Genomic Read Summary

Summary statistics for raw sequence reads in FASTQ format. For assembled contigs, see Genomic Contig Summary.

Install PySEGUL using pip if you haven’t done it yet

pip install pysegul

Create a new Python script, import the library, and write python code.

import pysegul

def summarize_reads():
    input_dir = 'tests/raw-data'
    input_format = 'auto'
    summary_mode = 'default'
    prefix = 'read_summary'
    output_dir = 'tests/output'
    summary = pysegul.ReadSummary(
        input_format,
        summary_mode,
        output_dir,
        prefix
        )
    summary.from_dir(input_dir)

You can also input the alignment paths in a list directly instead of using a directory. Replace the input_dir with input_files and provide a list of paths. Then, call the from_files method instead of from_dir.

import pysegul

def summarize_reads():
    input_path = ['tests/raw-data/read1.fastq', 'tests/raw-data/read2.fastq']
    input_format = 'auto'
    # Available values for summary_mode: 'default', 'complete', 'minimal'.
    summary_mode = 'default'
    prefix = 'read_summary'
    output_dir = 'tests/output'
    summary = pysegul.ReadSummary(
        input_format,
        summary_mode,
        output_dir,
        prefix
        )
    summary.from_files(input_path)

In complete mode, the output directory also has per-position statistics (read-pos-summary.zip), read distributions (read-dist-summary.zip), and all statistics as JSON (read-report.json), which you can load with Python’s json module:

import json

with open('tests/output/read_summary_read-report.json') as f:
    report = json.load(f)

for sample in report['samples']:
    metrics = sample['metrics']
    print(sample['sample'], metrics['read_count'], metrics['q30_pct'], metrics['duplicate_pct_est'])