UKBMain

This package aims at providing various command line interfaces to manipulate a UKB main dataset in order to generate phenotypes, confounders, covariates and treatments files. The specification of this process is done via a YAML configuration file for which a base is provided in config/config.yaml.

The associated docker image, hosted on Docker Hub, provides an environment to run all of the commands described below.

The data in a UKB main dataset is organised in fields. The fields themselves may not represent a specific trait but a list of traits organised in array and/or instances (see the Accessing data guide). An example configuration file corresponding to the traits reported by the gene ATLAS is provided in config/config.yaml and if you want to run a generic PheWAS it may simply be used as it is.

This YAML file contains up to 5 main entries:

• phenotypes
• confounders
• covariates
• treatments
• subset

Each entry is further organised as a list of traits of interest. Depending on their data type, the traits can be queried in any of the following ways:

• Continuous and Integer variables: Those can be queried by providing the associated UKB field-id. This can be done either as a single field or list of fields to make the file more readable. The optional "field" keyword can be used. Only the first column (-0.0) of the field, usually corresponding to the first assessment visit, is used.
• Categorical variables: The behavior is different depending on the field and output file:
  • Disease fields 40006, 20002, 41202, 41204: The keyword field must be used. Those variables are encoded by the UKB as lists and will be converted to binary variables indicating the presence/absence of a specific trait. When encoded by ICD10 codes, those traits can be defined either by the exact code or by parent codes or blocks. For instance the code A010 represents Typhoid Fever while the code A01 represents Typhoid and paratyphoid fevers. Further A01-A03 represents either Typhoid and paratyphoid fevers, Other Salmonella infections or Shigellosis. Further definition of aggregated diseases can be defined by the keywords any and name where any is a list of codes and name is the name of the aggregate. Finally, we also provide the ability to consider the union of fields themselves, as long as they are encoded in the same way (for instance 41202, 41204) to define trait with the "FIELD_1 | FIELD_2 | ..." pattern.
  • Other categorical variables: Only the first column (-0.0) is used and will be one hot encoded (except for extra treatments). If no codings are specified, all codes will be extracted, otherwise only those specified will be extracted.
  • Categorical variables for treatments: Values are simply extracted per the given codes (or all codes if none is provided).
• Ordinal variables: Some traits are declared as categorical by the UKB but an ordinal interpretation may be more appropriate. We have identified and hardcoded a list of such traits in the ORDINAL_FIELDS constant.

For further examples, look into the test/config folder.

This is typically used before a call to ukbconv which requires a list of fields of interest in a .txt file.

julia --project --startup-file=no scripts/build_fields_list.jl --conf CONF.yaml --output OUTPUT_FIELDS_PATH

See the man page for ukbconv, but a typical example would be:

./ukbconv ENCRYPTED_UKBMAIN_FILE csv -iOUTPUT_FIELDS_PATH -oUKBMAIN_PATH

where OUTPUT_FIELDS_PATH is the output from the previous command.

julia --project --startup-file=no src/fields_processing.jl UKBMAIN_PATH --conf CONF.yaml --out-prefix OUT_PREFIX --withdrawal-list WITHDRAWAL_LIST

where UKBMAIN_PATH is the output from the previous command.