Additional content extraction and annotations from pathway figures

[AlexanderPico]

for summarizing query path results during evaluation. For example, annotating pathway figures with terms from the Pathway Ontology will allow BTE users to filter genes by hierarchically-organized pathway classes.

[AlexanderPico]

@ariutta Shall we dive into this one? I was thinking we could add:

1. PMIDs
2. Pathway Ontology terms (IDs and names)
3. Disease Ontology terms (IDs and names)

You have 1 already. We have the start of 3 (from Jensen). And we should brainstorm on 2.

Other ideas?

[AlexanderPico]

@khanspers Why don't you try getting GO:BP terms associated with PFOCR results.

[AlexanderPico]

@ariutta I'll send you a tsv with figid mappings to disease terms. Can you work with kevin to get consensus on the formatting.

[ariutta]

@kevinxin90, we're looking to add more fields (PMID, Pathway Ontology, Disease Ontology) to our data for BTE. What do you think about the format below (the values are just placeholders)? The keys match http://identifiers.org/ prefixes in order to ensure they stay consistent and unique.

{"_id": "PMC0000000__nihm00000000",
 "associatedWith": {
    "figureUrl": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC0000000/bin/nihm00000000.jpg",
    "pmc": "PMC0000000",
    "pubmed": "00000000",
    "ncbigene": ["1000", "1001", "1002", "1003"],
    "PW": ["0000001", "0000002"],
    "DOID": ["10000", "10001"]
  }
}

[kevinxin90]

@ariutta Hi Anders, this looks great to me!!

[AlexanderPico]

@ariutta, Here's a map of figid to doid and human readable terms:
https://www.dropbox.com/s/vgazcxdq4wsl5yk/pfocr_disease_map.tsv?dl=0

@kevinxin90, Should we include both DOID and term name? As a proposed "node property" the human readable term name may be more useful than DOID. But if you already have a mapping for Disease Ontology IDs and terms, then it's perhaps not necessary. Thoughts?

[kevinxin90]

@AlexanderPico Yes. I think it's a good idea to include both DOID and term name in the API response. For Biothing Explorer, it doesn't matter whether you include the name or not (we will do the ID resolving internally). But as an API itself, it would be very useful (in case the user doesn't access it through BioThings Explorer).

[ariutta]

@kevinxin90, in this reporting period, @AlexanderPico and I have done more work to parse our PFOCR data, using APIs like PubTator to extract chemical and disease mentions in the OCR text. Notice that these disease mentions are pulled directly from the OCR text, unlike the disease associations Alex referenced above, which come from pathway enrichment analysis. I'm thinking of the former as disease mentions and the latter as disease annotations.

In order to include this additional information, I propose we use the following updated JSON format, but I'm open to suggestions. We also need to distinguish between mentions vs. annotations somehow, so I set the mentions
as key/value pairs under associatedWith, and the annotations as key/value pairs under associatedWith.annotations.

{
  "_id": "PMC0000000__nihm00000000",
  "associatedWith": {
    "figureUrl": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC0000000/bin/nihm00000000.jpg",
    "pmc": "PMC0000000",
    "pubmed": "00000000",
    "ncbigene": [
      "1000",
      "1001",
      "1002",
      "1003"
    ],
    "disease:mesh": [
      "D000860"
    ],
    "chemical:mesh": [
      "D000431",
      "D000079",
      "D000085"
    ],
    "annotations": {
      "PW": [
        "0000001",
        "0000002"
      ],
      "DOID": [
        "10000",
        "10001"
      ]
    }
  }
}

(dummy data -- just showing the format)

Questions:

1. How do you want to distinguish mentions vs. annotations?
2. The PubTator API returns MESH IDs, so that's why I used MESH IDs for disease:mesh but not DOID. Would it be worth translating to use a single identifier for diseases?
3. Unlike the other identifiers, mesh covers genes, diseases, chemicals, etc. That's why I specified disease:mesh. Do you prefer something else?