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Sample GSM240101 Query DataSets for GSM240101
Status Public on Oct 30, 2007
Title OV01-24_pre-treatment
Sample type RNA
Source name biopsy from patient with suspected ovarian cancer
Organism Homo sapiens
Characteristics Responder
Extracted molecule total RNA
Extraction protocol RNA was extracted using RNA-Easy kit from Qiagen according to manufacturer's instructions.
Label biotin
Label protocol Biotinylated cRNA were prepared according to the standard Affymetrix protocol from 1 ug total RNA (Expression Analysis Technical Manual, 2001, Affymetrix). Samples with less than 1 ug quantities were amplified using 10 ng of total RNA.
Hybridization protocol Following fragmentation, 10 ug of cRNA were hybridized for 16 hr at 45C on GeneChip Drosophila Genome Array. GeneChips were washed and stained in the Affymetrix Fluidics Station 400.
Scan protocol GeneChips were scanned using the Hewlett-Packard GeneArray Scanner G2500A.
Description Responder
Data processing All statistical analysis was conducted using the R environment and the R packages affy and affy-PLM. All the raw data tables are included in the accompanying CD in the folder (OV01). We first started by reading the data files into R. > library(affy) > library(affyPLM) > Data <- ReadAffy() > sampleNames(Data) <- c('12a', '14a', '15a', '16a', '19a', '24a2', '27a2', + '28a2', '2a', '33a2', '34a', '38a2', '39a', + '41a', '43a', '44a', '5a2', '7a', '8a', '9a') Normalization Background subtraction and normalization was performed using the method of Li and Wong. This method finds a rank-invariant set of probes across the arrays and uses this for between array normalization. > Data.norm <- expresso(Data, normalize.method='invariantset', + bg.correct=FALSE, pmcorrect.method='pmonly', summary.method='liwong') > Data.norm.values <- exprs(Data.norm) Present and absent calls Affy probes are arranged as 11 pairs of perfect matches and mismatches for each affymetrix ID present on the array. Ideally, a mismatch should yield minimum intensity values. Thus, for a specific hybridization to have occurred, the intensity from the perfect match probes should be “significantly” higher than that from the mismatched probes. Probe level data were used to categorize genes to either present ( p < 0.04), absent ( p > 0.06) or marginal (0.04 ≤ p ≤ 0.06). The mean percentage present calls across all arrays was 51.1% (sd = 8.9%). All the arrays had a percentage present calls of more than 33% of the total number of probe pair sets on an array. > Calls <- mas5calls(Data) > <- exprs(Calls) > Data filtering Data filtering was performed in two stages. First, genes that were either absent or marginal in more than 6 arrays (30% of the arrays) were filtered out. After applying this filtering method only 10,161 genes (out of 22,227) remained for downstream analysis. > <-| > <- apply(, 1, sum) > <- which( > 6) > <- which( <= 6) > eset.AP.retained <- Data.norm.values[,] > length( Second, genes that showed non significant variation in gene expression across arrays were removed according to the method adopted by Simon et al in which only genes that were significantly more variable across arrays than the median variance of all genes were included. This was done by computing the quantity (n − 1) ∗ (Var.i/ ) and comparing it against the chi-square distribution at n − 1 degrees of freedom. After performing this step only 3426 genes were retained for further downstream analysis. > eset.AP.retained.var <- apply(log2(eset.AP.retained), 1, var) > eset.AP.retained.var.quant <- + (ncol(eset.AP.retained)-1)*(eset.AP.retained.var/median(eset.AP.retained.var)) > eset.AP.retained.var.quant.centile <- pchisq(eset.AP.retained.var.quant, + df=ncol(eset.AP.retained)-1) # Genes above the 95th centile (p<0.05) were retained > Var.retain <- which(eset.AP.retained.var.quant.centile > 0.95) > eset.AP.var.retained <- eset.AP.retained[Var.retain,] > dim(eset.AP.var.retained)
Submission date Oct 29, 2007
Last update date Aug 14, 2011
Contact name Ahmed Ashour Ahmed
Organization name Cancer Research UK Cambridge Research Institute
Department Oncology, University of Cambridge
Street address Robinson Way
City Cambridge
ZIP/Postal code CB2 0RE
Country United Kingdom
Platform ID GPL571
Series (1)
GSE9455 Pre-treatment expression data from patients recruited to the paclitaxel arm of the CTCR-OV01 study

Data table header descriptions
VALUE Invariant Set Normalization (Li and Wong)
ABS_CALL the call in an absolute analysis that indicates if the transcript was present (P), absent (A), marginal (M), or no call (NC)

Data table
1007_s_at 189.4095139 P
1053_at 73.1821666 A
117_at 106.3739012 A
121_at 75.44082591 A
1255_g_at 63.73756974 A
1294_at 173.6148856 P
1316_at 124.9085354 P
1320_at 65.872505 A
1405_i_at 80.44037639 P
1431_at 63.01714376 A
1438_at 72.02192318 A
1487_at 78.31593468 A
1494_f_at 70.2727167 P
1598_g_at 585.5744142 P
160020_at 366.0720544 A
1729_at 158.4472607 P
1773_at 61.84643922 A
177_at 107.6236053 P
179_at 119.9037153 A
1861_at 75.04253988 P

Total number of rows: 22277

Table truncated, full table size 540 Kbytes.

Supplementary file Size Download File type/resource
GSM240101.CEL.gz 1.6 Mb (ftp)(http) CEL
Processed data included within Sample table

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