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brew

Installer badread avec Homebrew

Consultez les chemins d'installation, exécutables, métadonnées et notes de sécurité de badread pour les workflows d'agents IA.

installation

Commandes d'installation supplémentaires

macOS

Homebrewvérifié · 100%
brew install badread

local Homebrew formula metadata

aperçu

Résumé du paquet

Long read simulator that can imitate many types of read problems

Commandes et alias

  • badread

historique

Historique du projet et usages

Badread is a bioinformatics CLI for simulating error-prone long sequencing reads. It is historically notable less as a large software platform and more as a citable research tool that gave developers controlled ways to stress-test long-read assemblers and analysis pipelines.

Historique du projet

The Badread GitHub repository was created in June 2018, with the first v0.1.0 GitHub release in July 2018. The README says Badread was made to test tools that take long reads as input by letting users control read problems such as chimeras, low-quality regions, systematic basecalling errors, junk reads, random reads, adapters, glitches, and quality-score models.

Badread was published in the Journal of Open Source Software in 2019 as 'Badread: simulation of error-prone long reads' with DOI 10.21105/joss.01316. That gave the package a stable academic citation path alongside its command-line distribution.

The project continued to track long-read practice in later releases, with README examples for older Oxford Nanopore reads, newer Nanopore R10.4.1-style settings, PacBio HiFi-style reads, and configurable error and qscore models.

Historique d'adoption

Badread's adoption is mainly in computational biology workflows where developers need reproducible fake FASTQ data. Its packaging in Homebrew makes it easy for macOS bioinformatics users to install without manually cloning the repository, while the README also documents pip installation directly from GitHub.

The JOSS publication and Zenodo DOI made Badread easier to cite in papers and benchmarking notes than many informal simulator scripts. GitHub release activity from 2018 through 2026 shows a maintained niche tool rather than a frozen paper artifact.

Modes d'utilisation

Typical usage is badread simulate with a reference FASTA and requested quantity, piping FASTQ output through gzip. Users tune read length, identity, error model, qscore model, adapter sequences, chimeras, glitches, junk reads, random reads, and seeds.

The README emphasizes control over realism: users can deliberately make reads very bad, pretty good, very good, or platform-like in order to test how downstream tools react.

Pourquoi les passionnés de paquets s'y intéressent

Badread matters to package nerds because it is a compact example of research software that deserves normal CLI packaging: it has a paper, DOI, reproducible command-line interface, domain data models, and a long tail of users who may just need the executable in a workflow.

It also shows why scientific packages often live awkwardly between GitHub, pip, Homebrew, and citation systems: the code, docs, releases, and scholarly identity all matter.

Chronologie

  • 2018: Badread GitHub repository created and v0.1.0 released.
  • 2019: Badread published in the Journal of Open Source Software.
  • 2021: v0.2.0 released.
  • 2023: v0.3.0 and v0.4.0 released.
  • 2026: v0.4.2 released.

Related projects

  • Badread is related to long-read sequencing platforms and models such as Oxford Nanopore and PacBio.
  • The README compares Badread with other long-read simulators and notes dependencies such as Edlib, NumPy, SciPy, and Matplotlib.

posture de sécurité

Niveau de risque : vert

narrow executable package without higher-risk signals.

Classificateur de risque

risque vert · confiance faible · appliance

Pourquoi

  • narrow executable package without higher-risk signals

Signaux

  • metadata:no-higher-risk-signals

Comportement d'installation

  • Aucun hook post-install Homebrew n’est enregistré dans les métadonnées de formule.
  • Les métadonnées de bottle Homebrew sont disponibles pour 6 plateformes.
  • S’installe avec 3 dépendances d’exécution.

Revue recommandée

Avant une utilisation sans surveillance par un agent, vérifiez si l'outil lit des identifiants en clair, écrit un état distant, publie des artefacts ou lance des plugins.

exécutables

Exécutables installés

CommandeTypeExpositionNote
badreadcliexécutable global

fraîcheur

Version et fraîcheur

Ces signaux séparent l'âge de génération de la page, l'activité du gestionnaire de paquets et la comparaison avec les versions amont. Un retard de version n'est signalé que lorsqu'une URL de preuve et des versions comparables sont présentes.

page générée2026-07-10
version du gestionnaire0.4.2
gestionnaire mis à jour2026-04-22
données localesOK
amontà jour
dernière version détectéev0.4.2

https://github.com/rrwick/Badread

  • OKAucun avertissement de fraîcheur n'a été généré.

métadonnées d'installation

Métadonnées du paquet

Clé du paquetbrew:badread
Version0.4.2
Gestionnaire de paquetsHomebrew
Page du gestionnaire de paquetshttps://formulae.brew.sh/formula/badread
Page d'accueilhttps://github.com/rrwick/Badread
Dépôthttps://github.com/rrwick/Badread
Docs amonthttps://github.com/rrwick/Badread#readme
LicenceGPL-3.0-or-later
Archive sourcehttps://github.com/rrwick/Badread/archive/refs/tags/v0.4.2.tar.gz
Dernière mise à jour2026-04-22T09:09:57Z
Pulseupdated
Dépendancesnumpy, python@3.14, scipy
Bouteilledisponible (sur arm64_linux, arm64_sequoia, arm64_sonoma, arm64_tahoe, sonoma, x86_64_linux)
post-install Homebrewnon défini
Serviceaucun déclaré

faits du registre

Détails de la base source

Source DatabaseHomebrew formula API
Taphomebrew/core
Full Namebadread
Version Scheme0
Revision0
Bottle Stable Root URLhttps://ghcr.io/v2/homebrew/core
Deprecatedno
Disabledno
Keg Onlyno
URL Keys
  • stable

piste source

Généré depuis les données du dépôt

Cette page est servie par av-web depuis l'artéfact SQLite privé des paquets généré par scripts/generate-pkg-sqlite.py.

Sources utilisées

  • Geiger risk classifier
  • Nucleus package database
  • av.db category and tag curation
  • cross-ecosystem install command graph
  • curated package history
  • package relationship graph
  • package version freshness
  • package-page enrichment