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Zodiac Software Package for Retrieving and Processing TCGA Data

TCGA-Assembler is an open-source tool that can automatically retrieve and process public TCGA data, including mRNA-seq data, miRNA-seq data, protein expression data, DNA methylation data, DNA copy number data, and patient clinical information. TCGA-Assembler is freely available here.

 

Zodiac Software Package for Bayesian Graphical Model (BGM) Analysis

We provide here the software for doing BGM analyses in Zodiac. The software was written in R (freely available at http://www.r-project.org/) with its core computation modules written in C to speed up analyses. Currently, the software package works on Linux, Windows, and Mac OS. A ReadMe document is provided with the software package to guide users in applying BGM on their own data.

 

Multi-modal TCGA Data Used for Inferring Cancer Genomic Interactions in Zodiac

Click here to download the multi-modal TCGA data used for Zodiac analysis. The data were retrieved from TCGA Data Coordinating Center in April, 2013 using TCGA-Assembler, and then processed as described in the Supplementary Information Section 2.1 "Data Preparation" of the Zodiac paper. The data are in a tab-delimited column table. The first column gives gene symbol. The second column is the description of feature. And the other columns are data. The first row gives the TCGA sample barcodes that include the patient IDs and tissue type codes. In the feature description column, "||" is used as a separator, and for different types of features, the description provides different information. Take gene ACACB as an example. Description "CN||CHR12||+" indicates that the feature is Copy Number (CN) and that the gene is on the plus strand of chromosome 12. Description "GE||32" indicates that the feature is Gene Expression (GE) and the NCBI ID of the gene is 32. Description "Me" indicates that the feature is DNA methylation. Description "PE||ACC_pS79-R-V" indicates that the feature is Protein Expression (PE) and ACC_pS79-R-V is the antibody used for measuring the protein expression level.