MetaCNV - a consensus approach to infer accurate copy numbers from low coverage data.

ABSTRACT:

Background

The majority of copy number callers requires high read coverage data that is often achieved with elevated material input, which increases the heterogeneity of tissue samples. However, to gain insights into smaller areas within a tissue sample, e.g. a cancerous area in a heterogeneous tissue sample, less material is used for sequencing, which results in lower read coverage. Therefore, more focus needs to be put on copy number calling that is sensitive enough for low coverage data.

Results

We present MetaCNV, a copy number caller that infers reliable copy numbers for human genomes with a consensus approach. MetaCNV specializes in low coverage data, but also performs well on normal and high coverage data. MetaCNV integrates the results of multiple copy number callers

SUBMITTER: Friedrich S 

PROVIDER: S-EPMC7268502 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature