Copy Number Variations (CNV)
Analysis
Background
A copy number variant (CNV)
is a segment of DNA in which differences of
copy-number (number of copies of a molecule or portions of it) can be found
by comparison of two or more genomes. These variants may either be inherited or
caused by de novo mutation, such as deletions, duplications, inversions, and
translocations. The segment may range from one kilobase to several megabases in
size. Diploid organisms ordinarily have
two copies of each autosomal region, one per chromosome. This may vary for
particular genetic regions due to deletion or duplication.
It has been shown that SNP microarrays can be used to identify a variety of copy number variations, such
as insertions and deletions as well as loss of heterozygosity (copy number
neutral variations) (Oosting, Lips et al.
2007).
Analysis
Simbiot contains functions to perform CNV
analysis on data generated using Affymetrix and Illumina SNP microarrays. The analysis is implemented using the algorithm published in the Bioconductor (Gentleman, Carey et al.
2004)
snapCGH (Marioni, Thorne et al.
2006; Smith, Marioni et al. 2006) library. A total of five copy number analysis
algorithms are available including two versions of Hidden Markov Models.
Free demo accounts are available at http://www.simbiot.net.
Please also see more information about Simbiot Single User Accounts and Private Server installations as well as a brief introduction to microarray analysis.
References
Oosting, J., E. H. Lips, et al. (2007). "High-resolution copy number
analysis of paraffin-embedded archival tissue using SNP BeadArrays." Genome
Res 17(3): 368-76.
Gentleman, R. C., V. J. Carey, et al.
(2004). "Bioconductor: open software development for computational biology
and bioinformatics." Genome Biol 5(10): R80.
Marioni, J. C.,
N. P. Thorne, et al. (2006). "BioHMM: a heterogeneous hidden Markov model
for segmenting array CGH data." Bioinformatics 22(9): 1144-6.
Smith, M. L., J.
C. Marioni, et al. (2006). "snapCGH: Segmentation, Normalization and
Processing of aCGH Data Users' Guide." Bioconductor.
|
