list of sequence alignment software

| Local search with fast k-tuple heuristic (Basic Local Alignment Search Tool)

| NCBI compliant multinode and multicore BLAST wrapper. Distributed with the latest version of BLAST, this wrapper facilitates parallelization of the algorithm on modern hybrid architectures with many nodes and many cores within each node.HPC-BLAST code repository https://github.com/UTennessee-JICS/HPC-BLAST

| Sequence-context specific BLAST, more sensitive than BLAST, FASTA, and SSEARCH. Position-specific iterative version CSI-BLAST more sensitive than PSI-BLAST

| GPU accelerated Smith Waterman algorithm for multiple shared-host GPUs

| BLASTX and BLASTP aligner based on double indexing

| Local search with fast k-tuple heuristic, slower but more sensitive than BLAST

| Global:Global (GG), Global:Local (GL) alignment with statistics

| Software for ultra fast local DNA sequence motif search and pairwise alignment for NGS data (FASTA, FASTQ).

| Genoogle uses indexing and parallel processing techniques for searching DNA and Proteins sequences. It is developed in Java and open source.

| Local and global search with profile Hidden Markov models, more sensitive than PSI-BLAST

| Pairwise comparison of profile Hidden Markov models; very sensitive

| Inverse Document Frequency

| Profile SCFG search

| High-performance general purpose sequence similarity search tool

| High performance local aligner compatible to BLAST, but much faster; supports SAM/BAM

| Software suite to search and cluster huge sequence sets. Similar sensitivity to BLAST and PSI-BLAST but orders of magnitude faster

| Ultra-fast sequence analysis tool

|OpenCL Smith-Waterman on Altera's FPGA for Large Protein Databases

|Protein

|Rucci E, García C, Botella G, De Giusti A, Naiouf M, Prieto-Matías M{{Cite journal|last1=Rucci|first1=Enzo|last2=Garcia|first2=Carlos|last3=Botella|first3=Guillermo|last4=Giusti|first4=Armando E. De|last5=Naiouf|first5=Marcelo|last6=Prieto-Matias|first6=Manuel|date=2016-06-30|title=OSWALD: OpenCL Smith–Waterman on Altera's FPGA for Large Protein Databases|url=http://hpc.sagepub.com/content/early/2016/06/30/1094342016654215|journal=International Journal of High Performance Computing Applications|volume=32|issue=3|pages=337–350|doi=10.1177/1094342016654215|s2cid=212680914|issn=1094-3420|hdl=11336/48798|hdl-access=free}}

|2016

| Fast Smith-Waterman search using SIMD parallelization

| Position-specific iterative BLAST, local search with position-specific scoring matrices, much more sensitive than BLAST

| Combining the Smith-Waterman search algorithm with the PSI-BLAST profile construction strategy to find distantly related protein sequences, and preventing homologous over-extension errors.

|Retrieve and Relate (R&R) is a high performance yet sensitive multi-database search engine, capable of searching in parallel through DNA,RNA and Protein sequences.

|Both

|

|2019

| Highly parallel Scalable BLAST

| Linking and profiling sequence alignment data from NCBI-BLAST results with major sequence analysis servers/services

| Local and global search with profile Hidden Markov models, more sensitive than PSI-BLAST

| Smith-Waterman search, slower but more sensitive than FASTA

| First parallelized algorithm employing the emerging Intel Xeon Phis to accelerate Smith-Waterman protein database search

| First parallel Smith-Waterman algorithm exploiting Intel Xeon Phi clusters to accelerate the alignment of long DNA sequences

| Smith-Waterman implementation for Intel Multicore and Manycore architectures

| Enhanced Smith-Waterman on Intel's Multicore and Manycore architectures based on AVX-512 vector extensions

| Fast Smith-Waterman search using SIMD parallelization

| Fast heuristic anchor based pairwise alignment

| Alignments for membrane protein sequences

|For DNA, RNA and protein molecules up to 32MB, aligns all sequences of size K or greater. Similar alignments are grouped together for analysis. Automatic repetitive sequence filter.

|Both

|Local

|E. Wachtel

|2017

| Dynamic programming

| Dynamic programming

| Seeded pattern-matching

| DNA sequence alignment of unrestricted size in single or multiple GPUs

| Web-based dot-plot tool

| Java-based dot-plot tool

| Posterior based local extension with descriptive evolution model

|Align chromatogram files (.ab1, .scf) against a template sequence, locate errors, and correct them instantly.

|Nucleotide

|Local

|Genome Compiler Corporation

|2014

| GPU-based dynamic programming with backtracking

| Does pairwise sequence alignment with one gap

| Software for ultra fast local DNA sequence motif search and pairwise alignment for NGS data (FASTA, FASTQ).

| Global:Global (GG), Global:Local (GL) alignment with statistics

| Java open-source implementation of Smith-Waterman

| Protein sequence to structure alignment that includes secondary structure, structural conservation, structure-derived sequence profiles, and consensus alignment scores

| Multiple, non-overlapping, local similarity (same algorithm as SIM)

| Standard Needleman-Wunsch dynamic programming algorithm

| Waterman-Eggert local alignment (based on LALIGN)

| explicit models of indel evolution

| Software to align DNA, RNA, protein, or DNA + protein sequences via pairwise and multiple sequence alignment algorithms including MUSCLE, Mauve, MAFFT, Clustal Omega, Jotun Hein, Wilbur-Lipman, Martinez Needleman-Wunsch, Lipman-Pearson and Dotplot analysis.

| suffix tree based

| Needleman-Wunsch dynamic programming

| logarithmic and affine gap costs and explicit models of indel evolution

| Needleman-Wunsch dynamic programming

| C/C++/Python/Java SIMD dynamic programming library for SSE, AVX2

| Smith-Waterman on protein back-translation graph (detects frameshifts at protein level)

| Seeded pattern-matching

| Stochastic partition function sampling via dynamic programming

| "align" command aligns sequence & applies it to structure

| suffix tree based

| Alignment using predicted Connectivity Profiles

| Parallel whole-genome synteny alignments

| Various dynamic programming

| Local similarity with varying gap treatments

| Local similarity

| Fast pairwise global alignment

| Local (Smith-Waterman) alignment with statistics

| |Java applet demonstrating various algorithms from{{Cite book|first=Dan |last=Gusfield |year=1997|title= Algorithms on strings, trees and sequences|publisher= Cambridge university press| isbn= 978-0-521-58519-4}}

| Smith-Waterman Acceleration on Intel's FPGA with OpenCL for Long DNA Sequences

| Fast Local Alignment Searching

| Memory-optimized Needleman-Wunsch dynamic programming

| Aligns nucleic acid sequences given a protein alignment

| Opensource Smith-Waterman for SSE/CUDA, Suffix array based repeats finder & dotplot

| Smith-Waterman dynamic programming

| k-tuple pairwise match

| Seeded pattern-matching

| A-Bruijn alignment

| manual alignment ; some software assistance

|For DNA, RNA and protein molecules up to 32MB, aligns all sequences of size K or greater, MSA or within a single molecule. Similar alignments are grouped together for analysis. Automatic repetitive sequence filter.

|Both

|Local

|E. Wachtel

|2017

|Free

| Sequence annealing

| Tree+multi-alignment; probabilistic-Bayesian; joint estimation

| Java-based multiple sequence alignment editor with integrated analysis tools

| Iterative alignment

| Progressive alignment

| Multi-alignment; ClustalW & Phrap support

| COmparison of Multiple Protein sequence Alignments with assessment of Statistical Significance

| Progressive-iterative alignment

| Segment-based method

| Segment-based method for intraspecific alignments

| Multi-alignment; Full automatic sequence alignment; Automatic ambiguity correction; Internal base caller; Command line seq alignment

| linked DNA to Protein multiple alignment with MUSCLE, Clustal and Smith-Waterman

| Energy Based Multiple Sequence Alignment for DNA Binding Sites

|Progressive alignment for extremely large protein families (hundreds of thousands of members)

|Protein

|Global

|Deorowicz et al.

|2016

|{{free}}, GPL 3

| Sequence annealing

| Progressive-Iterative alignment; ClustalW plugin

| Quality control and filtering of multiple sequence alignments

| Progressive alignment

|Progressive-iterative alignment. Multiple alignment of coding sequences accounting for frameshifts and stop codons.

|Nucleotides

|Global

|V. Ranwez et al.

|2011 (latest version, v2.07 2023)

|

| Progressive-iterative alignment

| Multi-alignment of RNAs

| Progressive alignment

| Software to align DNA, RNA, protein, or DNA + protein sequences via pairwise and multiple sequence alignment algorithms including MUSCLE, Mauve, MAFFT, Clustal Omega, Jotun Hein, Wilbur-Lipman, Martinez Needleman-Wunsch, Lipman-Pearson and Dotplot analysis.

| Dynamic programming

| Dynamic programming

| Dynamic programming-clustering

| Progressive dynamic programming alignment

| Progressive-iterative alignment

| Progressive-iterative alignment

| Probabilistic-consistency

| A human computing framework for comparative genomics to solve multiple alignment

| Progressive structure aware alignment

| RNA

| Global

| D. DeBlasio, J Braund, S Zhang

| 2009

|

| Progressive-iterative-consistency-homology-extended alignment with preprofiling and secondary structure prediction

| Nonprogressive, maximum expected accuracy alignment

| Partial order/hidden Markov model

| Probabilistic/consistency with partition function probabilities

| Probabilistic/consistency

| Progressive alignment/hidden Markov model/Secondary structure/3D structure

| Iterative alignment (especially refinement)

| Alignment preserving non-heuristic

| Combines DNA and Protein alignment, by back translating the protein alignment to DNA.

| Sequence alignment by genetic algorithm

| Hidden Markov model

| Manual alignment

| Bayesian co-estimation of alignment and phylogeny (MCMC)

| Multiple alignment and secondary structure prediction

| More sensitive progressive alignment

| Supports multiple alignment with MUSCLE, KAlign, Clustal and MAFFT plugins

| VectorFriends Aligner, MUSCLE plugin, and ClustalW plugin

| Adaptive pair-Hidden Markov Model based approach

| An ultra-fast tool to find relative absent words in genomic data

| Nucleotide

| Synteny and comparative genomics

| Nucleotide

| Pairwise global alignment with whole genomes

| Alignment of cDNA sequences to a genome.

| Alignment of rearranged genomes using 6 frame translation

| Fuzzy whole genome alignment and analysis

| Alignment of cDNA sequences to a genome. Identifies splice site junctions with high accuracy.

| Alignment of cDNA sequences to a genome. Identifies splice site junctions with high accuracy. Able to recognize and separate gene duplications.

| Multiple alignment of rearranged genomes

| Multiple Genome Aligner

| Local multiple alignments of genome-length sequences

| Multiple alignment of genomes

| Search for ncRNAs in genomes by partition function local alignment

| Profiling sequence alignment data with major servers/services

| Profiling sequence alignment data from NCBI-BLAST results with major servers-services

| Pairwise global alignment of completed genome regions

| A program designed to align an expressed DNA sequence with a genomic sequence, allowing for introns

| Gene finding, alignment, annotation (human-mouse homology identification)

|

| An efficient aligner for assemblies with explicit guarantees, aligning reads without splices

| Motif search and discovery

| Motif search and discovery (can get also positive & negative sequences as input for enriched motif search)

| Ungapped motif identification from BLOCKS database

| Extraction and identification of shorter motifs

| Stochastic motif extraction by statistical likelihood

| Prediction of transmembrane helices and topology of proteins

| Local structure motif library

| Prediction of Coiled coil and Leucine Zipper

| Motif discovery and search

| GPU accelerated MEME (v4.4.0) algorithm for GPU clusters

| Discriminative motif discovery and search

| Motif search and alignment tool

| Motif search tool

| Pattern generation for use with ScanProsite

| Motif database search tool

| Motif extraction and database search

| Multiple motif and regular expression search

|

| Letunic, Copley, Schmidt, Ciccarelli, Doerks, Schultz, Ponting, Bork

| Thompson, Plewniak, Poch

| Raghava, Searle, Audley, Barber, Barton

| Edgar

| Mizuguchi

| Edgar

| Van Walle, Lasters, Wyns

| Computes Smith-Waterman gapped alignments and mapping qualities on one or more GPUs. Supports BS-seq alignments. Processes 100,000 to 500,000 reads per second (varies with data, hardware, and configured sensitivity).

| {{yes}}

| {{no}}

| {{yes}}

| {{yes}}

| {{free}}, BSD

|{{cite journal|last1=Wilton|first1=Richard|last2=Budavari|first2=Tamas|last3=Langmead|first3=Ben|last4=Wheelan|first4=Sarah J.|last5=Salzberg|first5=Steven L.|last6=Szalay|first6=Alexander S.|title=Arioc: high-throughput read alignment with GPU-accelerated exploration of the seed-and-extend search space|journal=PeerJ|volume=3|pages=e808|year=2015|doi=10.7717/peerj.808|pmid=25780763|pmc=4358639 |doi-access=free }}

| 2015

| A GPGPU accelerated Burrows–Wheeler transform (FM-index) short read alignment program based on BWA, supports alignment of indels with gap openings and extensions.

| {{yes}}

| {{no}}

| {{yes}}

| {{yes}}, POSIX Threads and CUDA

| {{free}}, GPL

|

|

| Uses a short kmers to rapidly index genome; no size or scaffold count limit. Higher sensitivity and specificity than Burrows–Wheeler aligners, with similar or greater speed. Performs affine-transform-optimized global alignment, which is slower but more accurate than Smith-Waterman. Handles Illumina, 454, PacBio, Sanger, and Ion Torrent data. Splice-aware; capable of processing long indels and RNA-seq. Pure Java; runs on any platform. Used by the Joint Genome Institute.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{free}}, BSD

|

| 2010

| Explicit time and accuracy tradeoff with a prior accuracy estimation, supported by indexing the reference sequences. Optimally compresses indexes. Can handle billions of short reads. Can handle insertions, deletions, SNPs, and color errors (can map ABI SOLiD color space reads). Performs a full Smith Waterman alignment.

|

|

|

| {{yes}}, POSIX Threads

| {{free}}, GPL

|{{cite journal|last1=Homer|first1=Nils|last2=Merriman|first2=Barry|last3=Nelson|first3=Stanley F.|title=BFAST: An Alignment Tool for Large Scale Genome Resequencing|journal=PLOS ONE|volume=4|issue=11|year=2009|pages=e7767|pmid=19907642|pmc=2770639|doi=10.1371/journal.pone.0007767|bibcode=2009PLoSO...4.7767H|doi-access=free}}

| 2009

| Runs the Burrows–Wheeler Aligner-BWA on a Hadoop cluster. It supports the algorithms BWA-MEM, BWA-ALN, and BWA-SW, working with paired and single reads. It implies an important reduction in the computational time when running in a Hadoop cluster, adding scalability and fault-tolerance.

| {{yes}}

| {{partial|Low quality bases trimming}}

| {{yes}}

| {{yes}}

| {{free}}, GPL 3

|{{cite journal|last1=Abuín|first1=J.M.|last2=Pichel|first2=J.C.|last3=Pena|first3=T.F.|last4=Amigo|first4=J.|title=BigBWA: approaching the Burrows–Wheeler aligner to Big Data technologies|journal=Bioinformatics|year=2015|doi=10.1093/bioinformatics/btv506|pmid=26323715|volume=31|issue=24|pages=4003–5|doi-access=free}}

| 2015

| BLAST's nucleotide alignment program, slow and not accurate for short reads, and uses a sequence database (EST, Sanger sequence) rather than a reference genome.

|

|

|

|

|

|

|

| Made by Jim Kent. Can handle one mismatch in initial alignment step.

|

|

|

| {{yes}}, client-server

| {{proprietary}}, freeware for academic and noncommercial use

|{{cite journal|last1=Kent|first1=W. J.|title=BLAT---The BLAST-Like Alignment Tool|journal=Genome Research|volume=12|issue=4|year=2002|pages=656–664|issn=1088-9051|doi=10.1101/gr.229202|pmid=11932250|pmc=187518}}

|2002

| Uses a Burrows–Wheeler transform to create a permanent, reusable index of the genome; 1.3 GB memory footprint for human genome. Aligns more than 25 million Illumina reads in 1 CPU hour. Supports Maq-like and SOAP-like alignment policies

| {{yes}}

| {{yes}}

| {{no}}

| {{yes}}, POSIX Threads

| {{free}}, Artistic

|{{cite journal|last1=Langmead|first1=Ben|last2=Trapnell|first2=Cole|last3=Pop|first3=Mihai|last4=Salzberg|first4=Steven L|title=Ultrafast and memory-efficient alignment of short DNA sequences to the human genome|journal=Genome Biology|volume=10|issue=3|year=2009|pages=R25|issn=1465-6906|doi=10.1186/gb-2009-10-3-r25|pmid=19261174|pmc=2690996 |doi-access=free }}

|2009

| Uses a Burrows–Wheeler transform to create an index of the genome. It's a bit slower than Bowtie but allows indels in alignment.

