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A Quantitative Fitness Analysis Workflow
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Herramientas reproducibles y flujos de trabajo computacionales mejorados para la evaluación de efectos de lote de

Jessica K Anderson, Jiwei Zhang, Xinshou Ge

    bioRxiv : the preprint server for biology
    |February 23, 2026
    PubMed
    Resumen

    La corrección de efectos de lote es crucial para un análisis de datos fiable. BatchQC es un nuevo paquete R que ofrece herramientas y visualizaciones para evaluar y corregir efectos de lote en diversos tipos de datos.

    Palabras clave:
    efectos de loteanálisis de datoscorrección de efectos de loteevaluación de efectos de lotepaquete Rbioinformáticabiología computacionalciencia de datosreproducibilidadvisualización

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    Área de la Ciencia:

    • Bioinformática
    • Biología Computacional
    • Ciencia de Datos

    Sus antecedentes:

    • Los efectos de lote introducen sesgos en el análisis de datos de lotes múltiples.
    • La evaluación de la gravedad de los efectos de lote es fundamental para seleccionar estrategias de corrección.
    • Las herramientas existentes carecen de una evaluación integral y reproducible de los efectos de lote.

    Objetivo del estudio:

    • Introducir BatchQC, un novedoso paquete R para la evaluación y corrección de efectos de lote.
    • Proporcionar herramientas y visualizaciones reproducibles para el análisis cuantitativo y cualitativo de efectos de lote.
    • Facilitar decisiones informadas sobre estrategias de corrección de efectos de lote.

    Principales métodos:

    • Desarrolló BatchQC como un paquete R con un diseño orientado a objetos.
    • Integró estructuras de datos estandarizadas de Bioconductor para una amplia compatibilidad.
    • Implementó métodos comunes de evaluación de efectos de lote junto con métricas cuantitativas novedosas.

    Principales resultados:

    • BatchQC ofrece flujos de trabajo reproducibles para evaluar efectos de lote.
    • Proporciona visualizaciones para la evaluación cualitativa y cuantitativa.
    • Las métricas novedosas permiten la comparación directa de métodos de corrección de efectos de lote.

    Conclusiones:

    • BatchQC es el primer paquete R integral para la corrección de efectos de lote.
    • Facilita la evaluación y corrección reproducibles de los efectos de lote.
    • Ayuda a determinar los beneficios de la corrección de efectos de lote para diversos conjuntos de datos.