What RDoQ Does

RDoQ is a program that acts as a front-end to NCBI databases. As input it takes two sets of "terms", which are text lines having one of the two formats
NCBI Query
concept phrase : NCBI Query
and analyze them in a table of associations.

For example, we could find associations between people and genes. Our first set of terms should then be queries about people:
#  Project Direction
Bob Bilder:                 Bilder Robert  [FAU]  OR  Bilder R   [AU]  # Director of CNP
Roberto Peccei:             Peccei Roberto [FAU]  OR  Peccei R   [AU]
Leonard Rome:               Rome Leonard   [FAU]  OR  Rome LH    [AU]
Fred Sabb:                  Sabb Fred      [FAU]  OR  Sabb FW    [AU]

#  Cognitive Neuroscience
Carrie Bearden:             Bearden Carrie [FAU]  OR  Bearden CE [AU]
Bob Bilder:                 Bilder Robert  [FAU]  OR  Bilder R   [AU]
Ty Cannon:                  Cannon Tyrone  [FAU]  OR  Cannon TD  [AU]
Pound signs (#) and everything after them are ignored, permitting comments about the queries.

PubMed permits use of many search field 'tags' like '[AU]' indicating that the text preceding the tag is to be interpreted as a specific kind of information, and used as a search key in the corresponding NCBI index. In this example, the [AU] Author name tag indicates that the preceding text is a name (a last name followed by initials). The [FAU] Full Author name tag is used whenever full names are used instead of initials.

The second set of terms should be queries about gene identifiers, like these:
DAT1:       "DAT1" [TIAB] OR "DAT-1" [TIAB]
DRD2:       "DRD2" [TIAB] OR "DRD-2" [TIAB] OR ("D2" [TIAB] AND "dopamine receptor" [TIAB])
DRD4:       "DRD4" [TIAB] OR "DRD-4" [TIAB] OR ("D4" [TIAB] AND "dopamine receptor" [TIAB])
DRD5:       "DRD5" [TIAB] OR ("D5" [TIAB] AND "dopamine receptor" [TIAB])
SNAP2:      "SNAP2" [TIAB] OR "SNAP-25" [TIAB]
RDoQ takes these two sets of terms and evaluates all NCBI associations between the first set (people) and the second (genes), and yields a table like the following:


RDoQ also has a number of predefined term sets — vocabularies of typically about 100 terms that can be used as "shotgun" association finders. The table above can be generated easily by just using the predefined sets for CNP people and CNP genes, with an input screen like this:

For more information see the RDoQ Tutorial.

The RDoQ Gallery also has examples that show what RDoQ can do.

Familiarity with NCBI databases (and eUtils) can help you succeed with RDoQ. There is an extensive online tutorial/reference/help system for PubMed. The RDoQ query page has links to information about important features. This knowledge is important; being aware of how queries are interpreted enables you to find associations (and relevant publications) that otherwise might be missed. Spending 10 minutes looking through this may end up saving you hours of search.

Awareness of MeSH, the Medical Subject Heading "ontology" is also important. MeSH is a kind of keyword index, or set of indexing terms or topics.


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