pulseTD: RNA life cycle dynamics analysis based on pulse model of 4sU-seq time course sequencing data
1College of Bioinformatics Science and Technology, Harbin Medical University, Heilongjiang, China.
Peerj
|July 28, 2020
Summary
Accurately identifying RNA life cycle dynamics (RLCD) is challenging. We developed pulseTD, an R package integrating 4sU-seq and RNA-seq data, to robustly capture and predict RNA dynamics.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genomics
Background:
- Intracellular RNA undergoes dynamic changes throughout its life cycle, including transcription, splicing, and degradation.
- These dynamic changes, termed RNA life cycle dynamics (RLCD), are crucial for gene expression regulation but challenging to accurately identify.
- Current methods struggle with the unknown functional forms of RLCD, limiting robust analysis.
Purpose of the Study:
- To develop a robust and accurate method for identifying RNA life cycle dynamics (RLCD).
- To create an R package that integrates multiple data types for comprehensive RLCD analysis.
- To enable prediction of future RNA transcription and expression trends.
Main Methods:
- Development of an R package named pulseTD.
- Integration of 4sU-seq and RNA-seq data.
- Application of a pulse model to capture continuous changes in RLCD rates.
Main Results:
- The pulseTD package accurately and robustly identifies RLCD.
- It provides flexible functions to capture continuous changes in RLCD rates.
- pulseTD demonstrates superior accuracy and robustness compared to existing methods.
- The package can predict future trends in RNA transcription and expression.
Conclusions:
- pulseTD offers a significant advancement in the accurate and robust identification of RNA life cycle dynamics.
- The R package facilitates a deeper understanding of RNA metabolism and gene regulation.
- pulseTD is a valuable tool for researchers studying RNA dynamics, available on GitHub.
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