Using MEMo to Discover Mutual Exclusivity Modules in Cancer
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- Abstract
- Table of Contents
- Figures
- Literature Cited
Abstract
Although individual tumors show surprisingly diverse genomic alterations, these events tend to occur in a limited number of pathways, and alterations that affect the same pathway tend to not co?occur in the same patient. While pathway analysis has been a powerful tool in cancer genomics, our knowledge of oncogenic pathway modules is incomplete. To systematically identify such modules, we have developed a novel method, Mutual Exclusivity Modules in Cancer (MEMo). The method searches and identifies modules characterized by three properties: (1) member genes are recurrently altered across a set of tumor samples; (2) member genes are known to or are likely to participate in the same biological process; and (3) alteration events within the modules are mutually exclusive. MEMo integrates multiple data types and maps genomic alterations to biological pathways. MEMo's mutual exclusivity uses a statistical model that preserves the number of alterations per gene and per sample. The MEMo software, source code and sample data sets are available for download at: http://cbio.mskcc.org/memo. Curr. Protoc. Bioinform. 41:8.17.1?8.17.12. © 2013 by John Wiley & Sons, Inc.
Keywords: mutual exclusivity; network modules; cancer genomics
Table of Contents
- Introduction
- Basic Protocol 1: Running MEMo on Template Data
- Basic Protocol 2: Running MEMo Integrating Copy‐Number Alterations and Somatic Mutations
- Basic Protocol 3: Running MEMo with Customized Alterations
- Support Protocol 1: Setting Up MEMo on Linux or MAC OS
- Support Protocol 2: Setting Up MEMo on Windows
- Support Protocol 3: Compile MEMo from Source Code
- Guidelines for Understanding Results
- Commentary
- Literature Cited
- Figures
- Tables
Materials
Figures
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Figure 8.17.1 Example tab‐delimited MEMo report file opened and viewed in a spreadsheet application. View Image
Videos
Literature Cited
| Bell, D., Berchuck, A., Birrer, M., Chien, J., Cramer, D.W., Dao, F., Dhir, R., DiSaia, P., Gabra, H., Glenn, P., et al. 2011. Integrated genomic analyses of ovarian carcinoma. Nature 474:609‐615. | |
| Beroukhim, R., Getz, G., Nghiemphu, L., Barretina, J., Hsueh, T., Linhart, D., Vivanco, I., Lee, J.C., Huang, J.H., Alexander, S., Du, J., Kau, T., Thomas, R.K., Shah, K., Soto, H., Perner, S., Prensner, J., Debiasi, R.M., Demichelis, F., Hatton, C., Rubin, M.A., Garraway, L.A., Nelson, S.F., Liau, L., Mischel, P.S., Cloughesy, T.F., Meyerson, M., Golub, T.A., Lander, E.S., Mellinghoff, I.K., and Sellers, W.R. 2007. Assessing the significance of chromosomal aberrations in cancer: Methodology and application to glioma. Proc. Natl. Acad. Sci. U.S.A. 104:20007‐20012. | |
| Ciriello, G., Cerami, E., Sander, C., and Schultz, N. 2012. Mutual exclusivity analysis identifies oncogenic network modules. Genome Res. 22:398‐406. | |
| Dees, N.D., Zhang, Q., Kandoth, C., Wendl, M.C., Schierding, W., Koboldt, D.C., Mooney, T.B., Callaway, M.B., Dooling, D., Mardis, E.R., Wilson, R.K., and Ding, L. 2012. MuSiC: Identifying mutational significance in cancer genomes. Genome Res. 22:1589‐1598. | |
| Getz, G., Hofling, H., Mesirov, J.P., Golub, T.R., Meyerson, M., Tibshirani, R., and Lander, E.S. 2007. Comment on “The consensus coding sequences of human breast and colorectal cancers”. Science 317:1500. | |
| Taylor, B.S., Barretina, J., Socci, N.D., Decarolis, P., Ladanyi, M., Meyerson, M., Singer, S., and Sander, C. 2008. Functional copy‐number alterations in cancer. PLoS One 3:e3179. | |
| TCGA. 2008. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455:1061‐1068. | |
| TCGA. 2011. Integrated genomic analyses of ovarian carcinoma. Nature 474:609‐615. | |
| TCGA. 2012a. Comprehensive molecular characterization of human colon and rectal cancer. Nature 487:330‐337. | |
| TCGA. 2012b. Comprehensive molecular portraits of human breast tumours. Nature 490:61‐70. | |
| Internet Resources | |
| http://cbio.mskcc.org/memo | |
| MEMo source code, required libraries, and sample data. | |
| http://www.cbioportal.org/public‐portal/ | |
| Constantly updated background networks in simple interaction format (SIF) are available through the cBio Cancer Genomics Portal (Cerami et al., 2012) by clicking on the Networks tab. | |
| https://wiki.nci.nih.gov/display/TCGA/Mutation+Annotation+Format+(MAF)+Specification+‐+v2.2 | |
| Details on the Mutation Annotation Format (MAF). |









