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Pheno-Ranker-0.00_3
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NAME

pheno-ranker: A script that performs semantic similarity in PXF/BFF data structures and beyond (JSON|YAML)

SYNOPSIS

pheno-ranker -r <individuals.json> -t <patient.json> [-options]

Arguments:                       
* Cohort mode:
  -r|reference                   BFF/PXF file(s) (JSON|YAML array or object)

* Patient mode:
  -t|target                      BFF/PXF file (JSON|YAML object or array of 1 object)

Options:
  -age                           Include age-related variables [>no-age|age]
  -a|align                       Write alignment file(s). If no argument is given the files will be named [alignment.*]
  -append-prefixes               The prefixes to be added to the primary_key of individuals when #cohorts >= 2 [C]
  -config                        YAML config file to change default parameters [share/conf/config.yaml)
  -e|export                      Export miscellanea JSON files. If no argument is given the files will be named [export.*]
  -exclude-terms                 Exclude BFF/PXF terms (e.g., --exclude-terms sex id)
  -include-hpo-ascendants        Include ascendant terms from the Human Phenotype Ontology (HPO)
  -include-terms                 Include BFF/PXF terms (e.g., --ixclude-terms diseases)
  -max-number-var                Maximum number of variables to be used in binary string [10000]
  -max-out                       Print only N of comparisons (used with --t)  [50]
  -o|out-file                    Output file path [-r matrix.txt|-t rank.txt]
  -poi|patients-of-interest      Export JSON files for the selected individual ids (dry-run)
  -poi-out-dir                   Directory where to write JSON files (to be used with --poi)
  -sort-by                       Sort reference-patient comparison by Hamming-distance or Jaccard-index [>hamming|jaccard]
  -w|weights                     YAML file with weights

Generic Options:
  -debug                         Print debugging (from 1 to 5, being 5 max)
  -h|help                        Brief help message
  -log                           Save log file (JSON). If no argument is given then the log is named [pheno-ranker-log.json]
  -man                           Full documentation
  -no-color                      Don't print colors to STDOUT [>color|no-color]
  -v|verbose                     Verbosity on
  -V|version                     Print version

DESCRIPTION

pheno-ranker: A script that performs semantic similarity in PXF/BFF data structures and beyond (JSON|YAML)

SUMMARY

Pheno-Ranker is a lightweight and easily to install tool specifically designed for performing semantic similarity analysis on phenotypic data structured in JSON format, such as Beacon v2 Models or Phenopackets v2.

INSTALLATION

Containerized

Method 1: From Docker Hub

Download a docker image (latest version - amd64|x86-64) from Docker Hub by executing:

docker pull manuelrueda/pheno-ranker:latest
docker image tag manuelrueda/pheno-ranker:latest cnag/pheno-ranker:latest

See additional instructions below.

Method 2: With Dockerfile

Please download the Dockerfile from the repo:

wget https://raw.githubusercontent.com/cnag-biomedical-informatics/pheno-ranker/main/Dockerfile

And then run:

docker build -t cnag/pheno-ranker:latest .

Additional instructions for Methods 1 and 2

To run the container (detached) execute:

docker run -tid -e USERNAME=root --name pheno-ranker cnag/pheno-ranker:latest

To enter:

docker exec -ti pheno-ranker bash

The command-line executable can be found at:

/usr/share/pheno-ranker/bin/pheno-ranker

The default container user is root but you can also run the container as $UID=1000 (dockeruser).

 docker run --user 1000 -tid --name pheno-ranker cnag/pheno-ranker:latest

Mounting volumes

Docker containers are fully isolated. If you need the mount a volume to the container please use the following syntax (-v host:container). Find an example below (note that you need to change the paths to match yours):

docker run -tid --volume /media/mrueda/4TBT/data:/data --name pheno-ranker-mount cnag/pheno-ranker:latest

Then I will do something like this:

# First I create an alias to simplify invocation (from the host)
alias pheno-ranker='docker exec -ti pheno-ranker-mount /usr/share/pheno-ranker/bin/pheno-ranker'

# Now I use the alias to run the command (note that I use the flag --o to specify the filepath)
pheno-ranker -r /data/individuals.json -o /data/matrix.txt

Non containerized

The script runs on command-line Linux and it has been tested on Debian/RedHat/MacOS based distributions (only showing commands for Debian's). Perl 5 is installed by default on Linux, but we will install a few CPAN modules with cpanminus.

