ss-validate 0.4.1

GWAS summary statistics file validator

Summary Statistics TSV file Validator

A file validator for validating GWAS summary statistics TSV files prior to and post harmonisation using pandas_schema. The purpose is to validate files before their conversion to HDF5.

Requirements

• python3

Installation

• pip install ss-validate

Running the validator

To run the validator on a file:

• ss-validate -f <file_to_validate.tsv> --logfile <logfile_name>

Information and errors are logged to the console and errors logged to the file specified. A console output might look like:

(INFO): Filename is good!
(INFO): Validating file...
(ERROR): Length of row 7 is: 16 instead of 15
(ERROR): Please fix the table. Some rows have different numbers of columns to the header
(INFO): Rows with different numbers of columns to the header are not validated
(ERROR): {row: 1, column: "p_value"}: "-99" was not in the range [0, 1)

The errors from the output tell us that row seven has too many columns and row one does not have a valid pvalue. If these rows are not fixed, they will later be dropped and not converted to HDF5.

Addional options

• --linelimit : int, default 1000

  Once this number of erroneous rows has been reached, stop looking for more.

• --minrows : int, default 100000

  The minimum number of rows the file is required to have in order to validate sucZZcessfully.

• --drop-bad-lines : bool, default False

  Drops the the lines with errors from the file and writes it to a new file called <file_to_validate.tsv.valid>

• --stage : {'standard', 'harmonised', 'curated'}, default 'standard'

  The stage the file is in. It is either standard format ('standard'), harmonised ('harmonised') or pre-standard in the custom curated format ('curated'). Recommended to leave as default.