Training Data Sets: Streamlining mRNA-Seq Data Preprocessing and Statistical Analysis: A Rapid Protocol Empowering Insightful Exploration within a Richly Annotated Biological Context

Abstract

mRNA-seq is a powerful tool that provides comprehensive insights into gene expression and regulation, thereby advancing our understanding of biology and contributing to various fields such as medicine and agriculture. The complexity of RNA-seq analysis for biologists arises from the challenge to combine experimental biology with technical and computational skills, underscoring the need for interdisciplinary expertise. To enable integrating bioinformatics and robust analytical frameworks for extracting meaningful insights from RNA-seq experiments and answering biological questions, I introduce here a streamlined mRNA-Seq data preprocessing pipeline. The protocol, executed mainly through sequential execution of the provided bash scripts in the Linux console, encompasses decompression, quality and adapter trimming, quality control, alignment of the reads and transcript quantification. The implementation necessitates only basic knowledge of the Linux shell, making it accessible equally to novice and bioinformatically inexperienced senior scientists. Additionally, the provided R script automatically performs basic statistical data analyses with the newly generated data in RStudio, yielding all the important tables and figures that form an excellent starting point for creating the relevant charts and/or further analyses. Thus, the here-described method is designed for easy, rapid and efficient RNA-seq data extraction, requiring minimal expertise in bioinformatics.

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Keywords

dataset, mRNA-Seq, RNA-Seq, preprocessing, pre-processing, integrity, trimming, quality control, fastqc, trimmomatic, kallisto, RStudio, R, analysis, statistics

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