hca_to_scea

A tool to assist in the automatic conversion of an hca metadata spreadsheet to scea metadata MAGE-TAB files.

Installation

pip install hca-to-scea

Description

The tool takes as input an HCA metadata spreadsheet and converts the metadata to SCEA MAGE-TAB files which are then saved to an output directory.

Usage

To run it as a package, after installing it via pip:

$ hca-to-scea -h                                                  
usage: hca2scea.py [-h] -s SPREADSHEET -id PROJECT_UUID -study STUDY
                   [-name {cs_name,cs_id,sp_name,sp_id,other}] -ac
                   ACCESSION_NUMBER -c CURATORS [CURATORS ...] -et
                   {baseline,differential} [--facs] -f
                   EXPERIMENTAL_FACTORS [EXPERIMENTAL_FACTORS ...] -pd
                   PUBLIC_RELEASE_DATE -hd HCA_UPDATE_DATE
                   [-r RELATED_SCEA_ACCESSION [RELATED_SCEA_ACCESSION ...]]
                   [-o OUTPUT_DIR]

run hca -> scea tool

optional arguments:
  -h, --help            show this help message and exit
  -s SPREADSHEET, --spreadsheet SPREADSHEET
                        Please provide a path to the HCA project spreadsheet.
  -id PROJECT_UUID, --project_uuid PROJECT_UUID
                        Please provide an HCA ingest project submission id.
  -study STUDY          Please provide the SRA or ENA study accession.
  -name {cs_name,cs_id,sp_name,sp_id,other}
                        Please indicate which field to use as the sample name.
                        cs=cell suspension, sp = specimen.
  -ac ACCESSION_NUMBER, --accession_number ACCESSION_NUMBER
                        Provide an E-HCAD accession number. Please find the
                        next suitable accession number by checking the google
                        tracker sheet.
  -c CURATORS [CURATORS ...], --curators CURATORS [CURATORS ...]
                        space separated names of curators
  -et {baseline,differential}, --experiment_type {baseline,differential}
                        Please indicate whether this is a baseline or
                        differential experimental design
  --facs                Please specify this argument if FACS was used to
                        isolate single cells
  -f EXPERIMENTAL_FACTORS [EXPERIMENTAL_FACTORS ...], --experimental_factors EXPERIMENTAL_FACTORS [EXPERIMENTAL_FACTORS ...]
                        space separated list of experimental factors
  -pd PUBLIC_RELEASE_DATE, --public_release_date PUBLIC_RELEASE_DATE
                        Please enter the public release date in this format:
                        YYYY-MM-DD
  -hd HCA_UPDATE_DATE, --hca_update_date HCA_UPDATE_DATE
                        Please enter the last time the HCA prohect submission
                        was updated in this format: YYYY-MM-DD
  -r RELATED_SCEA_ACCESSION [RELATED_SCEA_ACCESSION ...], --related_scea_accession RELATED_SCEA_ACCESSION [RELATED_SCEA_ACCESSION ...]
                        space separated list of related scea accession(s)
  -o OUTPUT_DIR, --output_dir OUTPUT_DIR
                        Provide full path to preferred output dir

To run it as a python module:

cd /path-to/hca_to_scea
python -m hca-to-scea-tools.hca2scea-backend.hca2scea -h

Arguments

Definitions

Factor values

A factor value is a chosen experimental characteristic which can be used to group or differentiate samples. Multiple factor values can be entered and should be chosen from the following list.

• Known disease(s)
• Development stage
• Organ
• Organ part
• Selected cell type(s)
• Individual

There must be at least 1 factor value. If you cannot identify a factor value i.e. all donors and samples share the same metadata with respect to the above list of factor values, then enter 'Individual'.

Datasets with more than 1 technolgoy type are not eligible for SCEA. Therefore, technology type is not a valid factor value.

Experiment type

An experiment with samples which can be grouped or differentiatied by a factor value is classified as 'differential'. The list of possible factor values can be found above.

If 1 or more factor values other than 'Individual' is identified, then the experiment type should be 'Differential'. If the only factor value is 'Individual', then the experiment type should be 'Baseline'.

Related E-HCAD-ID

If the project has been split into two separate E-HCAD datasets, due to different technologies being used in the same project, or any other reason, then enter the E-HCAD-ID for the other dataset here. Example: E-HCAD-50.

Examples

Required arguments only

python3 hca2scea.py -s /home/aday/GSE111976-endometrium_MC_SCEA.xlsx -id 379ed69e-be05-48bc-af5e-a7fc589709bf -study SRP135922 -ac 50 -c AD -tt 10Xv3_3 -et differential -f menstrual cycle day -pd 2021-06-29 -hd 2021-02-12

Specify optional name argument

python3 hca2scea.py -s /home/aday/GSE111976-endometrium_MC_SCEA.xlsx -id 379ed69e-be05-48bc-af5e-a7fc589709bf -study SRP135922 -name cs_name -ac 50 -c AD -tt 10Xv3_3 -et differential -f menstrual cycle day -pd 2021-06-29 -hd 2021-02-12

Specify optional related scea accession

python3 hca2scea.py -s /home/aday/GSE111976-endometrium_MC_SCEA.xlsx -id 379ed69e-be05-48bc-af5e-a7fc589709bf -study SRP135922 -ac 50 -c AD -tt 10Xv3_3 -et differential -f menstrual cycle day -pd 2021-06-29 -hd 2021-02-12 -r 51

Specify that FACS was used

python3 hca2scea.py -s /home/aday/GSE111976-endometrium_MC_SCEA.xlsx -id 379ed69e-be05-48bc-af5e-a7fc589709bf -study SRP135922 -ac 50 -c AD -tt 10Xv3_3 -et differential -f menstrual cycle day -pd 2021-06-29 -hd 2021-02-12 --facs

Specify optional output dir

python3 hca2scea.py -s /home/aday/GSE111976-endometrium_MC_SCEA.xlsx -id 379ed69e-be05-48bc-af5e-a7fc589709bf -study SRP135922 -ac 50 -c AD -tt 10Xv3_3 -et differential -f menstrual cycle day -pd 2021-06-29 -hd 2021-02-12 -o my_output_dir

Developer Notes

Developing Code in Editable Mode

Using pip's editable mode, projects using hca-to-scea as a dependency can refer to the latest code in this repository directly without installing it through PyPI. This can be done either by manually cloning the code base:

pip install -e path/to/hca-to-scea

or by having pip do it automatically by providing a reference to this repository:

pip install -e \
git+https://github.com/ebi-ait/hca-to-scea-tools.git\
#egg=hca-to-scea

Publish to PyPI

1. Create PyPI Account through the registration page.

   Take note that PyPI requires email addresses to be verified before publishing.

2. Package the project for distribution.

    python setup.py sdist
   

3. Install Twine

    pip install twine        
   

4. Upload the distribution package to PyPI.

    twine upload dist/*
   

   Running python setup.py sdist will create a package in the dist directory of the project base directory.