Supplementary data website

Ming Lin, Lee-Jen Wei, William R. Sellers, Marshall Lieberfarb, Wing Hung Wong and Cheng Li (2004) dChipSNP: Significance Curve and Clustering of SNP-Array-Based Loss-of-Heterozygosity Data. Bioinformatics. 20: 1233-1240. (Abstract)

Data

Data download: DCP files (to use with dChip, containing CEL and genotype information), array list and sample info files.

Also see “Supporting material” for “Genome-wide loss-of-heterozygosity analysis from laser-capture microdissected prostate cancer using SNP arrays and a novel bioinformatics platform dChipSNP” at Sellers Lab.

Software

dChipSNP

dChip, Manual (Pleas use the latest dChip for the updated SNP analysis functions in dChip)

Figures

Figure 1

Figure 2

Figure 3

Supplementary figure 1

The Inferred LOH data view. The LOH data in Figure 2 are redisplayed after applying “Nearest Neighbor” method to infer the “Non-informative” markers. The default extension size of 10 megabases is used here.

Supplementary figure 2

We generated the inferred LOH views on the whole genome for each of the three situations: 1. using all tumor samples; 2. without using triplicate tumor samples; 3. without using any replicate tumor samples. Comparing these three figures showed that:

1. Without using any replicate tumor samples tend to give more LOH regions than using all tumor samples. Hence we believe by using replicate samples can reduce the probability of giving false LOH regions.

2. Using duplicate tumor samples but not triplicate tumors samples gives similar LOH regions as using all tumor samples overall, though it detects slightly less LOH regions.