From Github

git clone https://github.com/cnag-biomedical-informatics/pheno-ranker.git
cd pheno-ranker

Install system level dependencies:

sudo apt-get install cpanminus libperl-dev

Now you have two choose between one of the 3 options below:

Option 1: Install dependencies (they're harmless to your system) as sudo:

cpanm --notest --sudo --installdeps .
bin/pheno-ranker --help

Option 2: Install the dependencies at ~/perl5:

cpanm --local-lib=~/perl5 local::lib && eval $(perl -I ~/perl5/lib/perl5/ -Mlocal::lib)
cpanm --notest --installdeps .
bin/pheno-ranker --help

Option 3: Install the dependencies in a "virtual environment" (at local/) . We'll be using the module Carton for that:

mkdir local
cpanm --notest --local-lib=local/ Carton
export PATH=$PATH:local/bin; export PERL5LIB=$(pwd)/local/lib/perl5:$PERL5LIB
carton install
carton exec -- bin/pheno-ranker -help

From CPAN

First install system level dependencies:

sudo apt-get install cpanminus libperl-dev

Now you have two choose between one of the 3 options below:

Option 1: System-level installation:

cpanm --notest --sudo Pheno::Ranker
pheno-ranker -h

Option 2: Install Pheno-Ranker and the dependencies at ~/perl5

cpanm --local-lib=~/perl5 local::lib && eval $(perl -I ~/perl5/lib/perl5/ -Mlocal::lib)
cpanm --notest Pheno::Ranker
pheno-ranker --help

Option 3: Install Pheno-Ranker and the dependencies in a "virtual environment" (at local/) . We'll be using the module Carton for that:

mkdir local
cpanm --notest --local-lib=local/ Carton
echo "requires 'Pheno::Ranker';" > cpanfile
export PATH=$PATH:local/bin; export PERL5LIB=$(pwd)/local/lib/perl5:$PERL5LIB
carton install
carton exec -- pheno-ranker -help

System requirements

* Ideally a Debian-based distribution (Ubuntu or Mint), but any other (e.g., CentOs, OpenSuse) should do as well.
* Perl 5 (>= 5.26 core; installed by default in most Linux distributions). Check the version with "perl -v".
* >= 4GB of RAM
* 1 core
* At least 16GB HDD

HOW TO RUN PHENO-RANKER

For executing pheno-ranker you will need a PXF/BFF file(s) in JSON|YAML format. The reference cohort must be a JSON array, where each individual data are consolidated in one object.

There are two modes of operation:

Cohort mode:

Intra-cohort: With --r argument and 1 cohort.

Inter-cohort: With --r and multiple cohort files. It can be used in combination with --append-prefixes to add prefixes to each individual id.

Patient Mode:

With -r reference cohort(s) and --t patient data.

Examples:

$ ./pheno-ranker -r phenopackets.json  # intra-cohort

$ ./pheno-ranker -r phenopackets.yaml -o my_matrix.txt # intra-cohort

$ ./pheno-ranker -r phenopackets.json -w weights.yaml --exclude-terms sex ethnicity exposures # intra-cohort with weights

$ $path/pheno-ranker -r individuals.json others.yaml --append-prefixes CANCER CONTROL  # inter-cohort

$ $path/pheno-ranker -r individuals.json -t patient.yaml -max-out 100 # mode patient

COMMON ERRORS AND SOLUTIONS

* Error message: Foo
  Solution: Bar

* Error message: Foo
  Solution: Bar

CITATION

The author requests that any published work that utilizes Pheno-Ranker includes a cite to the the following reference:

Rueda, M et al., (2023). Advancing Semantic Similarity Analysis of Phenotypic Data Stored in GA4GH Standards and Beyond. Manuscript in preparation.

AUTHOR

Written by Manuel Rueda, PhD. Info about CNAG can be found at https://www.cnag.eu.

COPYRIGHT AND LICENSE

This PERL file is copyrighted. See the LICENSE file included in this distribution.