SUMMARY: Copy number variants (CNVs) are a major source of genetic variation. Comparing CNVs between samples is important in elucidating their potential effects in a wide variety of biological contexts. HD-CNV (hotspot detector for copy number variants) is a tool for downstream analysis of previously identified CNV regions from multiple samples, and it detects recurrent regions by finding cliques in an interval graph generated from the input. It creates a unique graphical representation of the data, as well as summary spreadsheets and UCSC (University of California, Santa Cruz) Genome Browser track files. The interval graph, when viewed with other software or by automated graph analysis, is useful in identifying genomic regions of interest for further study. AVAILABILITY AND IMPLEMENTATION: HD-CNV is an open source Java code and is freely available, with tutorials and sample data from http://daleylab.org. CONTACT: jcamer7@uwo.ca
SUMMARY: Copy number variants (CNVs) are a major source of genetic variation. Comparing CNVs between samples is important in elucidating their potential effects in a wide variety of biological contexts. HD-CNV (hotspot detector for copy number variants) is a tool for downstream analysis of previously identified CNV regions from multiple samples, and it detects recurrent regions by finding cliques in an interval graph generated from the input. It creates a unique graphical representation of the data, as well as summary spreadsheets and UCSC (University of California, Santa Cruz) Genome Browser track files. The interval graph, when viewed with other software or by automated graph analysis, is useful in identifying genomic regions of interest for further study. AVAILABILITY AND IMPLEMENTATION:HD-CNV is an open source Java code and is freely available, with tutorials and sample data from http://daleylab.org. CONTACT: jcamer7@uwo.ca
Authors: Joshua J Faber-Hammond; Etienne Bezault; David H Lunt; Domino A Joyce; Suzy C P Renn Journal: Genome Biol Evol Date: 2019-10-01 Impact factor: 3.416
Authors: M Elizabeth O Locke; Maja Milojevic; Susan T Eitutis; Nisha Patel; Andrea E Wishart; Mark Daley; Kathleen A Hill Journal: BMC Genomics Date: 2015-07-04 Impact factor: 3.969
Authors: Christina A Castellani; Melkaye G Melka; Andrea E Wishart; M Elizabeth O Locke; Zain Awamleh; Richard L O'Reilly; Shiva M Singh Journal: BMC Bioinformatics Date: 2014-04-21 Impact factor: 3.169