Published January 19, 2022
| Version 1.0
Dataset
Open
Metaclusters by DPCfam clustering of UniRef50 v 2017_07
Authors/Creators
- 1. Sissa, Trieste (IT); Area Science Park, Trieste (IT)
- 2. Area Science Park, Trieste (IT)
Contributors
Data curator:
Other:
Researcher:
Supervisor (2):
- 1. Area Science Park, Trieste (IT)
- 2. SISSA, Trieste (IT)
- 3. Center for Omics Sciences, IRCCS San Raffaele Hospital Milan (IT)
- 4. European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton. UK
Description
Metaclusters obtained from the DPCfam clustering of UniRef50, v. 2017_07.
Metaclusters represent putative protein families automatically derived using the DPCfam method, as described in Unsupervised protein family classification by Density Peak clustering, Russo ET, 2020, PhD Thesis http://hdl.handle.net/20.500.11767/116345 . Supervisors: Alessandro Laio, Marco Punta.
Visit also https://dpcfam.areasciencepark.it/ to easily navigate the data.
FILES DESCRIPTION:
- metaclusters_xml.tar.gz Metaclusters' seeds, unaligned in an xml table. All metaclusters are listed. Metaclusters entries include also some statistical information about each MC (such as size, average length, low complexity fraction etc, ) and Pfam comparison (Dominant Architecture). A README file is included describing the data. A parser is included to transform XML data to space-separated tables. XML schema is included.
- metaclusters_msas.tar.gz Metsclusters' multiple sequence alignments, in fasta format. Only MCs with seeds with 1) more than 50 elements and 2) average length larger than 50 a.a.s are reported .
- metaclusters_hmms.tar.gz Metsclusters' profile-hmms. A ".hmm" file for each metacluser. Only MCs with seeds with 1) more than 50 elements and 2) average length larger than 50 a.a.s are reported .
- all_metaclusters_hmm.tar.gz Collctive metaclusters' profile-hmm. A single .hmm file collecting all MC's profile-hmm. . Only MCs with seeds with 1) more than 50 elements and 2) average length larger than 50 a.a.s are reported
- uniref50_annotated.xml.gz UniRef50 v.2017_07 database annotated with Pfam families and DPCfam metaclusters. A README file is included describing the data. A parser is included to transform XML data to space-separated tables. XML schema is included. XML schema is derived from uniprot's UniRef50 xml schema.
Files
Additional details
References
- Unsupervised protein family classification by Density Peak clustering, Russo ET, 2020, PhD Thesis http://hdl.handle.net/20.500.11767/116345 . Supervisors: Alessandro Laio, Marco Punta.