AI Article Synopsis
- RNA-seq analysis is crucial for transcriptomic research, covering steps from raw reads to differential expression results.
- A comparative review of various tools used in RNA-seq analysis emphasizes their key features and includes a taxonomy for easier navigation.
- The article addresses quality control, visualization tools, and offers practical guidelines for analysts while highlighting ongoing research challenges in the field.
Article Abstract
Analysis of RNA-sequence (RNA-seq) data is widely used in transcriptomic studies and it has many applications. We review RNA-seq data analysis from RNA-seq reads to the results of differential expression analysis. In addition, we perform a descriptive comparison of tools used in each step of RNA-seq data analysis along with a discussion of important characteristics of these tools. A taxonomy of tools is also provided. A discussion of issues in quality control and visualization of RNA-seq data is also included along with useful tools. Finally, we provide some guidelines for the RNA-seq data analyst, along with research issues and challenges which should be addressed.
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| http://dx.doi.org/10.1109/TCBB.2018.2873010 | DOI Listing |
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