Getting started with ssw-r: Sequence alignment examples

The R package ssw offers an R interface for SSW, a fast implementation of the Smith-Waterman algorithm for sequence alignment using SIMD, described in Zhao et al. (2013). The package is currently built on ssw-py.

library("ssw")

A short read sequence:

read <- "ACGT"

Exact alignment

Align the read against the reference sequence (TTTTACGTCCCCC) and print the results:

read |> 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

Get specific results, such as the alignment scores:

a <- read |> align("TTTTACGTCCCCC")

a$alignment$optimal_score

[1] 8

a$alignment$sub_optimal_score

[1] 0

Deletion

read |> align("TTTTACAGTCCCCC")

CIGAR start index 4: 2M1D2M
optimal_score: 5
sub-optimal_score: 0
target_begin: 4 target_end: 8
query_begin: 0
query_end: 3

Target:        4    ACAGT    8
                    ||*||
Query:         0    AC-GT    3

Insertion with gap open

read |> 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

Insertion with no gap open penalty

read |> align("TTTTACTCCCCC", gap_open = 0)

CIGAR start index 4: 2M1I1M
optimal_score: 6
sub-optimal_score: 0
target_begin: 4 target_end: 6
query_begin: 0
query_end: 3

Target:        4    AC-T    6
                    ||*|
Query:         0    ACGT    3

Specify start index

a <- align("ACTG", "ACTCACTG", start_idx = 4)
a

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

Target:        0    ACTC    3
                    |||*
Query:         0    ACTG    3

Print the results from position 4:

a |> print(start_idx = 4)

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

Target:        0    ACTG    3
                    ||||
Query:         0    ACTG    3

Forced alignment

Enforce no gaps by increasing the penalty:

a <- force_align("ACTG", "TTTTCTGCCCCCACG")
a

The results are truncated:

CIGAR start index 4: 3M
optimal_score: 6
sub-optimal_score: 0
target_begin: 4 target_end: 6
query_begin: 1
query_end: 3

Target:        4    CTG    6
                    |||
Query:         1    CTG    3

Use formatter() to avoid the truncation:

b <- a |> formatter()
b

[[1]]
[1] "TTTTCTGCCCCCACG"

[[2]]
[1] "   ACTG"

Or pretty-print the formatted results directly:

a |> formatter(print = TRUE)

TTTTCTGCCCCCACG
   ACTG

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.

References

Zhao, Mengyao, Wan-Ping Lee, Erik P Garrison, and Gabor T Marth. 2013. “SSW Library: An SIMD Smith-Waterman C/C++ Library for Use in Genomic Applications.” PloS ONE 8 (12): e82138. https://doi.org/10.1371/journal.pone.0082138.