pysradb: A Python package to query next-generation sequencing metadata and data from NCBI Sequence Read Archive
Abstract
NCBIs Sequence Read Archive (SRA) is the primary archive of next-generation sequencing datasets. SRA makes metadata and raw sequencing data available to the research community to encourage reproducibility, and to provide avenues for testing novel hypotheses on publicly available data. However, existing methods to programmatically access these data are limited. We introduce a Python package pysradb that provides a collection of command line methods to query and download metadata and data from SRA utilizing the curated metadata database available through the SRAdb project. We demonstrate the utility of pysradb on multiple use cases for searching and downloading SRA datasets. It is available freely at https://github.com/saketkc/pysradb.
02 /Specification & Classification
Click any tag to browse matching papersReproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- srahunter: a user-friendly tool to speed up and simplify data downloading from NCBI SRA
Enrico Bortoletto, Riccardo Frizzo, … Umberto Rosani·bioRxiv·Mar 19, 2024
- MetaSRA: normalized sample-specific metadata for the Sequence Read Archive
Matthew N. Bernstein, AnHai Doan, Colin N. Dewey·BioinformaticsPeer-reviewed·May 21, 2017
- iSeq: An integrated tool to fetch public sequencing data
Haoyu Chao, Z Li, … Ming Chen·BioinformaticsPeer-reviewed·Oct 23, 2024
- Increasing metadata coverage of SRA BioSample entries using deep learning based Named Entity Recognition
Adam Klie, Brian Tsui, … Hannah K. Carter·DatabasePeer-reviewed·Jan 1, 2021
- SraTailor: GUI software for visualizing high-throughput sequence read archives
Shinya Oki, Kazumitsu Maehara, … Chikara Meno·bioRxiv·May 16, 2014
- Reproducible acquisition, management, and meta-analysis of nucleotide sequence (meta)data using q2-fondue
Michał Ziemski, Anja Adamov, … Nicholas A. Bokulich·BioinformaticsPeer-reviewed·Sep 19, 2022