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Functionality demonstrated in this vignette benefited greatly from code originally written by hhunterzinck.
This describes how to package some Synapse processed data as a cBioPortal study dataset. A cBioPortal study contains one or more data types, see cBioPortal docs. The current API covers creating a cBioPortal study with a subset of data types relevant to the NF workflow (so not all data types). The design has been inspired by and should feel somewhat like working with the R package usethis, and data types can be added to the study package interactively.
Though there is some checking depending on the data type, final validation with the official cBioPortal validation tools/scripts should still be run.
Breaking changes are possible as the API is still in development.
First load the nfportalutils
package and log in.
The recommended default usage of syn_login
is to use it without directly passing in credentials.
Instead, have available the SYNAPSE_AUTH_TOKEN
environment variable with your token stored therein.
library(nfportalutils) syn_login()
First create the study dataset "package" where we can put together the data. Each study dataset combines multiple data types -- clinical, gene expression, gene variants, etc.
cbp_new_study(cancer_study_identifier = "npst_nfosi_ntap_2022", name = "Plexiform Neurofibroma and Neurofibroma (Pratilas 2022)", citation = "TBD")
Data types can be most easily added in any order using the cbp_add*
functions.
These functions download data files and create the meta for them.
Note that:
make_meta_*
or edit the files manually after.maf_data
references a final merged maf output file from the NF-OSI processing pipeline OK for public release. maf_data <- "syn36553188" add_cbp_maf(maf_data)
cna_data
is expected to be a .seg
file on Synapse.cna_data <- "syn********" cbp_add_cna(cna_data)
expression_data
is expected to be a .txt
called gene_tpm.tsv
file on Synapse.gene_counts.tsv
, but this can be omitted.mrna_data <- "syn********" mrna_data_raw <- "syn********" cbp_add_expression(mrna_data, expression_data_raw = mrna_data_raw)
clinical_data
is a prepared clinical data table already subsetted to those released in this study, or pass in a query that can be used for subsetting if using a full clinical database table. For example, the full clinical cohort comprises patients 1-50, but this study dataset consists of available and releasable data only for patients 1-20 for expression data and data patients 15-20 for cna data. Here, clinical_data
can be a smaller table of just those 1-30, or it can be the original table but pass in a suitable additional filter, e.g. where release = 'batch1'
.ref_map
defines the mapping of clinical variables from the NF-OSI data dictionary to cBioPortal's. Only variables in the mapping are exported to cBioPortal. Follow link below to inspect the default file and format used.clinical_data <- "select * from syn43278088" ref_map <- "https://raw.githubusercontent.com/nf-osi/nf-metadata-dictionary/main/mappings/cBioPortal.yaml" cbp_add_clinical(clinical_data, ref_map)
There are additional steps such as generating case lists and validation that have to be done outside of the package with a cBioPortal backend, where each portal may have specific configurations (such as genomic reference) to validate against. See the general docs for dataset validation.
For the public portal, the suggested step using the public server is given below.
Assuming your present working directory is ~/datahub/public
and a study folder called npst_nfosi_ntap_2022
has been placed into it, mount the dataset into the container and run validation like:
STUDY=npst_nfosi_ntap_2022 sudo docker run --rm -v $(pwd):/datahub cbioportal/cbioportal:5.4.7 validateStudies.py -d /datahub -l $STUDY -u http://cbioportal.org -html /datahub/$STUDY/html_report
The html report will list issues by data types to help with any corrections needed.
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