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Status |
Public on Dec 31, 2010 |
Title |
CC_Kidney_156_SNP_Xba |
Sample type |
genomic |
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Source name |
Clear cell renal cell caricinoma
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Organism |
Homo sapiens |
Characteristics |
tissue: Clear cell renal cell caricinoma gender: F tumor size(cm): 2.2
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Extracted molecule |
genomic DNA |
Extraction protocol |
extraction of total Genomic DNA was performed using Genomed JETquick tissue DNA Maxi Kit (part # 452050), according to manufacturers instructions.
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Label |
R-Phycoerythrin Streptavidin (SAPE)
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Label protocol |
40 ug per Xba1 chip and 40 ug per HindIII chip. Purified pooled 3 Xba1 PCRs with 3 pooled HindIII PCRs. R-Phycoerythrin Streptavidin (SAPE), from Molecular Probes, 1 mg/ml (we use 6ul per reaction).
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Hybridization protocol |
Following fragmentation, 40 ug of genomic DNA was hybridized for 16 hr at 48C on Affymetrix GeneChip Human Mapping 50K chip, either Xba Array or Hind array. GeneChips were washed and stained in the Affymetrix Fluidics Station 450.
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Scan protocol |
GeneChips were scanned using the Affymetrix GeneChip Scanner 7G.
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Description |
GR156T Hybridized to 50K Xba
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Data processing |
Starting from the CEL files, we used the R package oligo (48) to read the raw SNP data set. The result is an object containing the summarized signals of either A or B allele, of sense or antisense strand for each SNP on the array. The SNP's A or B allele signal was averaged by its sense and antisense signals respectively. To obtain SNP raw copy numbers, we used a total of 56 normal references either downloaded from Affymetrix (n = 48) or obtained by our own scan on normal kidney tissues (n = 8) to calculate the reference signals for each SNP's A and B alleles. The overall signal for the SNP was the sum of its A and B signals. The raw copy number for a SNP of a target sample was its overall signal subtracted by the averaged overall signals from the normal references (as all signals are in logarithm scale). We then used a divide-and-conquer algorithm to partition the raw copy numbers into segments based on the maximum likelihood estimate of the break points. It is a top-down algorithm to speed up the segmentation process. The raw copy numbers of SNPs within any identified segment will be regarded identical. The (one-sided t-) test score (to test location=0) would replace the raw copy numbers within the identified segment and was reported thereafter. A segment identified in an individual sample would be declared either a gain or a loss if the score for the segment was larger or smaller than a preselected cutoff value (e.g., 10). The actual segmentation algorithm was a two round algorithm. In the first round, the algorithm identifies segments with unusual large or small test scores (e.g., 5 standard deviations away from the mean), will mark the segment as outliers. The reported scores were actually the output from the second round of segmentation based on the raw copy numbers after removal of the outliers identified from the first round. Table containing t-test scores of identified segmental gains or losses is provided as a supplementary file on the Series record.
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Submission date |
Nov 15, 2010 |
Last update date |
Dec 31, 2010 |
Contact name |
Bin Tean Teh |
Organization name |
Van Andel Institute
|
Department |
Cancer Genetics
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Street address |
330 Bostwick Av
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City |
Grand Rapids |
State/province |
MI |
ZIP/Postal code |
49503 |
Country |
USA |
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Platform ID |
GPL2005 |
Series (1) |
GSE25399 |
Expression of PTTG1 is associated with aggressive clear cell RCC |
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