PTEE

PTEE prioritizes target analysis tissues (TAs) for RNA-seq–based clinical genetics by integrating phenotype-annotated genes with Genotype-Tissue Expression (GTEx) data across 54 tissues and evaluating shared expressed genes and transcripts between tissues of interest (TIs) and candidate TAs.

Key Features:

• Phenotype-annotated gene integration: Integrates phenotype-annotated gene lists with tissue-expression data to link clinical phenotypes to gene expression profiles.
• GTEx data utilization: Leverages Genotype-Tissue Expression (GTEx) project expression data from 54 tissues for cross-tissue comparisons.
• Correlation analyses: Performs comprehensive correlation analyses to identify expressed genes and transcripts shared between TIs and candidate TAs.
• Alternative tissue recommendation: Recommends surrogate or alternative TAs when direct analysis of the TI is impractical, including identifying skeletal muscle for cardiac arrhythmia–related genes and skin for certain neurodevelopmental disorder genes.
• Expression dynamics awareness: Highlights expression on-off switching during ontogenesis and circadian rhythms that can create blind spots in RNA-seq analyses.
• Tissue prioritization for diagnostics and discovery: Prioritizes tissues for transcriptome analysis to support diagnosis and gene-discovery efforts in clinical genetics.

Scientific Applications:

• Clinical tissue selection: Selecting optimal TAs for RNA-seq experiments in clinical genetics studies.
• Surrogate tissue identification: Identifying surrogate tissues when the tissue of interest is inaccessible or unsuitable for RNA-seq.
• Variant interpretation support: Supporting transcriptome-based interpretation of variants by matching expression patterns between TIs and TAs.
• Gene discovery prioritization: Guiding gene-discovery efforts by prioritizing tissues with shared expression of phenotype-associated genes.
• Expression dynamics analysis: Informing analyses that account for developmental and circadian expression changes that may affect RNA-seq detectability.

Methodology:

Integrates phenotype-annotated genes with GTEx expression data from 54 tissues and applies correlation analyses to identify shared expressed genes and transcripts between TIs and TAs, and flags expression on-off switching related to ontogenesis and circadian rhythms.