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Big GIM I

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Guangrong Qin edited this page Dec 8, 2021 · 2 revisions

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Multiomic Provider Tool Description - (include a few sentences describing your tool, a high level explanation what is this tool used for, link to modes of access which will give the metadata about the resource, and a how-to guide for the tools.) See example below.

BigGIM I is KP created/supported/maintained by a Multiomic Provider. Click here to view the Multiomic Provider page.

BigGIM I KGs mainly include co-expression between genes as well as protein-protein interactions from public data resources.

We have updated BigGIM I to BigGIM II by updating the data resources and adding new components.

  • BigGIM II - Gene Gene interaction (expression-based) KG: BigGIM II - Gene Gene interactions (expression-based) is an updated version for BigGIM I with updated datasets from tumor based co-expression or tissue-based gene expression. Update from the tumor-based co-expression: With the updated datasets from TCGA pancan study, we used the new version of gene expression value from the ISB-CGC PanCancer Atlas BigQuery Tables (pancancer-atlas.Filtered.EBpp_AdjustPANCAN_IlluminaHiSeq_RNASeqV2_genExp_filtered) to generate the graph (BigGIM II - Gene Gene interaction (expr-expr)). Gene co-expression correlations were computed using Pearson correlation. Gene expressions with observations in at least 25 samples were taken into consideration. Coefficient and p-value were derived from Pearson correlation analysis.

Update from the normal tissue-based co-expression from the updated datasets from GTEx. Gene TPMs and sample information were downloaded from The GTEx portal (GTEx_Analysis_2017-06-05_v8_RNASeQCv1.1.9_gene_tpm.gct.gz, and GTEx_Analysis_v8_Annotations_SampleAttributesDD.xlsx). Spearman correlation was performed for each gene pair, the result pairs with correlation coefficiency smaller than -0.5 or greater than 0.5 are used as the output to the KGs.

Beyond the update of BigGIM I, the BigGIM II KGs also include the following components:

  • BigGIM II - Drug response (mutation-based):

  • BigGIM II - Drug response (gene expression based):

  • BigGIM II - Disease Gene association (Disease-Gene)

  • Technical User Guide to TIARA - (instructions should allow a reasonably-competent user to make a test query using a specific example, retrieve the results, then create their own query, with tips and common errors described – similar to https://github.com/NCATSTranslator/Relay/wiki/ARS-Query-Process)

  • Modes of Access (provide a link) - Reasoner API v.#.#.#, SmartAPI registry, KGX - formatted Knowledge Graph

    • Link
    • Link
    • Link

  • Guide for user on how to open an issue and find current issues to avoid duplicate issues

  • How to build your own instance for NCATS Deployment pipeline

Use Cases- (Several use cases and detailed curl commands to retrieve the results using the most current Translator standards (eg: TRAPI, biolink, Architecture Principles) (with any that are NOT using these standards marked as such) Please store these use cases in the NCATS Translator Testing Repo and provide a link to the use cases in this wiki page.)

  • Link
  • Link

Knowledge Sources Accessed - (List the knowledge sources that your tools ingest). See example below.

  • BigGIM and BigCLAM
  • Columbia Open Health Data

Source Code - (include links to your source code). See example below

  • Jupyter notebook
  • Code file

External Documentation (List of urls for documentation sites). See example below.

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Knowledge Providers (KP)

Autonomous Relay Agents (ARA)

Autonomous Relay System (ARS)

Standards and Reference Implementation (SRI)

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