ADaCGH: A parallelized web-based application and R package for the analysis of aCGH data.
BACKGROUND
Copy number alterations (CNAs) in genomic DNA have been associated with complex human diseases, including cancer. One of the most common techniques to detect CNAs is array-based comparative genomic hybridization (aCGH). The availability of aCGH platforms and the need for identification of CNAs has resulted in a wealth of methodological studies.


RESULTS
ADaCGH is an R package and a web-based application for the analysis of aCGH data. It implements eight methods for detection of CNAs, gains and losses of genomic DNA, including all of the best performing ones from two recent reviews (CBS, GLAD, CGHseg, HMM). For improved speed, we use parallel computing (via MPI). Additional information (GO terms, PubMed citations, KEGG and Reactome pathways) is available for individual genes, and for sets of genes with altered copy numbers.


CONCLUSIONS
ADACGH represents a qualitative increase in the standards of these types of applications: a) all of the best performing algorithms are included, not just one or two; b) we do not limit ourselves to providing a thin layer of CGI on top of existing BioConductor packages, but instead carefully use parallelization, examining different schemes, and are able to achieve significant decreases in user waiting time (factors up to 45x); c) we have added functionality not currently available in some methods, to adapt to recent recommendations (e.g., merging of segmentation results in wavelet-based and CGHseg algorithms); d) we incorporate redundancy, fault-tolerance and checkpointing, which are unique among web-based, parallelized applications; e) all of the code is available under open source licenses, allowing to build upon, copy, and adapt our code for other software projects.
Díaz-Uriarte
Ramón
R
Structural Biology and Biocomputing Programme, Spanish National Cancer Center, Madrid, Spain. rdiaz02@gmail.com
Rueda
Oscar M
OM
D000465:Algorithms; D055028:Comparative Genomic Hybridization / Q000379:methods*; D019295:Computational Biology / Q000379:methods; D056915:DNA Copy Number Variations; D020869:Gene Expression Profiling / Q000379:methods; D006801:Humans; D020407:Internet; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012984:Software; D013997:Time Factors
Proc Natl Acad Sci U S A. 2004 Jun 15;101(24):9067-72
15199222
BMC Genomics. 2006;7:91
16638145
BMC Bioinformatics. 2005;6:124
15910681
Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W477-81
16845053
PLoS Comput Biol. 2007 Jun;3(6):e122
17590078
Nat Genet. 2005 Jun;37 Suppl:S11-7
15920524
Cancer Res. 2004 May 1;64(9):3060-71
15126342
BMC Bioinformatics. 2007;8:9
17214880
Clin Cancer Res. 2005 Apr 15;11(8):2907-18
15837741
Biotechniques. 2003 Mar;Suppl:45-51
12664684
BMC Bioinformatics. 2007;8:145
17477871
Bioinformatics. 2005 Nov 15;21(22):4084-91
16159913
Science. 2004 Jul 23;305(5683):525-8
15273396
Comput Biol Chem. 2005 Feb;29(1):47-54
15680585
Cancer Res. 2004 Jul 1;64(13):4428-33
15231651
Biostatistics. 2005 Apr;6(2):211-26
15772101
PLoS Comput Biol. 2006 Sep 8;2(9):e87
16965174
Proc Natl Acad Sci U S A. 2006 Mar 21;103(12):4534-9
16537408
Nucleic Acids Res. 2005;33(11):3455-64
15961730
Nucleic Acids Res. 2006;34(2):445-50
16439806
Hum Genomics. 2004 May;1(4):287-99
15588488
Cancer Res. 2000 Feb 15;60(4):799-802
10706083
Eur J Hum Genet. 2006 Feb;14(2):139-48
16288307
Cancer Res. 2005 Jul 15;65(14):6071-9
16024607
Bioinformatics. 2004 Dec 12;20(18):3413-22
15381628
Cancer Res. 2000 Aug 15;60(16):4519-25
10969801
Biostatistics. 2004 Oct;5(4):557-72
15475419
Bioinformatics. 2005 Oct 1;21(19):3763-70
16081473
Bioinformatics. 2005 Mar15;21(6):821-2
15531610
BMC Bioinformatics. 2006;7:83
16504045
Cancer Inform. 2007 Feb 10;2:48-58
17992253
Nucleic Acids Res. 2007 Jul;35(Web Server issue):W81-5
17468499
Proc Natl Acad Sci U S A. 2002 Oct 1;99(20):12963-8
12297621
BMC Bioinformatics. 2005;6:85
15807904
BMC Bioinformatics. 2005;6:27
15705208
Bioinformatics. 2006 May 1;22(9):1144-6
16533818