td, 'index'), file.path(td, 'my_result.sam'), options='--rf', seq1=read_1, seq2=read_2)
    #> [1] 0

    ## Bam file created with single-end file
    nvBowtie(file.path(td, 'index'), file.path(td, 'my_result.bam'), options='', seq1=read_1)
    #> [1] 0