Improving structural variant clustering to reduce the negative effect of the breakpoint uncertainty problem.

ABSTRACT:

Background

Structural variants (SVs) represent an important source of genetic variation. One of the most critical problems in their detection is breakpoint uncertainty associated with the inability to determine their exact genomic position. Breakpoint uncertainty is a characteristic issue of structural variants detected via short-read sequencing methods and complicates subsequent population analyses. The commonly used heuristic strategy reduces this issue by clustering/merging nearby structural variants of the same type before the data from individual samples are merged.

Results

We compared the two most used dissimilarity measures for SV clustering in terms of Mendelian inheritance errors (MIE), kinship prediction, and deviation from Hardy-Weinberg equilibrium. We analyzed t

SUBMITTER: Geryk J 

PROVIDER: S-EPMC8474851 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature