Reduction, alignment and visualisation of large diverse sequence families.

ABSTRACT:

Background

Current volumes of sequence data can lead to large numbers of hits identified on a search, typically in the range of 10s to 100s of thousands. It is often quite difficult to tell from these raw results whether the search has been a success or has picked-up sequences with little or no relationship to the query. The best approach to this problem is to cluster and align the resulting families, however, existing methods concentrate on fast clustering and either do not align the sequences or only perform a limited alignment.

Results

A method (MULSEL) is presented that combines fast peptide-based pre-sorting with a following cascade of mini-alignments, each of which are generated with a robust profile/profile method. From these mini-alignments, a representative sequence

SUBMITTER: Taylor WR 

PROVIDER: S-EPMC4971687 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature