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Detecting differential transcript usage in complex diseases with SPIT
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DOI：10.1016/j.crmeth.2024.100736.png)
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Abstract
En 中文
Differential transcript usage (DTU) plays a crucial role in determining how gene expression differs among cells, tissues, and developmental stages, contributing to the complexity and diversity of biological systems. In abnormal cells, it can also lead to deficiencies in protein function and underpin disease pathogenesis. Analyzing DTU via RNA sequencing (RNA-seq) data is vital, but the genetic heterogeneity in populations with complex diseases presents an intricate challenge due to diverse causal events and undetermined subtypes. Although the majority of common diseases in humans are categorized as complex, state-of-theart DTU analysis methods often overlook this heterogeneity in their models. We therefore developed SPIT, a statistical tool that identifies predominant subgroups in transcript usage within a population along with their distinctive sets of DTU events. This study provides comprehensive assessments of SPIT's methodology and applies it to analyze brain samples from individuals with schizophrenia, revealing previously unreported DTU events in six candidate genes.
Keywords:
RNA-SEQ
EXPRESSION
SCHIZOPHRENIA
STRESS
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