Proposed Analysis: Create an API for annotating long-format tables generated by analysis modules

[logstar]

What are the scientific goals of the analysis?

Create an R function and an R script API for adding gene and cancer_group annotations to the long-format tables that are generated by analysis modules. The module developers could incorporate the function or in their modules via either source('path/to/the/function') or Rscript --vanilla path/to/the/script long.tsv long_annotated.tsv.

This module is suggested by @jharenza and @kgaonkar6 in Slack at https://opentargetspediatrics.slack.com/archives/C021Z53SK98/p1626290031138100?thread_ts=1626287625.133600&cid=C021Z53SK98, in order to alleviate the burdens of analysis module developers for adding annotations and keeping track of what annotations need to be added. This module could also potentially handle large file storage issues at a later point, since the file size limit of GitHub is 100MB.

The gene annotations to be added:

Annotation column name	Source data
RMTL	data/ensg-hugo-rmtl-v1-mapping.tsv
Gene_type	analyses/fusion_filtering/references/genelistreference.txt
OncoKB_cancer_gene	analyses/snv-frequencies/input/oncokb_cancer_gene_list.tsv
OncoKB_oncogene_TSG	analyses/snv-frequencies/input/oncokb_cancer_gene_list.tsv
Gene_full_name	TBD. Download from https://mygene.info/ to this module.
Protein_RefSeq_ID	TBD. Download from https://mygene.info/ to this module.

Update Fri Jul 16 2021 by @logstar : Add Protein_RefSeq_ID to gene annotations.

Note: only add Gene_type to gene-level tables.

The disease annotations to be added:

Annotation column name	Source data
EFO	data/efo-mondo-map.tsv
MONDO	data/efo-mondo-map.tsv

The tables that could be annotated by the script:

Analysis module	Table path	GitHub PR
snv-frequencies	analyses/snv-frequencies/results/gene-level-snv-consensus-annotated-mut-freq.tsv analyses/snv-frequencies/results/var-level-snv-consensus-annotated-mut-freq.tsv	Open PR: d3b-center/OpenPedCan-analysis#45
rna-seq-expression-summary-stats	analyses/rna-seq-expression-summary-stats/results/long_n_tpm_mean_sd_quantile_gene_wise_zscore.tsv.gz analyses/rna-seq-expression-summary-stats/results/long_n_tpm_mean_sd_quantile_group_wise_zscore.tsv.gz	Merged PR: d3b-center/OpenPedCan-analysis#27
fusion-frequencies	analyses/fusion-frequencies/results/putative-oncogene-fusion-freq.tsv analyses/fusion-frequencies/results/putative-oncogene-fused-gene-freq.tsv	Open PR: d3b-center/OpenPedCan-analysis#49
cnv-frequencies	analyses/cnv-frequencies/results/cnv-consensus-annotated-autosomes-frequencies.tsv.gz analyses/cnv-frequencies/results/cnv-consensus-annotated-frequencies-x_and_y.tsv.gz	Open PR: d3b-center/OpenPedCan-analysis#52
tumor-gtex-plots	TBD (?)	Open PR: d3b-center/OpenPedCan-analysis#29
DESeq_analysis	TBD (?)	Open PR: d3b-center/OpenPedCan-analysis#28

What methods do you plan to use to accomplish the scientific goals?

Check all long-format TSV tables have the following columns:

Column name	Description
Gene_symbol	HUGO symbols, e.g. PHLPP1, TM6SF1, and DNAH5.
Gene_Ensembl_ID	Ensembl ENSG IDs without .# versions, e.g. ENSG00000039139, ENSG00000111261, and ENSG00000169710
Disease	The cancer_group in the histologies.tsv, e.g. Adamantinomatous Craniopharyngioma, Atypical Teratoid Rhabdoid Tumor, and Low-grade glioma/astrocytoma

Annotate the aforementioned annotation columns with their corresponding source data.

What input data are required for this analysis?

• data/ensg-hugo-rmtl-v1-mapping.tsv
• analyses/fusion_filtering/references/genelistreference.txt
• analyses/snv-frequencies/input/oncokb_cancer_gene_list.tsv
• data/efo-mondo-map.tsv

How long do you expect is needed to complete the analysis? Will it be a multi-step analysis?

2-4 days.

Who will complete the analysis (please add a GitHub handle here if relevant)?

@logstar

What relevant scientific literature relates to this analysis?

OncoKB papers: https://ascopubs.org/doi/full/10.1200/PO.17.00011 and https://science.sciencemag.org/content/339/6127/1546.full.

Gene_type sources https://github.com/d3b-center/annoFuse#prerequisites-for-cohort-level-analysis.

Notes

@kgaonkar6 @ewafula @sangeetashukla @komalsrathi @jharenza Let me know if you have any suggestions on this module.

[jharenza]

Great description @logstar! We will also want to add Uberon codes for Gtex tissues, as will be released in v7, per issue #85

[logstar]

Great description @logstar! We will also want to add Uberon codes for Gtex tissues, as will be released in v7, per issue #85

Thank you for the note!

[logstar]

All relevant PRs merged.