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Chip type: GenomeWideSNP_6

Genome-Wide Human SNP Array 6.0

Affymetrix' press release: Affymetrix Sets New Standard in Genotyping With Genome-Wide Human SNP Array 6.0, May 21, 2007.

From the press release: "The Affymetrix SNP Array 6.0 contains more than 900,000 single nucleotide polymorphisms (SNPs) and more than 946,000 non-polymorphic probes for the detection of copy number variation. [...]".

The design of the 6.0 is better than 5.0. For instance, for SNPs the allele A and allele B probes where not necessarily aligned in target sequence on the 5.0 chip, but is (again) on the 6.0 chip.

The Affymetrix SNP 6.0 Array interrogates 934,946 SNPs and 946,371 CNPs totalling 1,878,317 loci.

Enzymes Nsp and Sty are used in parallel in the assay and the amplified targets are mixed together at the very end. For this reason, some of the probes on the array are targeting sequences that may sit on fragments cut by either enzymes or both. According to Jim Veitch (Affymetrix, 2007-10-22): the SNP probes occur in a Nsp, Sty or Nsp+Sty fragment, but the CN probes occur only Nsp and Nsp+Sty fragments (not Sty-alone fragments).

The Broad Institute has a Research News article 'A unique collaboration between Cambridge and Silicon Valley' (Sept 7, 2008), which gives some background on how the GenomeWideSNP_5 and GenomeWideSNP_6 chip types were developed as part of a collaboration between Affymetrix and the Broad Institute.

Early versions of this chip type are GenomeWideEx_6 and GenomeWideEx_6_v2.


This is the CDF file that is recommended and supported by aroma.affymetrix. Note, make sure to rename it such that you replace the dot with a comma.

> cdf <- AffymetrixCdfFile$byChipType("GenomeWideSNP_6", tags="Full")
> print(cdf)

Path: annotationData/chipTypes/GenomeWideSNP_6
Filename: GenomeWideSNP_6,Full.CDF
Filesize: 470.44MB
Chip type: GenomeWideSNP_6,Full
RAM: 0.00MB
File format: v4 (binary; XDA)
Dimension: 2572x2680
Number of cells: 6892960
Number of units: 1881415
Cells per unit: 3.66
Number of QC units: 4

> print(getChecksum(cdf))
[1] "3fbe0f6e7c8a346105238a3f3d10d4ec"