biolib

Personal computational biology utility library for sequence analysis and qPCR data processing, built for Python 3.12+.

Installation

pip install -e ".[dev]"

Requirements

• Python >= 3.12
• numpy >= 1.26
• scipy >= 1.12
• pysam >= 0.22
• rpy2 >= 3.5 (required for R-based qPCR analysis and enrichment functions)

Modules

seqlib — Sequence Analysis Utilities

A broad collection of bioinformatics tools for next-generation sequencing analysis.

Module	Description
seqlib.stats	Statistical functions for genomic data
seqlib.util	General-purpose utility functions
seqlib.seqlib	Core sequence manipulation
seqlib.seqstats	Sequence-level statistics
seqlib.intervallib	Genomic interval operations
seqlib.mySam	SAM/BAM file handling
seqlib.GTFlib	GTF/GFF annotation parsing
seqlib.algorithms	Common bioinformatics algorithms
seqlib.prob	Probability distributions
seqlib.JensenShannon	Jensen-Shannon divergence
seqlib.Alignment	Sequence alignment utilities
seqlib.Chip	ChIP-seq analysis tools
seqlib.clustering	Clustering algorithms
seqlib.converters	Format conversion utilities
seqlib.bowtie	Bowtie aligner wrappers
seqlib.bwa	BWA aligner wrappers
seqlib.LSFlib	LSF cluster job submission
seqlib.QCtools	Quality control tools
seqlib.RIPDiff	RIP-seq differential analysis
seqlib.continuousData	Continuous data representation and operations
seqlib.blockIt	Block-based data iteration
seqlib.misc	Miscellaneous helper functions

qpcr — qPCR Analysis

Tools for quantitative PCR data processing and analysis.

Module	Description
qpcr.abi	ABI instrument file parsing
qpcr.qpcrAnalysis	ddCt analysis and qPCR workflows
qpcr.MinerMethod	Miner method for PCR efficiency estimation
qpcr.util	Utility functions for qPCR data

Usage Examples

Parse a GTF annotation file

from seqlib import GTFlib

gtf = GTFlib.GTFReader("annotation.gtf")
for gene in gtf:
    print(gene.gene_id, gene.chrom, gene.start, gene.end)

Compute Jensen-Shannon divergence

from seqlib.JensenShannon import JS_divergence

p = [0.25, 0.25, 0.25, 0.25]
q = [0.50, 0.50, 0.00, 0.00]
divergence = JS_divergence(p, q)
print(divergence)

Work with genomic intervals

from seqlib import intervallib

interval = intervallib.Interval("chr1", 1000, 2000, strand="+")
print(interval.length())

Load ABI qPCR results

from qpcr import abi

data = abi.parseABIResults("results.txt", "cycleData.txt")

Run ddCt qPCR analysis

from qpcr import qpcrAnalysis

results = qpcrAnalysis.ddCtAnalysis(
    data_file="results.txt",
    endogenous_control="GapDH",
    reference_sample="control"
)

Development

Setup

git clone https://github.com/gofflab/biolib.git
cd biolib
pip install -e ".[dev]"

Running Tests

pytest

With coverage:

pytest --cov=src --cov-report=html

Linting and Formatting

# Check for issues
ruff check src/

# Auto-fix issues
ruff check --fix src/

# Format code
ruff format src/

Pre-commit Hooks

pip install pre-commit
pre-commit install

Project Structure

biolib/
├── src/
│   ├── qpcr/           # qPCR analysis modules
│   └── seqlib/         # Sequence analysis modules
├── tests/              # Test suite
├── pyproject.toml      # Package configuration
└── requirements.txt    # Pinned dependencies

License

MIT