| {{yes}}

| {{partial|Low quality bases trimming}}

| {{yes}}

| {{yes}}

| {{free}}, GPL

|{{cite journal|last1=Li|first1=H.|last2=Durbin|first2=R.|title=Fast and accurate short read alignment with Burrows–Wheeler transform|journal=Bioinformatics|volume=25|issue=14|year=2009|pages=1754–1760|issn=1367-4803|doi=10.1093/bioinformatics/btp324|pmid=19451168|pmc=2705234}}

| 2009

| A probabilistic short read aligner based on the use of position specific scoring matrices (PSSM). The aligner is adaptable in the sense that it can take into account the quality scores of the reads and models of data specific biases, such as those observed in Ancient DNA, PAR-CLIP data or genomes with biased nucleotide compositions.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{free}}, GPL

|{{cite journal|last1=Kerpedjiev|first1=Peter|last2=Frellsen|first2=Jes|last3=Lindgreen|first3=Stinus|last4=Krogh|first4=Anders|title=Adaptable probabilistic mapping of short reads using position specific scoring matrices|journal=BMC Bioinformatics|volume=15|issue=1|year=2014|page=100|issn=1471-2105|doi=10.1186/1471-2105-15-100|pmid=24717095|pmc=4021105 |doi-access=free }}

| 2014

| Quantify and manage large quantities of short-read sequence data. CASHX pipeline contains a set of tools that can be used together, or separately as modules. This algorithm is very accurate for perfect hits to a reference genome.

|

|

|

| {{no}}

| {{proprietary}}, freeware for academic and noncommercial use

|

|

| Short-read mapping using Hadoop MapReduce

|

|

|

| {{yes}}, Hadoop MapReduce

| {{free}}, Artistic

|

|

| Short-read alignment error correction using GPUs.

|

|

|

| {{yes}}, GPU enabled

|

|

|

| A CUDA compatible short read aligner to large genomes based on Burrows–Wheeler transform

| {{yes}}

| {{yes}}

| {{no}}

| {{yes}} (GPU enabled)

| {{free}}, GPL

|{{cite journal|last1=Liu|first1=Y.|last2=Schmidt|first2=B.|last3=Maskell|first3=D. L.|title=CUSHAW: a CUDA compatible short read aligner to large genomes based on the Burrows–Wheeler transform|journal=Bioinformatics|volume=28|issue=14|year=2012|pages=1830–1837|issn=1367-4803|doi=10.1093/bioinformatics/bts276|pmid=22576173|doi-access=free}}

|2012

| Gapped short-read and long-read alignment based on maximal exact match seeds. This aligner supports both base-space (e.g. from Illumina, 454, Ion Torrent and PacBio sequencers) and ABI SOLiD color-space read alignments.

| {{yes}}

| {{no}}

| {{yes}}

| {{yes}}

| {{free}}, GPL

|

| 2014

| GPU-accelerated CUSHAW2 short-read aligner.

| {{yes}}

| {{no}}

| {{yes}}

| {{yes}}

| {{free}}, GPL

|

|

| Sensitive and accurate base-space and color-space short-read alignment with hybrid seeding

| {{yes}}

| {{no}}

| {{yes}}

| {{yes}}

| {{free}}, GPL

|{{cite journal|last1=Liu|first1=Y.|last2=Schmidt|first2=B.|title=Long read alignment based on maximal exact match seeds|journal=Bioinformatics|volume=28|issue=18|year=2012|pages=i318–i324|issn=1367-4803|doi=10.1093/bioinformatics/bts414|pmid=22962447|pmc=3436841}}

| 2012

| Read mapping alignment software that implements cache obliviousness to minimize main/cache memory transfers like mrFAST and mrsFAST, however designed for the SOLiD sequencing platform (color space reads). It also returns all possible map locations for improved structural variation discovery.

| {{yes}}

| {{yes}}, for structural variation

| {{yes}}

| {{no}}

| {{free}}, BSD

|

|

| Implemented by Illumina. Includes ungapped alignment with a finite read length.

|

|

|

|

|

|

|

| Extended Randomized Numerical alignEr for accurate alignment of NGS reads. It can map bisulfite-treated reads.

| {{yes}}

| {{partial|Low quality bases trimming}}

| {{yes}}

| Multithreading and MPI-enabled

| {{free}}, GPL 3

|

|

| Finds global alignments of short DNA sequences against large DNA banks

|

|

|

| Multithreading

| CeCILL version 2 License.

|{{cite journal|last1=Rizk|first1=Guillaume|last2=Lavenier|first2=Dominique|title=GASSST: global alignment short sequence search tool|journal=Bioinformatics|volume=26|issue=20|year=2010|pages=2534–2540|pmid=20739310|pmc=2951093|doi=10.1093/bioinformatics/btq485}}

| 2011

| High-quality alignment engine (exhaustive mapping with substitutions and indels). More accurate and several times faster than BWA or Bowtie 1/2. Many standalone biological applications (mapper, split mapper, mappability, and other) provided.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{free}}, GPL3

|{{cite journal|last1=Marco-Sola|first1=Santiago|last2=Sammeth|first2=Michael|last3=Guigó|first3=Roderic|last4=Ribeca|first4=Paolo|title=The GEM mapper: fast, accurate and versatile alignment by filtration|journal=Nature Methods|volume=9|issue=12|year=2012|pages=1185–1188|issn=1548-7091|doi=10.1038/nmeth.2221|pmid=23103880|s2cid=2004416}}

|2012

| Ultra fast and comprehensive NGS read aligner with high precision and small storage footprint.

| {{yes}}

| {{partial|Low quality bases trimming}}

| {{yes}}

| {{yes}}

| {{proprietary}}, commercial

|

|

| Fast, accurate overlap assembler with the ability to handle any combination of sequencing technology, read length, any pairing orientations, with any spacer size for the pairing, with or without a reference genome.

|

|

|

| {{yes}}

| {{proprietary}}, commercial

|

|

| Complete framework with user-friendly GUI to analyse NGS data. It integrates a proprietary high quality alignment algorithm and plug-in ability to integrate various public aligner into a framework allowing to import short reads, align them, detect variants, and generate reports. It is made for resequencing projects, namely in a diagnostic setting.

| {{yes}}

| {{no}}

| {{yes}}

| {{yes}}

| {{proprietary}}, commercial

|

|

| Robust, fast short-read alignment. GMAP: longer reads, with multiple indels and splices (see entry above under Genomics analysis); GSNAP: shorter reads, with one indel or up to two splices per read. Useful for digital gene expression, SNP and indel genotyping. Developed by Thomas Wu at Genentech. Used by the National Center for Genome Resources (NCGR) in Alpheus.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{proprietary}}, freeware for academic and noncommercial use

|

|

| Accurately performs gapped alignment of sequence data obtained from next-generation sequencing machines (specifically of Solexa-Illumina) back to a genome of any size. Includes adaptor trimming, SNP calling and Bisulfite sequence analysis.

|

| {{yes}}, also supports Illumina *_int.txt and *_prb.txt files with all 4 quality scores for each base

|

| Multithreading and MPI-enabled

|

|{{cite journal|last1=Clement|first1=N. L.|last2=Snell|first2=Q.|last3=Clement|first3=M. J.|last4=Hollenhorst|first4=P. C.|last5=Purwar|first5=J.|last6=Graves|first6=B. J.|last7=Cairns|first7=B. R.|last8=Johnson|first8=W. E.|title=The GNUMAP algorithm: unbiased probabilistic mapping of oligonucleotides from next-generation sequencing|journal=Bioinformatics|volume=26|issue=1|year=2009|pages=38–45|issn=1367-4803|doi=10.1093/bioinformatics/btp614|pmid=19861355|pmc=6276904}}

|2009

| Uses a hash table and bloom matrix to create and filter potential positions on the genome. For higher efficiency uses cross-similarity between short reads and avoids realigning non unique redundant sequences. It is faster than Bowtie and BWA and allows indels and divergent sensitive alignments on viruses, bacteria, and more conservative eukaryotic alignments.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{proprietary}}, freeware for academic and noncommercial users registered to HIVE deployment instance

|{{cite journal|last1=Santana-Quintero|first1=Luis|last2=Dingerdissen|first2=Hayley|last3=Thierry-Mieg|first3=Jean|last4=Mazumder|first4=Raja|last5=Simonyan|first5=Vahan|title=HIVE-Hexagon: High-Performance, Parallelized Sequence Alignment for Next-Generation Sequencing Data Analysis|journal=PLOS ONE|year=2014|pages=1754–1760|doi=10.1371/journal.pone.0099033|pmid=24918764|volume=9|issue=6|pmc=4053384|bibcode=2014PLoSO...999033S|doi-access=free}}

| 2014

| Improved Meta-aligner and Minimap2 On Spark. A long read distributed aligner on Apache Spark platform with linear scalability w.r.t. single node execution.

|

| {{yes}}

| {{yes}}

| {{yes}}

| {{free}}

|

|

| Fully uses all the computing power available on one server node; thus, it scales well over a broad range of hardware architectures, and alignment performance improves with hardware abilities

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{free}}, GPL

|

|

| Uses adaptative seeds and copes more efficiently with repeat-rich sequences (e.g. genomes). For example: it can align reads to genomes without repeat-masking, without becoming overwhelmed by repetitive hits.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{free}}, GPL

|{{cite journal|last1=Kielbasa|first1=S.M.|last2=Wan|first2=R.|last3=Sato|first3=K. |last4=Horton|first4=P.|last5=Frith|first5=M.C.|title=Adaptive seeds tame genomic sequence comparison|journal=Genome Research|volume=21|issue=3|year=2011|pages=487–493|pmid=21209072|pmc=3044862|doi=10.1101/gr.113985.110}}

| 2011

| Ungapped alignment that takes into account quality scores for each base.

|

|

|

|

| {{free}}, GPL

|

|

| Gapped (mrFAST) and ungapped (mrsFAST) alignment software that implements cache obliviousness to minimize main/cache memory transfers. They are designed for the Illumina sequencing platform and they can return all possible map locations for improved structural variation discovery.

| {{yes}}

| {{yes}}, for structural variation

| {{yes}}

| {{no}}

| {{free}}, BSD

|

|

| MOM or maximum oligonucleotide mapping is a query matching tool that captures a maximal length match within the short read.

|

|

|

| {{yes}}

|

|

|

| Fast gapped aligner and reference-guided assembler. Aligns reads using a banded Smith-Waterman algorithm seeded by results from a k-mer hashing scheme. Supports reads ranging in size from very short to very long.

