Biology:Sequence clustering
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In bioinformatics, sequence clustering algorithms attempt to group biological sequences that are somehow related. The sequences can be either of genomic, "transcriptomic" (ESTs) or protein origin. For proteins, homologous sequences are typically grouped into families. For EST data, clustering is important to group sequences originating from the same gene before the ESTs are assembled to reconstruct the original mRNA.
Some clustering algorithms use single-linkage clustering, constructing a transitive closure of sequences with a similarity over a particular threshold. UCLUST[1] and CD-HIT[2] use a greedy algorithm that identifies a representative sequence for each cluster and assigns a new sequence to that cluster if it is sufficiently similar to the representative; if a sequence is not matched then it becomes the representative sequence for a new cluster. The similarity score is often based on sequence alignment. Sequence clustering is often used to make a non-redundant set of representative sequences.
Sequence clusters are often synonymous with (but not identical to) protein families. Determining a representative tertiary structure for each sequence cluster is the aim of many structural genomics initiatives.
Sequence clustering algorithms and packages
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- CD-HIT[2]
- UCLUST in USEARCH[1]
- Starcode:[3] a fast sequence clustering algorithm based on exact all-pairs search.[4]
- OrthoFinder:[5] a fast, scalable and accurate method for clustering proteins into gene families (orthogroups)[6][7]
- Linclust:[8] first algorithm whose runtime scales linearly with input set size, very fast, part of MMseqs2[9] software suite for fast, sensitive sequence searching and clustering of large sequence sets
- TribeMCL: a method for clustering proteins into related groups[10]
- BAG: a graph theoretic sequence clustering algorithm[11]
- JESAM:[12] Open source parallel scalable DNA alignment engine with optional clustering software component
- UICluster:[13] Parallel Clustering of EST (Gene) Sequences
- BLASTClust single-linkage clustering with BLAST[14]
- Clusterer:[15] extendable java application for sequence grouping and cluster analyses
- PATDB: a program for rapidly identifying perfect substrings
- nrdb:[16] a program for merging trivially redundant (identical) sequences
- CluSTr:[17] A single-linkage protein sequence clustering database from Smith-Waterman sequence similarities; covers over 7 mln sequences including UniProt and IPI
- ICAtools[18] - original (ancient) DNA clustering package with many algorithms useful for artifact discovery or EST clustering
- Skipredudant EMBOSS tool[19] to remove redundant sequences from a set
- CLUSS Algorithm[20] to identify groups of structurally, functionally, or evolutionarily related hard-to-align protein sequences. CLUSS webserver [21]
- CLUSS2 Algorithm[22] for clustering families of hard-to-align protein sequences with multiple biological functions. CLUSS2 webserver [21]
Non-redundant sequence databases
- PISCES: A Protein Sequence Culling Server[23]
- RDB90[24]
- UniRef: A non-redundant UniProt sequence database[25]
- Uniclust: A clustered UniProtKB sequences at the level of 90%, 50% and 30% pairwise sequence identity.[26]
- Virus Orthologous Clusters:[27] A viral protein sequence clustering database; contains all predicted genes from eleven virus families organized into ortholog groups by BLASTP similarity
See also
References
- ↑ 1.0 1.1 "USEARCH". drive5.com. http://www.drive5.com/usearch.
- ↑ 2.0 2.1 "CD-HIT: a ultra-fast method for clustering protein and nucleotide sequences, with many new applications in next generation sequencing (NGS) data". cd-hit.org. http://cd-hit.org.
- ↑ "Starcode repository". 2018-10-11. https://github.com/gui11aume/starcode.
- ↑ "Starcode: sequence clustering based on all-pairs search". Bioinformatics 31 (12): 1913–9. June 2015. doi:10.1093/bioinformatics/btv053. PMID 25638815.
- ↑ "OrthoFinder". Steve Kelly Lab. http://www.stevekellylab.com/software/orthofinder.
- ↑ "OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy". Genome Biology 16 (1): 157. August 2015. doi:10.1186/s13059-015-0721-2. PMID 26243257.
- ↑ "OrthoFinder: phylogenetic orthology inference for comparative genomics". Genome Biology 20 (1): 238. November 2019. doi:10.1186/s13059-019-1832-y. PMID 31727128.
- ↑ "Clustering huge protein sequence sets in linear time". Nature Communications 9 (1): 2542. June 2018. doi:10.1038/s41467-018-04964-5. PMID 29959318. Bibcode: 2018NatCo...9.2542S.
- ↑ "MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets". Nature Biotechnology 35 (11): 1026–1028. November 2017. doi:10.1038/nbt.3988. PMID 29035372.
- ↑ "An efficient algorithm for large-scale detection of protein families". Nucleic Acids Research 30 (7): 1575–84. April 2002. doi:10.1093/nar/30.7.1575. PMID 11917018.
- ↑ "Archived copy". http://bio.informatics.indiana.edu/sunkim/BAG/.
- ↑ "Bioinformatics Paper: JESAM: CORBA software components for EST alignments and clusters". littlest.co.uk. http://www.littlest.co.uk/software/bioinf/old_packages/jesam/jesam_paper.html.
- ↑ "pedretti@eyeball -- Clustering Page". http://ratest.eng.uiowa.edu/pubsoft/clustering/.
- ↑ "NCBI News: Spring 2004-BLASTLab". nih.gov. https://www.ncbi.nlm.nih.gov/Web/Newsltr/Spring04/blastlab.html.
- ↑ "Clusterer: extendable java application for sequence grouping and cluster analyses". bugaco.com. http://bugaco.com/bioinf/clusterer/.
- ↑ "Index of /pub/nrdb". http://blast.wustl.edu/pub/nrdb/.
- ↑ "CluSTr". http://www.ebi.ac.uk/clustr/.
- ↑ "Introduction to the ICAtools". littlest.co.uk. http://www.littlest.co.uk/software/bioinf/old_packages/icatools/.
- ↑ "EMBOSS: skipredundant". pasteur.fr. http://bioweb2.pasteur.fr/docs/EMBOSS/skipredundant.html.
- ↑ "CLUSS: clustering of protein sequences based on a new similarity measure". BMC Bioinformatics 8: 286. August 2007. doi:10.1186/1471-2105-8-286. PMID 17683581.
- ↑ 21.0 21.1 "CLUSS Home Page". http://prospectus.usherbrooke.ca/CLUSS/.
- ↑ "CLUSS2: an alignment-independent algorithm for clustering protein families with multiple biological functions". International Journal of Computational Biology and Drug Design 1 (2): 122–40. 2008. doi:10.1504/ijcbdd.2008.020190. PMID 20058485.
- ↑ "Dunbrack Lab". fccc.edu. http://dunbrack.fccc.edu/pisces/.
- ↑ "Removing near-neighbour redundancy from large protein sequence collections". Bioinformatics 14 (5): 423–9. June 1998. doi:10.1093/bioinformatics/14.5.423. PMID 9682055.
- ↑ "About UniProt". uniprot.org. https://www.uniprot.org/database/DBDescription.shtml#uniref.
- ↑ "Uniclust databases of clustered and deeply annotated protein sequences and alignments". Nucleic Acids Research 45 (D1): D170–D176. January 2017. doi:10.1093/nar/gkw1081. PMID 27899574.
- ↑ "VOCS - Viral Bioinformatics Resource Center". uvic.ca. http://athena.bioc.uvic.ca/tools/VOCS.
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