https://github.com/se7en69/bio-wrangler

Bio-Wrangler is a Python package for bioinformatics data wrangling. It helps load, filter, merge, and summarize bioinformatics datasets from formats like FASTA, FASTQ, VCF, and GFF.
https://github.com/se7en69/bio-wrangler

bio-wrangler bioinformatics development fasta fastq gff python pythonpackage vcf wrangler

Last synced: 3 months ago
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Bio-Wrangler is a Python package for bioinformatics data wrangling. It helps load, filter, merge, and summarize bioinformatics datasets from formats like FASTA, FASTQ, VCF, and GFF.

• Host: GitHub
• URL: https://github.com/se7en69/bio-wrangler
• Owner: se7en69
• License: mit
• Created: 2024-10-09T07:52:04.000Z (4 months ago)
• Default Branch: main
• Last Pushed: 2024-10-09T08:13:52.000Z (4 months ago)
• Last Synced: 2024-11-12T19:25:00.156Z (3 months ago)
• Topics: bio-wrangler, bioinformatics, development, fasta, fastq, gff, python, pythonpackage, vcf, wrangler
• Language: Python
• Homepage: https://pypi.org/project/bio-wrangler/
• Size: 123 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE.md
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        
# Bio-Wrangler

**Bio-Wrangler** is a Python package designed for wrangling bioinformatics data, including formats such as **FASTA**, **FASTQ**, **VCF**, and **GFF**. The package allows users to load, filter, summarize, and merge bioinformatics datasets into pandas DataFrames, enabling efficient data manipulation and analysis.

## Features

- Load **FASTA**, **FASTQ**, **VCF**, and **GFF** files into pandas DataFrames.

- Filter data based on quality, chromosome, position, and attributes.

- Summarize datasets to extract key statistics.

- Merge multiple datasets.

- Save processed data to CSV or Excel formats.

## Table of Contents

- [Installation](#installation)

- [Usage](#usage)

  - [Loading Data](#loading-data)

  - [Filtering Data](#filtering-data)

  - [Summarizing Data](#summarizing-data)

  - [Merging Datasets](#merging-datasets)

  - [Saving Data](#saving-data)

- [Contributing](#contributing)

- [License](#license)

## Installation

To install Bio-Wrangler, use the following command:

pip install bio-wrangler

## Usage

### 1. Loading Data

Bio-Wrangler provides methods to load bioinformatics files into pandas DataFrames.

#### Example: Loading FASTA, FASTQ, VCF, and GFF Files

from bio_wrangler.bio_wrangler import BioWrangler

# Initialize the class

wrangler = BioWrangler()

# Load a FASTA file

fasta_data = wrangler.load_fasta('path/to/sample.fasta')

print(fasta_data.head())

# Load a FASTQ file

fastq_data = wrangler.load_fastq('path/to/sample.fastq')

print(fastq_data.head())

# Load a VCF file

vcf_data = wrangler.load_vcf('path/to/sample.vcf')

print(vcf_data.head())

# Load a GFF file

gff_data = wrangler.load_gff('path/to/sample.gff')

print(gff_data.head())

### 2. Filtering Data

Bio-Wrangler allows you to filter data based on various criteria such as quality, chromosome, position, and attributes.

#### Example: Filtering FASTQ by Quality

# Filter FASTQ data by average quality score threshold

filtered_fastq = wrangler.filter_fastq_by_quality(fastq_data, 30.0)

print(filtered_fastq.head())

#### Example: Filtering VCF by Chromosome

# Filter VCF data to retain only records from a specific chromosome

filtered_vcf = wrangler.filter_by_chromosome(vcf_data, 'chr1')

print(filtered_vcf.head())

#### Example: Filtering GFF by Attribute

# Filter GFF data by a specific attribute, such as gene_id

filtered_gff = wrangler.filter_by_attribute(gff_data, 'ID', 'gene1')

print(filtered_gff.head())

#### Example: Filtering VCF by Position Range

# Filter VCF data by a specific position range

filtered_vcf_range = wrangler.filter_by_position_range(vcf_data, 100000, 500000)

print(filtered_vcf_range.head())

### 3. Summarizing Data

Bio-Wrangler can generate summary statistics for your datasets.

#### Example: Summarizing FASTQ Data

# Summarize FASTQ data

fastq_summary = wrangler.summarize_fastq(fastq_data)

print(fastq_summary)

#### Example: Summarizing VCF Data

# Summarize VCF data

vcf_summary = wrangler.summarize_data(vcf_data)

print(vcf_summary)

### 4. Merging Datasets

Bio-Wrangler can merge multiple datasets into a single DataFrame.

#### Example: Merging VCF Datasets

# Merge two VCF datasets

merged_vcf = wrangler.merge_datasets(vcf_data, filtered_vcf)

print(merged_vcf.head())

### 5. Saving Data

After processing your data, you can save it to CSV or Excel formats using Bio-Wrangler.

#### Example: Saving Filtered VCF Data to CSV

# Save the filtered VCF data to a CSV file

wrangler.save_data(filtered_vcf, 'filtered_vcf_output.csv', 'csv')

#### Example: Saving Data to Excel

# Save data to an Excel file

wrangler.save_data(filtered_fastq, 'filtered_fastq_output.xlsx', 'xlsx')

## Contributing

Contributions to Bio-Wrangler are welcome! If you have any bug reports, feature requests, or pull requests, please follow the guidelines in the **CONTRIBUTING.md** file.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

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