OD-seq: outlier detection in multiple sequence alignments.

ABSTRACT:

Background

Multiple sequence alignments (MSA) are widely used in sequence analysis for a variety of tasks. Outlier sequences can make downstream analyses unreliable or make the alignments less accurate while they are being constructed. This paper describes a simple method for automatically detecting outliers and accompanying software called OD-seq. It is based on finding sequences whose average distance to the rest of the sequences in a dataset, is anomalous.

Results

The software can take a MSA, distance matrix or set of unaligned sequences as input. Outlier sequences are found by examining the average distance of each sequence to the rest. Anomalous average distances are then found using the interquartile range of the distribution of average distances or by bootstrapping th

SUBMITTER: Jehl P 

PROVIDER: S-EPMC4548304 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature