Accurate and reliable high-throughput detection of copy number variation in the human genome

Heike Fiegler; Richard Redon; Dan Andrews; Carol Scott; Robert Andrews; Carol Carder; Richard Clark; Oliver Dovey; Peter Ellis; Lars Feuk; Lisa French; Paul Hunt; Dimitrios Kalaitzopoulos; James Larkin; Lyndal Montgomery; George H. Perry; Bob W. Plumb; Keith Porter; Rachel E. Rigby; Diane Rigler; Armand Valsesia; Cordelia Langford; Sean J. Humphray; Stephen W. Scherer; Charles Lee; Matthew E. Hurles; Nigel P. Carter

doi:10.1101/gr.5630906

Accurate and reliable high-throughput detection of copy number variation in the human genome

Heike Fiegler, Richard Redon, Dan Andrews, Carol Scott, Robert Andrews, Carol Carder, Richard Clark, Oliver Dovey, Peter Ellis, Lars Feuk, Lisa French, Paul Hunt, Dimitrios Kalaitzopoulos, James Larkin, Lyndal Montgomery, George H. Perry, Bob W. Plumb, Keith Porter, Rachel E. Rigby, Diane RiglerArmand Valsesia, Cordelia Langford, Sean J. Humphray, Stephen W. Scherer, Charles Lee, Matthew E. Hurles, Nigel P. Carter^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

119 Citations (Scopus)

Abstract

This study describes a new tool for accurate and reliable high-throughput detection of copy number variation in the human genome. We have constructed a large-insert clone DNA microarray covering the entire human genome in tiling path resolution that we have used to identify copy number variation in human populations. Crucial to this study has been the development of a robust array platform and analytic process for the automated identification of copy number variants (CNVs). The array consists of 26,574 clones covering 93.7% of euchromatic regions. Clones were selected primarily from the published "Golden Path," and mapping was confirmed by fingerprinting and BAC-end sequencing. Array performance was extensively tested by a series of validation assays. These included determining the hybridization characteristics of each individual clone on the array by chromosome-specific add-in experiments. Estimation of data reproducibility and false-positive/negative rates was carried out using self-self hybridizations, replicate experiments, and independent validations of CNVs. Based on these studies, we developed a variance-based automatic copy number detection analysis process (CNVfinder) and have demonstrated its robustness by comparison with the SW-ARRAY method.

Original language	English
Pages (from-to)	1566-1574
Number of pages	9
Journal	Genome Research
Volume	16
Issue number	12
DOIs	https://doi.org/10.1101/gr.5630906
Publication status	Published - Dec 2006

Access to Document

10.1101/gr.5630906

Cite this

Fiegler, H., Redon, R., Andrews, D., Scott, C., Andrews, R., Carder, C., Clark, R., Dovey, O., Ellis, P., Feuk, L., French, L., Hunt, P., Kalaitzopoulos, D., Larkin, J., Montgomery, L., Perry, G. H., Plumb, B. W., Porter, K., Rigby, R. E., ... Carter, N. P. (2006). Accurate and reliable high-throughput detection of copy number variation in the human genome. Genome Research, 16(12), 1566-1574. https://doi.org/10.1101/gr.5630906

@article{1cadf9b4324a4654a0c817ce57615599,

title = "Accurate and reliable high-throughput detection of copy number variation in the human genome",

abstract = "This study describes a new tool for accurate and reliable high-throughput detection of copy number variation in the human genome. We have constructed a large-insert clone DNA microarray covering the entire human genome in tiling path resolution that we have used to identify copy number variation in human populations. Crucial to this study has been the development of a robust array platform and analytic process for the automated identification of copy number variants (CNVs). The array consists of 26,574 clones covering 93.7% of euchromatic regions. Clones were selected primarily from the published {"}Golden Path,{"} and mapping was confirmed by fingerprinting and BAC-end sequencing. Array performance was extensively tested by a series of validation assays. These included determining the hybridization characteristics of each individual clone on the array by chromosome-specific add-in experiments. Estimation of data reproducibility and false-positive/negative rates was carried out using self-self hybridizations, replicate experiments, and independent validations of CNVs. Based on these studies, we developed a variance-based automatic copy number detection analysis process (CNVfinder) and have demonstrated its robustness by comparison with the SW-ARRAY method.",

author = "Heike Fiegler and Richard Redon and Dan Andrews and Carol Scott and Robert Andrews and Carol Carder and Richard Clark and Oliver Dovey and Peter Ellis and Lars Feuk and Lisa French and Paul Hunt and Dimitrios Kalaitzopoulos and James Larkin and Lyndal Montgomery and Perry, {George H.} and Plumb, {Bob W.} and Keith Porter and Rigby, {Rachel E.} and Diane Rigler and Armand Valsesia and Cordelia Langford and Humphray, {Sean J.} and Scherer, {Stephen W.} and Charles Lee and Hurles, {Matthew E.} and Carter, {Nigel P.}",

