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Python API

Updated for basepair version: 2.0.0
Python bindings for Basepair’s API. An outline of the contents on this page:

  1. Listing available data
  2. Creating or deleting a sample
  3. Create an analysis
  4. Download result

After starting a python3 interactive session run:

import basepair
import json

bp = basepair.connect(json.load(open('/path/to/basepair.config.json')))

1. Listing available data​

You can list various types of data available to you via the bp.print_data() command. By default it prints a human-readable table (critical fields only). Set json=True to view the full raw JSON.

1.1 List genomes​

Print the genomes table:

bp.print_data('genomes')

Typical output:

 id  name                      date_created
---- -----------------------   --------------------------
  1  hg19                      2018-04-18T14:58:15.865993
  2  mm10                      2018-04-18T15:05:39.770488
  3  mm9                       2018-04-18T15:10:33.438603
  …

Raw JSON:

bp.genomes
[
  {"date_created": "2018-04-18T14:58:15.865993", "id": 1, "name": "hg19",
   "resource_uri": "/api/v1/genomes/1"},
  {"date_created": "2018-04-18T15:05:39.770488", "id": 2, "name": "mm10",
   "resource_uri": "/api/v1/genomes/2"},
  …
]

1.2 List workflows​

Pretty table:

bp.print_data('workflows')

Raw JSON:

bp.get_workflows()

1.3 List samples​

Pretty table:

bp.print_data('samples')

Raw JSON:

bp.get_samples()

1.4 Get a sample​

sample = bp.get_sample(10000)

1.5 List analyses​

Pretty table:

bp.print_data('analyses')

Raw JSON:

bp.get_analyses()

1.5.1 Analysis detail​

Pretty table for analysis 10000:

bp.print_data('analysis', uid=[10000])

Raw JSON:

bp.get_analysis(10000)

2. Creating or deleting a sample​

A Basepair sample is handled through the BpSample class. You can either create a new sample or get information for an existing one.

2.1 Create a new sample​

In this example we create Sample1—paired-end RNA-seq data on the Illumina platform using the hg19 genome (project ID optional).

data = {
    'name': 'Sample1',
    'genome': 'hg19',
    'datatype': 'rna-seq',
    'platform': 'illumina',
    'filepaths1': [
        'Sample1.lane1.R1.fastq.gz',
        'Sample1.lane2.R1.fastq.gz'],
    'filepaths2': [
        'Sample1.lane1.R2.fastq.gz',
        'Sample1.lane2.R2.fastq.gz'],
    # 'projects': '123',  # optional
}

sample = bp.create_sample(data=data)

Run ?BpSample in Python for more fields.

2.2 Delete a sample​

bp.delete_sample(10000)   # returns <Response [204]> on success

3. Creating or deleting an analysis​

This section is still under construction.

Create an analysis (e.g., STAR mapping) once you know the workflow_id:

bp.create_analysis(workflow_id='4', sample_id='3206')

Custom parameters example:

bp.create_analysis(
    workflow_id='5',
    sample_id='1',
    params={
        'node': {
            'annotate': {
                'upstream': '5000',
                'downstream': '5000',
            }
        }
    }
)

For pipelines needing >2 groups (e.g., DESeq, Cuffdiff):

bp.create_analysis(
    workflow_id='42',
    sample_ids=[5014, 5016, 5017, 5018],
    params={
        'node': {
            'deseq': {
                'group_ids': '5017,5018:5016:5014',
                'group_names': 'group 1 name:group 2 name:group 3 name'
            }
        }
    }
)

bp.create_analysis(
    workflow_id='29',
    sample_ids=[5014, 5016, 5017, 5018],
    params={
        'node': {
            'cuffdiff': {
                'group_ids': '5017,5018:5016:5014',
                'group_names': 'group 1 name:group 2 name:group 3 name'
            }
        }
    }
)

4. Download results​

You can download files from one or more analyses.

4.1 Example 1​

Downloads analysis 10000, excluding files tagged “bam”, into ./test/:

bp.download_analysis(
    10000,
    tags=[['bam']],
    tagkind='diff',
    outdir='./test/')

4.2 Example 2​

Downloads only files tagged “fastqc” from analysis 10000 into ./test/:

bp.download_analysis(
    10000,
    tags=[['fastqc']],
    tagkind='subset',
    outdir='./test/')

4.3 Example 3​

Downloads files tagged either (“rnaseq_metrics” & “json”) or (“fastqc” & “zip”) from analysis 10000 into ./test/:

bp.download_analysis(
    10000,
    tags=[['rnaseq_metrics', 'json'], ['fastqc', 'zip']],
    tagkind='exact',
    outdir='./test/')

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