|

|

|

| {{yes}}

|

|

|

| Fast aligner based on a filtration strategy (no indexing, use q-grams and Backward Nondeterministic DAWG Matching)

|

|

|

|

|

| {{cite book|last1=Rivals|first1=Eric|last2=Salmela|first2=Leena|last3=Kiiskinen|first3=Petteri|last4=Kalsi|first4=Petri|last5=Tarhio|first5=Jorma|title=Algorithms in Bioinformatics |chapter=Mpscan: Fast Localisation of Multiple Reads in Genomes |volume=5724|year=2009|pages= 246–260|doi=10.1007/978-3-642-04241-6_21|series=Lecture Notes in Computer Science|bibcode=2009LNCS.5724..246R|isbn=978-3-642-04240-9|citeseerx=10.1.1.156.928|s2cid=17187140 }}

| 2009

| Gapped alignment of single end and paired end Illumina GA I & II, ABI Colour space & ION Torrent reads. High sensitivity and specificity, using base qualities at all steps in the alignment. Includes adapter trimming, base quality calibration, Bi-Seq alignment, and options for reporting multiple alignments per read. Use of ambiguous IUPAC codes in reference for common SNPs can improve SNP recall and remove allelic bias.

| {{yes}}

| {{yes}}

| {{yes}}

| Multi-threading and MPI versions available with paid license

| {{proprietary}}, freeware single threaded version for academic and noncommercial use

|

|

| Developed for use by biologists performing analysis of next generation sequencing data from Roche Genome Sequencer FLX, Illumina GA/HiSeq, Life Technologies Applied BioSystems’ SOLiD System, PacBio and Ion Torrent platforms.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{proprietary}}, commercial

|

|

| Flexible and fast read mapping program (twice as fast as BWA), achieves a mapping sensitivity comparable to Stampy. Internally uses a memory efficient index structure (hash table) to store positions of all 13-mers present in the reference genome. Mapping regions where pairwise alignments are required are dynamically determined for each read. Uses fast SIMD instructions (SSE) to accelerate alignment calculations on CPU. If available, alignments are computed on GPU (using OpenCL/CUDA) further reducing runtime 20-50%.

| {{yes}}

| {{no}}

| {{yes}}

| {{yes}}, POSIX Threads, OpenCL/CUDA, SSE

| {{free}}

|{{cite journal|last1=Sedlazeck|first1=Fritz J.|last2=Rescheneder|first2=Philipp|last3=von Haeseler|first3=Arndt|title=NextGenMap: fast and accurate read mapping in highly polymorphic genomes|journal=Bioinformatics|volume=29|issue=21|year=2013|pages=2790–2791|pmid=23975764|doi=10.1093/bioinformatics/btt468|doi-access=free}}

| 2013

| Includes highly sensitive and highly accurate tools for detecting SNPs and indels. It offers a solution to map NGS short reads with a moderate distance (up to 30% sequence divergence) from reference genomes. It poses no restrictions on the size of the reference, which, combined with its high sensitivity, makes the Variant Toolkit well-suited for targeted sequencing projects and diagnostics.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{proprietary}}, commercial

|

|

| Efficiently computes both spliced and unspliced alignments at high accuracy. Relying on a machine learning strategy combined with a fast mapping based on a banded Smith-Waterman-like algorithm, it aligns around 7 million reads per hour on one CPU. It refines the originally proposed QPALMA approach.

|

|

|

| {{yes}}

| {{free}}, GPL

|

|

| For use by biologists and bioinformaticians. It supports ungapped, gapped and splice-junction alignment from single and paired-end reads from Illumina, Life technologies Solid TM, Roche 454 and Ion Torrent raw data (with or without quality information). It integrates powerful quality control on FASTQ/Qual level and on aligned data. Additional functionality include trimming and filtering of raw reads, SNP and InDel detection, mRNA and microRNA quantification and fusion gene detection.

| {{yes}}

| {{yes}}

| {{yes}}

| Multiprocessor-core, client-server installation possible

| {{proprietary}}, commercial, free trial version

|

|

| Indexes the genome, then extends seeds using pre-computed alignments of words. Works with base space, color space (SOLID), and can align genomic and spliced RNA-seq reads.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{proprietary}}, freeware for academic and noncommercial use

|

|

| Indexes the genome with periodic seeds to quickly find alignments with full sensitivity up to four mismatches. It can map Illumina and SOLiD reads. Unlike most mapping programs, speed increases for longer read lengths.

|

|

|

| {{yes}}

| {{free}}, GPL

|{{cite journal|last1=Chen|first1=Yangho|last2=Souaiaia|first2=Tade|last3=Chen|first3=Ting|title=PerM: efficient mapping of short sequencing reads with periodic full sensitive spaced seeds|journal=Bioinformatics|volume=25|issue=19|year=2009|pages=2514–2521|pmid=19675096|pmc=2752623|doi=10.1093/bioinformatics/btp486}}

|

| Indexes the genome with a k-mer lookup table with full sensitivity up to an adjustable number of mismatches. It is best for mapping 15-60 bp sequences to a genome.

| {{no}}

| {{no}}

| {{yes}}

| {{no}}, multiple processes per search

|

| [https://www.researchgate.net/publication/8966263_PRIMEX_rapid_identification_of_oligonucleotide_matches_in_whole_genomes]

| 2003

| Can use quality scores, intron lengths, and computation splice site predictions to perform and performs an unbiased alignment. Can be trained to the specifics of a RNA-seq experiment and genome. Useful for splice site/intron discovery and for gene model building. (See PALMapper for a faster version).

|

|

|

| {{yes}}, client-server

| {{free}}, GPL 2

|

|

| No read length limit. Hamming or edit distance mapping with configurable error rates. Configurable and predictable sensitivity (runtime/sensitivity tradeoff). Supports paired-end read mapping.

|

|

|

|

| {{free}}, LGPL

|

|

| REAL is an efficient, accurate, and sensitive tool for aligning short reads obtained from next-generation sequencing. The programme can handle an enormous amount of single-end reads generated by the next-generation Illumina/Solexa Genome Analyzer. cREAL is a simple extension of REAL for aligning short reads obtained from next-generation sequencing to a genome with circular structure.

