kmer_counting_loop.py
Introduction
This tool is designed for bioinformatics analysis to count k-mer frequencies in sequencing data stored in FASTQ format. It is particularly useful when dealing with large datasets as it leverages Python's multiprocessing capabilities for parallel processing, thus enhancing performance and reducing computation time.
Features
Count specified k-mer sizes in FASTQ files (compressed with gzip).
Use input CSV files containing k-mer sequences to filter and count only relevant k-mers.
Handle large datasets efficiently with chunk-based parallel processing.
Utilize multiple CPU cores for faster computation.
Generate output CSV files containing the count of each k-mer.
Release files for kmer-counting 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| kmer_counting-0.1.0.tar.gz | 4.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| kmer_counting-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.7 kB
Release files / kmer_counting-0.1.0.tar.gz
| Download URL | kmer_counting-0.1.0.tar.gz |
|---|---|
| Size | 4.2 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.10.4
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Release files / kmer_counting-0.1.0-py3-none-any.whl
| Download URL | kmer_counting-0.1.0-py3-none-any.whl |
|---|---|
| Size | 4.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.0.0 CPython/3.10.4
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