tsRFun

tsRFun integrates multiomics datasets to analyze tRNA-derived small RNAs (tsRNAs), enabling expression profiling, target identification, interaction network construction, and prognostic assessment.

Key Features:

• Multiomics integration: Integration of transcriptome, epitranscriptome, and targetome datasets for comprehensive tsRNA analysis.
• Expression profiling: Evaluation of tsRNA expression profiles across 32 types of cancers.
• Prognostic analysis: Assessment of the prognostic value of tsRNAs for patient outcome studies.
• Target identification: Identification of tsRNA target molecules using high-throughput CLASH/CLEAR and CLIP-Seq sequencing data.
• Interaction networks: Construction of interaction networks among tsRNAs, microRNAs, and mRNAs to elucidate regulatory relationships.
• tsRNA identification and target prediction: Computational identification of tsRNAs and prediction of their targets for downstream functional analyses.
• Functional enrichment analysis: Enrichment analysis of predicted or experimentally supported tsRNA targets to infer biological processes and pathways.

Scientific Applications:

• Cancer and disease association studies: Investigation of tsRNA expression and prognostic implications across multiple cancer types and other diseases.
• Molecular mechanism elucidation: Examination of tsRNA interactions with microRNAs and mRNAs to study regulatory mechanisms.
• Biomarker and therapeutic target discovery: Identification of candidate prognostic biomarkers and potential therapeutic targets based on tsRNA expression and targets.
• Multiomics investigations: Use of combined transcriptome, epitranscriptome, and targetome data to study tsRNA biology in a systems context.

Methodology:

Integration of transcriptome, epitranscriptome, and targetome datasets and analysis of high-throughput CLASH/CLEAR and CLIP-Seq data for tsRNA-target identification.