year = "2006",

month = dec,

doi = "10.1101/gr.5630906",

language = "English",

volume = "16",

pages = "1566--1574",

journal = "Genome Research",

issn = "1088-9051",

publisher = "Cold Spring Harbor Laboratory Press",

number = "12",

}

Fiegler, H, Redon, R, Andrews, D, Scott, C, Andrews, R, Carder, C, Clark, R, Dovey, O, Ellis, P, Feuk, L, French, L, Hunt, P, Kalaitzopoulos, D, Larkin, J, Montgomery, L, Perry, GH, Plumb, BW, Porter, K, Rigby, RE, Rigler, D, Valsesia, A, Langford, C, Humphray, SJ, Scherer, SW, Lee, C, Hurles, ME & Carter, NP 2006, 'Accurate and reliable high-throughput detection of copy number variation in the human genome', Genome Research, vol. 16, no. 12, pp. 1566-1574. https://doi.org/10.1101/gr.5630906

TY - JOUR

T1 - Accurate and reliable high-throughput detection of copy number variation in the human genome

AU - Fiegler, Heike

AU - Redon, Richard

AU - Andrews, Dan

AU - Scott, Carol

AU - Andrews, Robert

AU - Carder, Carol

AU - Clark, Richard

AU - Dovey, Oliver

AU - Ellis, Peter

AU - Feuk, Lars

AU - French, Lisa

AU - Hunt, Paul

AU - Kalaitzopoulos, Dimitrios

AU - Larkin, James

AU - Montgomery, Lyndal

AU - Perry, George H.

AU - Plumb, Bob W.

AU - Porter, Keith

AU - Rigby, Rachel E.

AU - Rigler, Diane

AU - Valsesia, Armand

AU - Langford, Cordelia

AU - Humphray, Sean J.

AU - Scherer, Stephen W.

AU - Lee, Charles

AU - Hurles, Matthew E.

AU - Carter, Nigel P.

PY - 2006/12

Y1 - 2006/12

N2 - This study describes a new tool for accurate and reliable high-throughput detection of copy number variation in the human genome. We have constructed a large-insert clone DNA microarray covering the entire human genome in tiling path resolution that we have used to identify copy number variation in human populations. Crucial to this study has been the development of a robust array platform and analytic process for the automated identification of copy number variants (CNVs). The array consists of 26,574 clones covering 93.7% of euchromatic regions. Clones were selected primarily from the published "Golden Path," and mapping was confirmed by fingerprinting and BAC-end sequencing. Array performance was extensively tested by a series of validation assays. These included determining the hybridization characteristics of each individual clone on the array by chromosome-specific add-in experiments. Estimation of data reproducibility and false-positive/negative rates was carried out using self-self hybridizations, replicate experiments, and independent validations of CNVs. Based on these studies, we developed a variance-based automatic copy number detection analysis process (CNVfinder) and have demonstrated its robustness by comparison with the SW-ARRAY method.

AB - This study describes a new tool for accurate and reliable high-throughput detection of copy number variation in the human genome. We have constructed a large-insert clone DNA microarray covering the entire human genome in tiling path resolution that we have used to identify copy number variation in human populations. Crucial to this study has been the development of a robust array platform and analytic process for the automated identification of copy number variants (CNVs). The array consists of 26,574 clones covering 93.7% of euchromatic regions. Clones were selected primarily from the published "Golden Path," and mapping was confirmed by fingerprinting and BAC-end sequencing. Array performance was extensively tested by a series of validation assays. These included determining the hybridization characteristics of each individual clone on the array by chromosome-specific add-in experiments. Estimation of data reproducibility and false-positive/negative rates was carried out using self-self hybridizations, replicate experiments, and independent validations of CNVs. Based on these studies, we developed a variance-based automatic copy number detection analysis process (CNVfinder) and have demonstrated its robustness by comparison with the SW-ARRAY method.

UR - http://www.scopus.com/inward/record.url?scp=33751349817&partnerID=8YFLogxK

U2 - 10.1101/gr.5630906

DO - 10.1101/gr.5630906

M3 - Article

SN - 1088-9051

VL - 16

SP - 1566

EP - 1574

JO - Genome Research

JF - Genome Research

IS - 12

ER -

Accurate and reliable high-throughput detection of copy number variation in the human genome

Abstract

Access to Document

Other files and links

Fingerprint

Cite this