Here we present an example of coGPS analysis.
Exon_exprs_matched |
Expression data for 44 tumors and 25 normals. Each row indicates a gene with row name showing gene name and each column indicates a sample with column name showing sample name. |
Exon_class_matched |
A length 69 vector showing status of corresponding exon samples, 0 for normals and 1 for tumors. |
Methy_exprs_matched |
Methylation data for 44 tumors and 25 normals. |
Methy_class_matched |
A length 69 vector showing status of corresponding methylation samples, 0 for normals and 1 for tumors. |
CNV_exprs_matched |
Copy number data for 44 tumors and 25 normals. |
CNV_class_matched |
A length 69 vector showing status of corresponding copy number samples, 0 for normals and 1 for tumors. |
Hs.gmtl.c1 |
Broad Institute C1 Positional Gene Sets. |
In this application, the columns of each data type are matched. In other words, the first columns of Exon_exprs_matched, Methy_exprs_matched and CNV_exprs_matched correspond to the same patient. And hence the Exon_class_matched, Methy_class_matched and CNV_class_matched are identical. However, suppose in applications that we are not concerned with the outlier gene list for each patient, we can leave with the samples (columns) unmatched.
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