Package: CNVMetrics
Authors: Astrid DeschĂȘnes [aut, cre] (ORCID: https://orcid.org/0000-0001-7846-6749), Pascal Belleau [aut] (ORCID: https://orcid.org/0000-0002-0802-1071), David A. Tuveson [aut] (ORCID: https://orcid.org/0000-0002-8017-2712), Alexander Krasnitz [aut]
Version: 1.11.0
Compiled date: 2024-10-29
License: Artistic-2.0

1 Licensing

The CNVMetrics package and the underlying CNVMetrics code are distributed under the Artistic license 2.0. You are free to use and redistribute this software.



2 Citing

If you use this package for a publication, we would ask you to cite one of the following.

When using the copy number profile simulating method:

DeschĂȘnes A, Belleau P, Tuveson DA and Krasnitz A. Quantifying similarity between copy number profiles with CNVMetrics package [version 1; not peer reviewed]. F1000Research 2022, 11:816 (poster) (doi: 10.7490/f1000research.1119043.1)

F1000Research poster

When using the metrics:

Belleau P, DeschĂȘnes A, Beyaz S et al. CNVMetrics package: Quantifying similarity between copy number profiles [version 1; not peer reviewed]. F1000Research 2021, 10:737 (slides) (doi: 10.7490/f1000research.1118704.1)

F1000Research poster



3 Introduction

Copy number variation (CNV) includes multiplication and deletion of DNA segment. Copy number variations have been shown to be associated with a wide spectrum of pathological conditions and complex traits, such as developmental neuropsychiatric disorders (Hiroi et al. 2013) and especially cancer (Stratton, Campbell, and Futreal 2009).

CNVs are usually reported, for each sample, as genomic regions that are duplicated or deleted with respect to a reference. Those regions are denoted as CNV status calls. The level of amplification or deletion can also be reported, usually in log2 ratio values or normalized read depth (Zhao et al. 2013). As an example, the Figure 1 shows the copy number profiles from sequencing data of two mouse pancreatic organoids (Oni et al. 2020), calculated with CNprep (Belleau et al. 2020) and plot with gtrellis (Gu, Eils, and Schlesner 2016).