Striped Smith-Waterman Algorithm for Sequence Alignment using SIMD.

ssw-r

ssw-r offers an R interface for SSW, a fast implementation of the Smith-Waterman algorithm for sequence alignment using SIMD. ssw-r is currently built on the Python package ssw-py.

Installation

You can install ssw-r from CRAN once available:

install.packages("ssw")

Or try the development version on GitHub:

remotes::install_github("nanxstats/ssw-r")

Install ssw-py

A simple way to install the Python package ssw-py that ssw-r can discover easily, is to run the helper function ssw::install_ssw_py(). By default, it installs ssw-py into an virtual environment named r-ssw-py.

ssw::install_ssw_py()

This follows the best practices suggested by the reticulate vignette Managing an R Package's Python Dependencies. There are also recommendations in the vignette on how to manage multiple R packages with different Python dependencies.

Usage

library("ssw")

"ACGT" |> align("TTTTACGTCCCCC")

CIGAR start index 4: 4M
optimal_score: 8
sub-optimal_score: 0
target_begin: 4	target_end: 7
query_begin: 0
query_end: 3

Target:        4    ACGT    7
                    ||||
Query:         0    ACGT    3

"ACGT" |> align("TTTTACTCCCCC", gap_open = 3)

CIGAR start index 4: 2M
optimal_score: 4
sub-optimal_score: 0
target_begin: 4	target_end: 5
query_begin: 0
query_end: 1

Target:        4    AC    5
                    ||
Query:         0    AC    1

"ACTG" |> force_align("TTTTCTGCCCCCACG") |> formatter(print = TRUE)

TTTTCTGCCCCCACG
   ACTG

For detailed usage, see the vignette.

Acknowledgements

ssw-r is built upon the work of two outstanding projects:

1. SSW - Original C implementation. Author: Mengyao Zhao
2. ssw-py - Python binding for SSW. Author: Nick Conway

We extend our sincere gratitude to Mengyao Zhao for developing the original SSW library and to Nick Conway for maintaining the ssw-py package. Their work forms the foundation of ssw-r. While ssw-r does not directly incorporate code from these projects, it serves as an R interface to their functionality. We encourage users to visit the original repositories for more information about the underlying implementation and to consider citing these works in publications that use ssw-r.

Code of Conduct

Please note that the ssw-r project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.