peanof - PaEdiatric ANthropometric measurement Outlier Flagging pipeline

Automated data cleaning of paediatric anthropometric data from longitudinal electronic health records: protocol and application to a large patient cohort

Hang T.T. Phan, Florina Borca, David Cable, James Batchelor, Justin H. Davies, Sarah Ennis University of Southampton, Southampton, UK

Dependencies for direct use of the peanof.py script

The pipeline requires Python 3.7 and the following packages to run.

1. ggplot
2. sklearn
3. statsmodels
4. matplotlib

Usages

Usage: python peanof.py [options] 

Options:
  --version             show program's version number and exit
  -h, --help            show this help message and exit
  -r REFG, --refg=REFG  Growth reference table used for calculating SDS values
                    from age, gender and measurement
  -n SDS, --number=SDS   0: calculate SDS values only for one individual,
                        require age or dob, measuredates, and measurements
                        1: outlier flagging for the whole input file, require
                        input file with ID, DOB, GENDER, AGE, MEASURE DATE,
                        MEASURE TYPE and MEASURE VALUE. If no AGE information
                        is available, both MEASURE DATE and DOB must be
                        present. These are required to calculate SDS values.
                        If --ids (-i) is set to a list of IDs then would only
                        process the specified IDs in the dataset
  -f FN, --fn=FN        Name of file containing height and weight measurements
                        with age and gender, can be xlsx file or csv file, and
                        the columns must be in order of ID, DOB, GENDER, AGE,
                        MEASURE DATE, MEASURE TYPE, MEASURE VALUE
  -o FON, --fon=FON     Name of output file
  -i IDS, --ids=IDS     List of IDs of individuals to process, comma separated
                        list, if no setting, the program will process all
  -p PREFIX, --prefix=PREFIX
                        Prefix of output images for --ids option in processing
                        a limited number of children
  -a AGE, --age=AGE     Age at measurement. Can have multiple age value
                        separated by comma
  -m MEASUREMENT, --measurement=MEASUREMENT
                        Measured value. Can have multiple measurement
                        separated by comma
  -t MEASURETYPE, --measureType=MEASURETYPE
                        Type of measurement, WEIGHT in kg or HEIGHT in cm,
                        default is WEIGHT
  -g GENDER, --gender=GENDER
                        Gender (M for Male and F for Female)
  -d DOB, --dob=DOB     Date of birth of the child (dd/mm/yyyy)
  -e DOM, --dom=DOM     Date of measurement of the child (dd/mm/yyyy), can
                        have multiple date of measurements separated by comma

Example use cases

1. Calculating SDS values for height or weight measurements

'python3 peanof.py -n 0 -d 1/01/2010 -e 12/3/2020,11/11/2019 -m 139,130 -g M -t HEIGHT -o testNow.png'

2. Outlier flagging of height/weight measurements for a few individuals from a big input file

The following will produce flagging results as well as the growth charts of 'Child1' and 'Child2' in the 'testData' folder

'python3 peanof.py -n 1 -f testData/test.csv -i Child1,Child2 -o testOut.csv -p testData/test'

3. Outlier flagging of height/weight measurments for the whole dataset

'python3 peanof.py -n 1 -f testData/test.csv -o testOut.csv'

or simply

'python3 peanof.py -n 1 -f testData/test.csv'

Docker usage

1. Docker image build or pull

First download the Dockerfile to a folder of where you plan to build the docker image, then run the command:

'docker build -t peanof:1.0 .'

Or you can pull the peanof image from the public Docker repository 'docker pull peanof:1.0'

2. Running pipeline using docker image

a. Calculating SDS values input directly from commandline

docker run --rm  \
  --name devtest \
  --mount source=`pwd`/testData,target=/data,type=bind \
  peanof:1.0 peanof.py -n 0 -d 1/01/2010 -e 12/3/2020,11/11/2019 -m 139,130 -g M -t HEIGHT   -o testNow.png

b. Running outlier flagging pipeline for an xlsx or csv inputfile containing height and weight measurements

docker run --rm \
  --name devtest \
  --mount source=`pwd`/testData,target=/data,type=bind \
  peanof:1.0 peanof.py -n 1 -f test.csv