title: Exome copy number variation detection: Use of a pool of unrelated healthy tissue as reference sample.
abstract: An increasing number of bioinformatic tools designed to detect CNVs (copy number variants) in tumor samples based on paired exome data where a matched healthy tissue constitutes the reference have been published in the recent years. The idea of using a pool of unrelated healthy DNA as reference has previously been formulated but not thoroughly validated. As of today, the gold standard for CNV calling is still aCGH but there is an increasing interest in detecting CNVs by exome sequencing. We propose to design a metric allowing the comparison of two CNV profiles, independently of the technique used and assessed the validity of using a pool of unrelated healthy DNA instead of a matched healthy tissue as reference in exome-based CNV detection. We compared the CNV profiles obtained with three different approaches (aCGH, exome sequencing with a matched healthy tissue as reference, exome sequencing with a pool of eight unrelated healthy tissue as reference) on three multiple myeloma samples. We show that the usual analyses performed to compare CNV profiles (deletion/amplification ratios and CNV size distribution) lack in precision when confronted with low LRR values, as they only consider the binary status of each CNV. We show that the metric-based distance constitutes a more accurate comparison of two CNV profiles. Based on these analyses, we conclude that a reliable picture of CNV alterations in multiple myeloma samples can be obtained from whole-exome sequencing in the absence of a matched healthy sample.
authors.affiliation: Laboratory of Human Genetics, GIGA-Research, University of Liège, Liège, Belgium.
authors.forename: Stephane
authors.initials: S
authors.lastname: Wenric
authors.affiliation: Laboratory of Human Genetics, GIGA-Research, University of Liège, Liège, Belgium.
authors.forename: Tiberio
authors.initials: T
authors.lastname: Sticca
authors.affiliation: Department of Human Genetics, University Hospital (CHU), Liège, Belgium.
authors.forename: Jean-Hubert
authors.initials: JH
authors.lastname: Caberg
authors.affiliation: Laboratory of Human Genetics, GIGA-Research, University of Liège, Liège, Belgium.
authors.forename: Claire
authors.initials: C
authors.lastname: Josse
authors.affiliation: Laboratory of Human Genetics, GIGA-Research, University of Liège, Liège, Belgium.
authors.forename: Corinne
authors.initials: C
authors.lastname: Fasquelle
authors.affiliation: Department of Human Genetics, University Hospital (CHU), Liège, Belgium.
authors.forename: Christian
authors.initials: C
authors.lastname: Herens
authors.affiliation: Department of Human Genetics, University Hospital (CHU), Liège, Belgium.
authors.forename: Mauricette
authors.initials: M
authors.lastname: Jamar
authors.affiliation: Department of Haematology and Immuno-haematology, University Hospital (CHU), Liège, Belgium.
authors.forename: Stéphanie
authors.initials: S
authors.lastname: Max
authors.affiliation: Department of Haematology and Immuno-haematology, University Hospital (CHU), Liège, Belgium.
authors.forename: André
authors.initials: A
authors.lastname: Gothot
authors.affiliation: Laboratory of Haematology, GIGA-Research, University of Liège, Liège, Belgium.|Department of Clinical Haematology, University Hospital (CHU), Liège, Belgium.
authors.forename: Jo
authors.initials: J
authors.lastname: Caers
authors.affiliation: Laboratory of Human Genetics, GIGA-Research, University of Liège, Liège, Belgium.|Department of Human Genetics, University Hospital (CHU), Liège, Belgium.
authors.forename: Vincent
authors.initials: V
authors.lastname: Bours
mesh_terms: D000465:Algorithms; D001853:Bone Marrow / Q000378:metabolism*; D016022:Case-Control Studies; D019295:Computational Biology; D056915:DNA Copy Number Variations / Q000235:genetics*; D059472:Exome / Q000235:genetics*; D006801:Humans; D009101:Multiple Myeloma / Q000235:genetics*; D012015:Reference Standards
keywords: CNV; NGS; WES; aCGH; control; multiple myeloma; normalization; read count