|

| {{yes}}

|

| {{yes}}

| {{free}}, GPL

|

|

| Can map reads with or without error probability information (quality scores) and supports paired-end reads or bisulfite-treated read mapping. There are no limitations on read length or number of mismatches.

| {{yes}}

| {{yes}}

| {{yes}}

|

| {{free}}, GPL 3

|

|

| A randomized Numerical Aligner for Accurate alignment of NGS reads

| {{yes}}

| {{partial|Low quality bases trimming}}

| {{yes}}

| Multithreading and MPI-enabled

| {{free}}, GPL 3

|

|

| Extremely fast, tolerant to high indel and substitution counts. Includes full read alignment. Product includes comprehensive pipelines for variant detection and metagenomic analysis with any combination of Illumina, Complete Genomics and Roche 454 data.

| {{yes}}

| {{yes}}, for variant calling

| {{yes}}

| {{yes}}

| {{proprietary}}, freeware for individual investigator use

|

|

| Can handle insertions, deletions, mismatches; uses enhanced suffix arrays

| {{yes}}

| {{no}}

| {{yes}}

| {{yes}}

| {{proprietary}}, freeware for noncommercial use

|{{cite journal|last1=Searls|first1=David B.|last2=Hoffmann|first2=Steve|last3=Otto|first3=Christian|last4=Kurtz|first4=Stefan|last5=Sharma|first5=Cynthia M.|last6=Khaitovich|first6=Philipp|last7=Vogel|first7=Jörg|last8=Stadler|first8=Peter F.|last9=Hackermüller|first9=Jörg|title=Fast Mapping of Short Sequences with Mismatches, Insertions and Deletions Using Index Structures|journal=PLOS Computational Biology|volume=5|issue=9|year=2009|pages=e1000502|issn=1553-7358|doi=10.1371/journal.pcbi.1000502|pmid=19750212|pmc=2730575|bibcode=2009PLSCB...5E0502H |doi-access=free }}

|2009

| Up to 5 mixed substitutions and insertions-deletions; various tuning options and input-output formats

|

|

|

|

| {{proprietary}}, freeware for academic and noncommercial use

|

|

| Short read error correction with a suffix tree data structure

|

|

|

| {{yes}}, Java

|

|

|

| Indexes the reference genome as of version 2. Uses masks to generate possible keys. Can map ABI SOLiD color space reads.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}, OpenMP

| {{free}}, [[BSD licenses

| {{free}}, BSD]] derivative

|

{{cite journal|last1=Rumble|first1=Stephen M.|last2=Lacroute|first2=Phil|last3=Dalca|first3=Adrian V.|last4=Fiume|first4=Marc|last5=Sidow|first5=Arend|last6=Brudno|first6=Michael|title=SHRiMP: Accurate Mapping of Short Color-space Reads|journal=PLOS Computational Biology

|volume=5|issue=5|year=2009|pages=e1000386|pmid=19461883|pmc=2678294|doi=10.1371/journal.pcbi.1000386|bibcode=2009PLSCB...5E0386R |doi-access=free }}

{{cite journal|last1=David|first1=Matei|last2=Dzamba|first2=Misko|last3=Lister|first3=Dan|last4= Ilie|first4=Lucian|last5=Brudno|first5=Michael|title=SHRiMP2: Sensitive yet Practical Short Read Mapping|journal=Bioinformatics|volume=27|issue=7|year=2011|pages=1011–1012|pmid=21278192|doi=10.1093/bioinformatics/btr046|doi-access=free}}

| 2009-2011

| Slider is an application for the Illumina Sequence Analyzer output that uses the "probability" files instead of the sequence files as an input for alignment to a reference sequence or a set of reference sequences.

| {{yes}}

| {{yes}}

| {{No}}

| {{No}}

|

|{{cite journal|last1=Malhis|first1=Nawar|last2=Butterfield|first2=Yaron S. N.|last3=Ester|first3=Martin|last4=Jones|first4=Steven J. M.|title=Slider – Maximum use of probability information for alignment of short sequence reads and SNP detection|journal=Bioinformatics

|volume=25|issue=1|year=2009|pages=6–13|pmid=18974170|pmc=2638935|doi=10.1093/bioinformatics/btn565}}{{cite journal|last1=Malhis|first1=Nawar|last2=Jones|first2=Steven J. M.|title=High Quality SNP Calling Using Illumina Data at Shallow Coverage|journal=Bioinformatics

|volume=26|issue=8|year=2010|pages=1029–1035|pmid=20190250|doi=10.1093/bioinformatics/btq092|doi-access=}}

| 2009-2010

| SOAP: robust with a small (1-3) number of gaps and mismatches. Speed improvement over BLAT, uses a 12 letter hash table. SOAP2: using bidirectional BWT to build the index of reference, and it is much faster than the first version. SOAP3: GPU-accelerated version that could find all 4-mismatch alignments in tens of seconds per one million reads. SOAP3-dp, also GPU accelerated, supports arbitrary number of mismatches and gaps according to affine gap penalty scores.

| {{yes}}

| {{no}}

| {{yes}}, SOAP3-dp

| {{yes}}, POSIX Threads; SOAP3, SOAP3-dp need GPU with CUDA support

| {{free}}, GPL

|{{cite journal|last1=Li|first1=R.|last2=Li|first2=Y.|last3=Kristiansen|first3=K.|last4=Wang|first4=J.|title=SOAP: short oligonucleotide alignment program|journal=Bioinformatics|volume=24|issue=5|year=2008|pages=713–714|issn=1367-4803|doi=10.1093/bioinformatics/btn025|pmid=18227114|doi-access=free}}{{cite journal|last1=Li|first1=R.|last2=Yu|first2=C.|last3=Li|first3=Y.|last4=Lam|first4=T.-W.|last5=Yiu|first5=S.-M.|last6=Kristiansen|first6=K.|last7=Wang|first7=J.|title=SOAP2: an improved ultrafast tool for short read alignment|journal=Bioinformatics|volume=25|issue=15|year=2009|pages=1966–1967|issn=1367-4803|doi=10.1093/bioinformatics/btp336|pmid=19497933|doi-access=}}

|

| For ABI SOLiD technologies. Significant increase in time to map reads with mismatches (or color errors). Uses an iterative version of the Rabin-Karp string search algorithm.

|

|

|

| {{yes}}

| {{free}}, GPL

|

|

| Integrates the Burrows–Wheeler Aligner (BWA) on an Apache Spark framework running atop Hadoop. Version 0.2 of October 2016, supports the algorithms BWA-MEM, BWA-backtrack, and BWA-ALN. All of them work with single-reads and paired-end reads.

| {{yes}}

| {{partial|Low quality bases trimming}}

| {{yes}}

| {{yes}}

| {{free}}, GPL 3

|{{Cite journal|last1=Abuín|first1=José M.|last2=Pichel|first2=Juan C.|last3=Pena|first3=Tomás F.|last4=Amigo|first4=Jorge|date=2016-05-16|title=SparkBWA: Speeding Up the Alignment of High-Throughput DNA Sequencing Data|journal=PLOS ONE|volume=11|issue=5|pages=e0155461|doi=10.1371/journal.pone.0155461|issn=1932-6203|pmid=27182962|pmc=4868289|bibcode=2016PLoSO..1155461A|doi-access=free}}

|2016

| Fast for a small number of variants

|

|

|

|

| {{proprietary}}, freeware for academic and noncommercial use

|

|

| For Illumina reads. High specificity, and sensitive for reads with indels, structural variants, or many SNPs. Slow, but speed increased dramatically by using BWA for first alignment pass.

| {{yes}}

| {{yes}}

| {{yes}}

| {{no}}

| {{proprietary}}, freeware for academic and noncommercial use

|{{cite journal|last1=Lunter|first1=G.|last2=Goodson|first2=M.|title=Stampy: A statistical algorithm for sensitive and fast mapping of Illumina sequence reads|journal=Genome Research|volume=21|issue=6|year=2010|pages=936–939|issn=1088-9051|doi=10.1101/gr.111120.110|pmid=20980556|pmc=3106326}}

| 2010

| For Illumina or ABI SOLiD reads, with SAM native output. Highly sensitive for reads with many errors, indels (full from 0 to 15, extended support otherwise). Uses spaced seeds (single hit) and a very fast SSE-SSE2-AVX2-AVX-512 banded alignment filter. For fixed-length reads only, authors recommend SHRiMP2 otherwise.

| {{no}}

| {{yes}}

| {{yes}}

| {{yes}}, OpenMP

| {{free}}

|{{cite journal|last1=Noe|first1=L.|last2=Girdea|first2=M.|last3=Kucherov|first3=G.|title=Designing efficient spaced seeds for SOLiD read mapping|journal=Advances in Bioinformatics|volume=2010|year=2010|page=708501|pmid=20936175|pmc=2945724|doi=10.1155/2010/708501|doi-access=free}}

|2010

| Superfast and accurate read aligners. Subread can be used to map both gDNA-seq and RNA-seq reads. Subjunc detects exon-exon junctions and maps RNA-seq reads. They employ a novel mapping paradigm named seed-and-vote.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{free}}, GPL 3

|

|

| De-novo assembler for Illumina reads

|

|

|

|

| {{proprietary}}, freeware for academic and noncommercial use

|

|

| Visual interface both for Bowtie and BWA, and an embedded aligner

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{free}}, GPL

|

|

| FPGA-accelerated reference sequence alignment mapping tool from TimeLogic. Faster than Burrows–Wheeler transform-based algorithms like BWA and Bowtie. Supports up to 7 mismatches and/or indels with no performance penalty. Produces sensitive Smith–Waterman gapped alignments.

| {{yes}}

| {{yes}}

| {{yes}}

| {{yes}}

| {{proprietary}}, commercial

|

|

| FPGA based sliding window short read aligner which exploits the embarrassingly parallel property of short read alignment. Performance scales linearly with number of transistors on a chip (i.e. performance guaranteed to double with each iteration of Moore's Law without modification to algorithm). Low power consumption is useful for datacentre equipment. Predictable runtime. Better price/performance than software sliding window aligners on current hardware, but not better than software BWT-based aligners currently. Can manage large numbers (>2) of mismatches. Will find all hit positions for all seeds. Single-FPGA experimental version, needs work to develop it into a multi-FPGA production version.

|

|

|

|

| {{proprietary}}, freeware for academic and noncommercial use

|

|

| 100% sensitivity for a reads between 15 and 240 bp with practical mismatches. Very fast. Support insertions and deletions. Works with Illumina & SOLiD instruments, not 454.

|

|

|

| {{partial|Yes (GUI), no (CLI)}}

| {{proprietary}}, commercial

| {{cite journal|last1=Lin|first1=H.|last2=Zhang|first2=Z.|last3=Zhang|first3=M.Q.|last4=Ma|first4=B.|last5=Li|first5=M.|title=ZOOM! Zillions of oligos mapped|journal=Bioinformatics|volume=24|issue=21|year=2008|pages=2431–2437|pmid=18684737|pmc=2732274|doi=10.1093/bioinformatics/btn416}}

|