NCI60 is a dataset of gene expression profiles of 60 National Cancer Institute (NCI) cell lines. These 60 human tumour cell lines are derived from patients with leukaemia, melanoma, along with, lung, colon, central nervous system, ovarian, renal, breast and prostate cancers. This panel of cell lines have been subjected to several different DNA microarray studies using both Affymetrix and spotted cDNA array technology. This dataset contains subsets from one cDNA spotted (Ross et al., 2000) and one Affymetrix (Staunton et al., 2001) study, and are pre-processed as described by Culhane et al., 2003.
The format is: List of 3
data.frame containing 144 rows and 60 columns.
144 gene expression log ratio measurements of the NCI60 cell lines.
data.frame containing 144 rows and 60 columns.
144 Affymetrix gene expression average difference measurements of the NCI60 cell lines.
matrix of 60 rows and 2 columns.
The first column contains the names of the 60 cell line which were analysed.
The second column lists the 9 phenotypes of the cell lines, which are
BREAST, CNS, COLON, LEUK, MELAN, NSCLC, OVAR, PROSTATE, RENAL.
matrix of 144 rows and 4 columns.
The 144 rows contain the 144 genes in the \$Ross and \$Affy datasets, together with their
Unigene IDs, and HUGO Gene Symbols. The Gene Symbols obtained for the \$Ross and \$Affy datasets differed
(see note below), hence both are given. The columns of the
matrix are the IMAGE ID of the clones of the \$Ross dataset, the HUGO Gene Symbols of these IMAGE clone ID obtained from SOURCE, the Affymetrix ID of the \$Affy dataset, and the HUGO Gene Symbols of these Affymetrix IDs obtained using
The datasets were processed as described by Culhane et al., 2003.
data.frame contains gene expression profiles of each cell lines in the NCI-60 panel,
which were determined using spotted cDNA arrays containing 9,703 human cDNAs (Ross et al., 2000).
The data were downloaded from The NCI Genomics and Bioinformatics Group Datasets resource
http://discover.nci.nih.gov/datasetsNature2000.jsp. The updated version of this dataset
(updated 12/19/01) was retrieved. Data were provided as log ratio values.
In this study, rows (genes) with greater than 15 and were removed from analysis, reducing the dataset to 5643 spot values per cell line. Remaining missing values were imputed using a K nearest neighbour method, with 16 neighbours and a Euclidean distance metric (Troyanskaya et al., 2001). The dataset \$Ross contains a subset of the 144 genes of the 1375 genes set described by Scherf et al., 2000. This datasets is available for download from http://bioinf.ucd.ie/people/aedin/R/.
In order to reduce the size of the example datasets, the Unigene ID's for each of the 1375 IMAGE ID's for these genes were obtained using SOURCE http://source.stanford.edu. These were compared with the Unigene ID's of the 1517 gene subset of the \$Affy dataset. 144 genes were common between the two datasets and these are contained in \$Ross.
The Affy data were derived using high density Hu6800 Affymetrix microarrays containing 7129 probe sets (Staunton et al., 2001). The dataset was downloaded from the Whitehead Institute Cancer Genomics supplemental data to the paper from Staunton et al., http://www-genome.wi.mit.edu/mpr/NCI60/, where the data were provided as average difference (perfect match-mismatch) values. As described by Staunton et al., an expression value of 100 units was assigned to all average difference values less than 100. Genes whose expression was invariant across all 60 cell lines were not considered, reducing the dataset to 4515 probe sets. This dataset NCI60\$Affy of 1517 probe set, contains genes in which the minimum change in gene expression across all 60 cell lines was greater than 500 average difference units. Data were logged (base 2) and median centred. This datasets is available for download from http://bioinf.ucd.ie/people/aedin/R/.
In order to reduce the size of the example datasets, the Unigene ID's for each of the 1517 Affymetrix ID of these genes were obtained using the function
aafUniGene in the
annaffy Bioconductor package. These 1517 Unigene IDs were compared with the Unigene ID's of the 1375 gene subset of the \$Ross dataset. 144 genes were common between the two datasets and these are contained in \$Affy.
These pre-processed datasets were available as a supplement to the paper:
Culhane AC, Perriere G, Higgins DG. Cross-platform comparison and visualisation of gene expression data using co-inertia analysis. BMC Bioinformatics. 2003 Nov 21;4(1):59. http://www.biomedcentral.com/1471-2105/4/59
Culhane AC, Perriere G, Higgins DG. Cross-platform comparison and visualisation of gene expression data using co-inertia analysis. BMC Bioinformatics. 2003 Nov 21;4(1):59.
Ross DT, Scherf U, Eisen MB, Perou CM, Rees C, Spellman P, Iyer V, Jeffrey SS, Van de Rijn M, Waltham M, Pergamenschikov A, Lee JC, Lashkari D, Shalon D, Myers TG, Weinstein JN, Botstein D, Brown PO: Systematic variation in gene expression patterns in human cancer cell lines. Nat Genet 2000, 24:227-235
Scherf U, Ross DT, Waltham M, Smith LH, Lee JK, Tanabe L, Kohn KW, Reinhold WC, Myers TG, Andrews DT, Scudiero DA, Eisen MB, Sausville EA, Pommier Y, Botstein D, Brown PO, Weinstein JN: A gene expression database for the molecular pharmacology of cancer.Nat Genet 2000, 24:236-244.
Staunton JE, Slonim DK, Coller HA, Tamayo P, Angelo MJ, Park J, Scherf U, Lee JK, Reinhold WO, Weinstein JN, Mesirov JP, Lander ES, Golub TR: Chemosensitivity prediction by transcriptional profiling. Proc Natl Acad Sci U S A 2001, 98:10787-10792.
Troyanskaya O, Cantor M, Sherlock G, Brown P, Hastie T, Tibshirani R, Botstein D, Altman RB: Missing value estimation methods for DNA microarrays. Bioinformatics 2001, 17:520-525.
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