Multiple Myeloma Genomics Portal (MMGP)
The Multiple Myeloma Genomics Portal is a part of the Multiple Myeloma Genomics Initiative, a collaboration of The Multiple Myeloma Research Consortium, The Broad Institute of MIT and Harvard, and the Translational Genomics Research Institute (TGen). Funding is provided by the Multiple Myeloma Research Foundation. Development of the portal and data curation was performed by the portal team of the Broad Institute and Dana Farber Cancer Center.
The Multiple Myeloma Genomics Portal (MMGP) has been made available to provide access to and limited analysis of the MMGP portal data sets. These include the MMRC funded reference aCGH and gene expression data and additional public multiple myeloma datasets.
The MMGP will be updated with new features such as additional data and analysis tools as they become available.
News / Events
Jun 3, 2014: The MMGP will be unavailable from 10AM through 1PM EST Friday June 6th for maintenance.
Mar 13, 2014: Survival data (updated yearly) for the patients in the MMRC reference collection is now available upon request. Please contact us if you would like to have access.
Jan 28, 2014: We have investigated the mutational spectrum and copy number profile of 203 patients with MM and other plasma cell dyscrasias, by whole genome sequencing, whole exome sequencing and high density SNP array profiling. We have determined the mutations that are most likely â??driverâ?? events, and we have determined the cancer cell fraction in which these mutations occur. For a complete listing of the available data and analyses performed, please refer to Widespread Genetic Heterogeneity in Multiple Myeloma: Implications for Targeted Therapy
Sep 24, 2013: The MMGP can now upload data directly to GenomeSpace. To learn more, see the GenomeSpace blog
Sep 18, 2013: The portal will be unavailable from Thursday October 17 through Sunday October 20th for server maintenance.
Sep 16, 2013: 5 additional publications have been added to the curated list of significant Multiple Myeloma publications
Aug 7, 2013: We have added 15 additional publications to the curated list of significant Multiple Myeloma publications
Please register for full access to the data and analyses tools MMGP provides.
Terms of Access Register
Tutorials / Manuals
Tutorials, analysis descriptions and other documentation is available at:
HELP > DOCUMENTS
Frequently Altered Genes
clouds summarizing genes frequently altered in the datasets of this
portal are available in the
Mutation tag cloud
Prognostic value of deep sequencing method for minimal residual disease detection in multiple, Martinez-Lopez J et al., Blood, 2014
Association of response endpoints with survival outcomes in multiple myeloma, Lonial S et al., Leukemia, 2014
Mutation of NRAS but not KRAS significantly reduces myeloma sensitivity to single-agent bortezomib, George Mulligan et al., Blood, 2014
The Cancer Therapeutic Response Portal provides profiles of the impact of a small-molecule collection of 185 compounds on a panel of 242 cancer cell lines
The Cancer Cell Line Encyclopedia provides public access to genomic data, analysis and visualization for about 1000 cell lines.
What you can do on this portal
Search for information
Enter a keyword to search for genes, news items and publications. Search
results for a gene include links to annotations and analyses.
Browse, analyze and download
studies and data sets.
BROWSE > DATA
The portal provides the
following analysis tools:
Integrative Genomics Viewer (IGV)
Visualize a data set in the Integrative Genomics Viewer (IGV), a high-performance
visualization tool for interactive exploration of large integrated data sets.
Differential Expression Analysis
Find genes that are significantly differentially expressed between two user-defined classes
of samples from an expression data set available on this portal.
View the top 20 genes in a data set that are co-expressed with a gene of interest.
Gene Set Enrichment Analysis (GSEA)
Find pathway gene sets correlated with a gene of interest. Domain
experts curate the pathway gene sets based on data from several online pathway databases.
Create your own sample sets based on a
large number of available criteria and use them in differential expression analysis.
CREATE SAMPLE SETS