SSW Library: An SIMD Smith-Waterman C/C++ Library for Use in Genomic Applications

License: MIT

Copyright (c) 2012-2015 Boston College

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Author: Mengyao Zhao & Wan-Ping Lee
Contact: Mengyao Zhao <[email protected]>
Last revision: 04/10/2013

1. Overview
SSW is a fast implementation of the Smith-Waterman algorithm, which uses the Single-Instruction Multiple-Data (SIMD) instructions 
to parallelize the algorithm at the instruction level. SSW library provides an API that can be flexibly used by programs written in 
C, C++ and other languages. We also provide a software that can do protein and genome alignment directly. Current version of our 
implementation is ~50 times faster than an ordinary Smith-Waterman. It can return the Smith-Waterman score, alignment location and 
traceback path (cigar) of the optimal alignment accurately; and return the sub-optimal alignment score and location heuristically.

2. How to use the API
The API files include ssw.h and ssw.c, which can be directly used by any C or C++ program. For the C++ users who are more comfortable to use a C++ style interface, an additional C++ wrapper is provided with the file ssw_cpp.cpp and ssw_cpp.h. 

To use the C style API, please: 
1) Download ssw.h and ssw.c, and put them in the same folder of your own program files.
2) Write #include "ssw.h" into your file that will call the API functions.
3) The API files are ready to be compiled together with your own C/C++ files.

The API function descriptions are in the file ssw.h. One simple example of the API usage is example.c. The Smith-Waterman penalties need to be integers. Small penalty numbers such as: match: 2, mismatch: -1, gap open: -3, gap extension: -1 are recommended, which will lead to shorter running time.  

To use the C++ style API, please: 
1) Download ssw.h, ssw.c, ssw_cpp.cpp and ssw_cpp.h and put them in the same folder of your own program files.
2) Write #include "ssw_cpp.h" into your file that will call the API functions.
3) The API files are ready to be compiled together with your own C/C++ files.

The API function descriptions are in the file ssw_cpp.h. A simple example of using the C++ API is example.cpp.

3. Speed and memory usage of the API
Test data set: 
Target sequence: reference genome of E. coli strain 536 (4,938,920 nucleotides) from NCBI
Query sequences: 1000 reads of Ion Torrent sequenced E. coli strain DH10B (C23-140, 318 PGM Run, 11/2011), read length: ~25-540 bp, most reads are ~200 bp

CPU time:
AMD CPU: default penalties: ~880 seconds; -m1 -x3 -o5 -e2: ~460 seconds
Intel CPU: default penalties: ~960 seconds; -m1 -x3 -o5 -e2: ~500 seconds 

Memory usage: ~40MB
 
4. Install the software
1) Download the software from https://github.com/mengyao/Complete-Striped-Smith-Waterman-Library.
2) cd src
3) make
4) The executable file will be ssw_test.

5. Run the software
Usage: ssw_test [options] ... <target.fasta> <query.fasta>(or <query.fastq>)
Options:
	-m N	N is a positive integer for weight match in genome sequence alignment. [default: 2]
	-x N	N is a positive integer. -N will be used as weight mismatch in genome sequence alignment. [default: 2]
	-o N	N is a positive integer. -N will be used as the weight for the gap opening. [default: 3]
	-e N	N is a positive integer. -N will be used as the weight for the gap extension. [default: 1]
	-p	Do protein sequence alignment. Without this option, the ssw_test will do genome sequence alignment.
	-a FILE	FILE is either the Blosum or Pam weight matrix. [default: Blosum50]
	-c	Return the alignment path.
	-f N	N is a positive integer. Only output the alignments with the Smith-Waterman score >= N.
	-r	The best alignment will be picked between the original read alignment and the reverse complement read alignment.
	-s	Output in SAM format. [default: no header]
	-h	If -s is used, include header in SAM output.

6. Software output
The software can output SAM format or BLAST like format results. 
1) SAM format output:
Example:

@HD VN:1.4  SO:queryname
@SQ SN:chr1 LN:1001
6:163296599:F:198;None;None/1   0   chr1    453 5   3M2D3M1D4M2D6M1D5M1D5M2I7M  *   0   0   CCAGCCCAAAATCTGTTTTAATGGTGGATTTGTGT *   AS:i:37 NM:i:11 ZS:i:28
3:153409880:F:224;None;3,153410143,G,A/1    0   chr1    523 4   2M1D32M1D3M1D6M1D8M *   0   0   GAAGAGTTAATTTAAGTCACTTCAAACAGATTACGTATCTTTTTTTTCCCT *   AS:i:42 NM:i:16 ZS:i:41
Y:26750420:R:-132;None;None/1   0   chr1    120 4   2M1I4M3D3M1I7M2I9M2D6M1I8M  *   0   0   AACAACAGAAGTTAATTAGCTTCAAAAATACTTTATATTTGCAA    *   AS:i:32 NM:i:16 ZS:i:29
13:91170622:R:-276;None;None/1  0   chr1    302 4   8M1D8M1D3M2D6M1D4M2I2M1D2M3D5M1I4M  *   0   0   CATTTATTGTTGTTTTTAAAGATTAAATGATTAAATGTTTCAAAA   *   AS:i:32 NM:i:18 ZS:i:30
15:37079528:R:-240;None;None/1  0   chr1    4   5   4M2D4M1D9M1I3M4I16M1I3M1D4M2D5M *   0   0   ACAGTGATGCCAAGCCAGTGGGTTTTAGCTTGTGGAGTTCCATAGGAGCGATGC  *   AS:i:30 NM:i:22 ZS:i:23
9:92308501:R:-176;None;None/1   0   chr1    142 4   4M3I5M4D10M2D4M1I2M2I6M5D1M1D6M2D3M *   0   0   AATAACCATAAAAATGGGCAAAGCAGCCTTCAGGGCTGCTGTTTCTA *   AS:i:26 NM:i:25 ZS:i:26
...

What is the output?
Please check the document "The SAM Format Specification" at: http://samtools.sourceforge.net/SAM1.pdf for the full description.
The additional optional field "ZS" indicates the suboptimal alignment score. For example, the 1st record in the upper example means the optimal alignment score of the given sequence is 37; the suboptimal alignment score is 28; the mismatch and INDEL base count within the aligned fragment of the read is 11.

2) An example of the BLAST like output:
target_name: chr1
query_name: 6:163296599:F:198;None;None/1
optimal_alignment_score: 37	sub-optimal_alignment_score: 28	strand: +	target_begin: 453	target_end: 492	query_begin: 17	query_end: 51

Target:      453    CCAATGCCACAAAACATCTGTCTCTAACTGGTG--TGTGTGT    492
                    |||**|||*||||**||||||*|*|||*|||||**|*|||||
Query:        17    CCA--GCC-CAAA--ATCTGT-TTTAA-TGGTGGATTTGTGT    51

target_name: chr1
query_name: 3:153409880:F:224;None;3,153410143,G,A/1
optimal_alignment_score: 42	sub-optimal_alignment_score: 41	strand: +	target_begin: 523	target_end: 577	query_begin: 3	query_end: 53

Target:      523    GAGAGAGAAAATTTCACTCCCTCCATAAATCTCACAGTATTCTTTTCTTTTTCCT    577
                    ||*||||**|||||*|*||*||*||*|*|**|*||*|||*||||||*||||*|||
Query:         3    GA-AGAGTTAATTTAAGTCACTTCAAACAGATTAC-GTA-TCTTTT-TTTTCCCT    53
...

7. Please cite this paper, if you need:
http://dx.plos.org/10.1371/journal.pone.0082138