Molecular Oncology Almanac is a clinical interpretation algorithm for cancer genomics to annotate and evaluate whole-exome and transcriptome genomic data from individual patient samples. Specifically, Molecular Oncology Almanac can:
- Identify mutations and genomic features related to therapeutic sensitivity and resistance and of prognostic relevance.
- Annotate somatic and germline variants based on their presence in several datasources.
- Sort and evaluate somatic mutations from single nucleotide variants, insertions and deletions, copy number alterations, and fusions based on clinical and biological relevance.
- Integrate data types to observe which genes have been altered in both the somatic and germline setting.
- Extract and evaluate germline mutations relevant to adult and hereditary cancers.
- Identify overlap between somatic variants observed from both DNA and RNA, or any other source of validation sequencing.
- Identify somatic and germline variants that may be related to microsatellite stability.
- Calculate coding mutational burden and compare your patient to TCGA.
- Calculate contribution of known COSMIC mutational signatures with deconstructsigs.
- Identify genomic features that may be related to one another.
- Create portable web-based actionability reports, summarizing clinically relevant findings.
The codebase is available for download through this Github repository, Dockerhub, and Terra. The method can also be run on FireCloud, without having to use FireCloud, by using our portal. Accessing Molecular Oncology Almanac through Github will require building some of the datasources but they also contained in the Docker container.
Molecular Oncology Almanac is a Python application using Python 3.6 but also utilizes R to run deconstructSigs as a subprocess. This application, datasources, and all dependencies are packaged on Docker and can be downloaded with the command
docker pull vanallenlab/moalmanacAlternatively, the package can be built from this Github repository. To download via Github,
git clone https://github.com/vanallenlab/moalmanac.gitWe recommend using a virtual environment and running Python with either Anaconda or Miniconda. After installing Anaconda or Miniconda, you can set up by running
conda create -n moalmanac python=3.6 -y
source activate moalmanac
pip install -r requirements.txtYou can install deconstructSigs after installing R with the following commands
Rscript -e 'install.packages("RCurl", repos = "http://cran.rstudio.com/")' \
&& Rscript -e 'source("http://bioconductor.org/biocLite.R"); biocLite("BSgenome"); biocLite("BSgenome.Hsapiens.UCSC.hg19"); biocLite("GenomeInfoDb")' \
&& Rscript -e 'install.packages("reshape2", repos = "http://cran.rstudio.com/")' \
&& Rscript -e 'install.packages("deconstructSigs", repos = "http://cran.rstudio.com/")'Molecular Oncology Almanac will run based on any combination of input data but does require a few inputs: patient_id, config.ini, and colnames.ini.
Required arguments:
--patient_id <string> patient identifier
--config_ini <string> configuration file, default=config.ini
--colnames_ini <string> configuration file for input column names and strings, default=colnames.ini
Optional arguments:
--tumor_type <string> tumor ontology, default=Unknown
--stage <string> tumor stage, default=Unknown
--snv_handle <string> handle for MAF file of somatic single nucleotide variants
--indel_handle <string> handle for MAF file of somatic insertions and deletions
--bases_covered_handle <string> handle for text file which contains the number of calcable somatic bases
--cnv_handle <string> handle for annotated seg file for somatic copy number
--fusion_handle <string> handle for STAR fusion output, .final.abridged
--germline_handle <string> handle for MAF file of germline single nucleotide variants and insertions and deletions
--validation_handle <string> handle for MAF file of somatic single nucleotide variant called from validation sequencing
--ms_status <string> microsatellite status as deemed by MSI sensor, MSI or MSS, default=Unknown
--purity <float> tumor purity
--ploidy <float> tumor ploidy
--wgd <boolean> specify the occurence of whole genome duplication
--disable_matchmaking <boolean> remove patient-to-cell line matchmaking from report
--description <string> description of patient
A file run_example.py was packaged with this application to run Molecular Oncology Almanac on data found in the folder example_data. The outputs produced are the same as those hosted in the folder example_output. From the application's folder, run
python run_example.pyIf you find this tool or any code herein useful, please cite:
DIAGNOSTIC AND CLINICAL USE PROHIBITED. DANA-FARBER CANCER INSTITUTE (DFCI) and THE BROAD INSTITUTE (Broad) MAKE NO REPRESENTATIONS OR WARRANTIES OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING, WITHOUT LIMITATION, WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, NONINFRINGEMENT OR VALIDITY OF ANY INTELLECTUAL PROPERTY RIGHTS OR CLAIMS, WHETHER ISSUED OR PENDING, AND THE ABSENCE OF LATENT OR OTHER DEFECTS, WHETHER OR NOT DISCOVERABLE.
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