Table 1.
Prominent online resources of genomic data.
Table 2.
aCGH data integrated in arrayMap.
Figure 1.
Distribution of resolutions and techniques of GEO platforms.
Each point represents a genomic array. The Y axis is labeled with probe number in log scale. The X axis denotes the time sequence of array data generation. From left to right are years from 2001 to 2011.
Figure 2.
Zoom-in visualization of focal CNA.
(A) GSM535547 (human high grade glioma, Agilent CGH 244A) shows high quality of probe hybridization signal. CNAs are easy to distinguish. (B) When zoom-in the whole chromosome 9, an approximately 80 MB deletion is displayed, with two breakpoints located in p and q arm respectively. In addition, a small regional deletion in 9p21 is quite clear. Color bars in lower region of the panel represent 848 genes located in chromosome 9. (C) Zoom in the potential homozygously deleted region in 9p21 by specifying the exact region: chr9∶21600000-22400000. The zoomed-in plot shows probes, chromosome band and two tumor suppressor genes, MTAP and CDKN2A. Gene name and location will be given while mouse hover. They link to UCSC genome browser with additional information.
Figure 3.
Copy number profiling of glioblastoma.
(A) Chromosomal ideogram and histogram showing frequency of copy number aberrations. Percentage values corresponding to gains (yellow) and losses (blue) identified over the whole dataset. The most frequent imbalances include gain of chromosome 7 and loss of chromosome 10, 9p21.3. (B) Matrix plot of 1478 glioblastoma cases. The Y axis represents individual samples. The distribution of genomic copy number imbalances reveals the individual aberration patterns of glioblastoma. (C) Heatmap of regional CNA frequencies for 1478 arrays. The intensity of green and red color components correlates to the relative gain and loss frequencies, respectively. If dataset contains cancer subtypes, cancers with similar CNA frequency profiles will be clustered together, such that differences between subtypes will be revealed (e.g. see Figure S4H).
Figure 4.
The overall cancer copy number aberration profile consisted of 29137 arrays.
This plot represents 177 cancer types according to ICD-O 3 code. Percentage values in Y axis corresponding to numbers of gains (green) and losses (red) account for the whole dataset.
Figure 5.
The flowchart of arrayMap data collection and analysis procedures.
Publicly available raw data or segmented data was collected from the respective data sources. Files were re-processed by distinct procedures, according to the different data types. Probe coordinates were remapped to the most commonly encountered human reference genome assembly (NCBI Build 36/hg18). All probe specific ratios were converted to log2 values. Thresholds for genomic gain and loss were obtained from the original publications or series annotations; if not available, empirical thresholds were assigned. A minimum of 2 probes was required for calling a CNA segment, with higher values used on high-density arrays and/or in cases of excessive probe level noise. Processed probe and segment information was converted to uniform formats and stored in per-sample text files, which are accessed through the arrayMap web applications.
Table 3.
Percentage of remapped probes according to platform types.