ArticleBioinformatics (Oxford, England)2023
Metadata retrieval from sequence databases with ffq.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- GEfetch2R: fetching single-cell/bulk RNA-seq data from public repositories to R and benchmarking the subsequent format conversion tools.GigaScience · 2026Article
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- iSeq: an integrated tool to fetch public sequencing data.Bioinformatics (Oxford, England) · 2024Article
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- A Fast, Reproducible, High-throughput Variant Calling Workflow for Population Genomics.Molecular biology and evolution · 2024Article
- Quantifying orthogonal barcodes for sequence census assays.Bioinformatics advances · 2024Article
- Universal preprocessing of single-cell genomics data.bioRxiv : the preprint server for biology · 2023Article
- GEOfetch: a command-line tool for downloading data and standardized metadata from GEO and SRA.Bioinformatics (Oxford, England) · 2023Article
- Challenges to sharing sample metadata in computational genomics.Frontiers in genetics · 2023Article
- Diving deep into fish bornaviruses: Uncovering hidden diversity and transcriptional strategies through comprehensive data mining.Virus evolution · 2023Article
- Efficient querying of genomic reference databases with gget.Bioinformatics (Oxford, England) · 2023Article
- KARAJ: An Efficient Adaptive Multi-Processor Tool to Streamline Genomic and Transcriptomic Sequence Data Acquisition.International journal of molecular sciences · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
motivationSeveral genomic databases host data and metadata for an ever-growing collection of sequence datasets. While these databases have a shared hierarchical structure, there are no tools specifically designed to leverage it for metadata extraction.
resultsWe present a command-line tool, called ffq, for querying user-generated data and metadata from sequence databases. Given an accession or a paper's DOI, ffq efficiently fetches metadata and links to raw data in JSON format. ffq's modularity and simplicity make it extensible to any genomic database exposing its data for programmatic access. AVAILABILITY AND IMPLEMENTATION: ffq is free and open source, and the code can be found here: https://github.com/pachterlab/ffq.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.