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Incorporación de la incertidumbre de escala en análisis de expresión diferencial utilizando ALDEx2

Scott J Dos Santos¹, Gregory B Gloor¹

¹Department of Biochemistry, Schulich School of Medicine and Dentistry, Western University, Ontario, Canada.

Current protocols

|February 4, 2026

Resumen

Este resumen es generado por máquina.

Los análisis de abundancia diferencial en datos de secuenciación mejoran al tener en cuenta la incertidumbre de la escala de la muestra. ALDEx2

Palabras clave:

ALDEx2 ARNSeq abundancia diferencial expresión diferencial metagenómica

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Área de la Ciencia:

Microbiología
Bioinformática
Genómica

Sus antecedentes:

Los análisis de abundancia y expresión diferencial son estándar para los datos de secuenciación.
Los métodos actuales a menudo carecen de información sobre la escala real de la muestra, lo que lleva a una mala interpretación de la variación técnica.
Las técnicas de normalización existentes hacen suposiciones erróneas sobre la escala biológica, lo que aumenta las tasas de falsos descubrimientos.

Objetivo del estudio:

Demostrar la incorporación de modelos de escala en el análisis de expresión diferencial para datos de ARN-seq, transcriptoma y metatranscriptoma.
Destacar el impacto del modelado de escala en los resultados del análisis.
Presentar métodos de visualización para los resultados de ALDEx2.

Principales métodos:

Utilización del paquete R ALDEx2 para construir y aplicar modelos de escala.
Realización de análisis de expresión diferencial en conjuntos de datos de transcriptoma y metatranscriptoma completos.
Aplicación del análisis de componentes principales para la visualización de datos.

Principales resultados:

Los modelos de escala mitigan las suposiciones incorrectas en la normalización, reduciendo las tasas de falsos descubrimientos.
La incorporación de modelos de escala mejora la precisión del análisis de expresión diferencial.
Los resultados de ALDEx2 se pueden visualizar de manera efectiva utilizando el análisis de componentes principales composicionales.

Conclusiones:

Tener en cuenta la incertidumbre de la escala de la muestra a través de modelos de escala es crucial para análisis precisos de abundancia y expresión diferencial.
ALDEx2 proporciona un marco para integrar el modelado de escala en flujos de trabajo bioinformáticos estándar.
Este enfoque mejora la confiabilidad de los hallazgos de datos de secuenciación de alto rendimiento.