Streamlining Quantitative Analysis of Long RNA Sequencing Reads.

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Transcriptome analysis links RNA expression to cellular functions but can be time-consuming, especially with long-read sequencing.
• Existing software solutions for RNA sequencing data analysis are often not cost- or time-efficient, particularly for non-human datasets.
• There is a need for user-friendly, quantitative tools for transcriptome analysis, especially for long RNA reads.

Purpose of the Study:

• To develop a user-friendly tool, Alignator, for rapid analysis of long RNA reads.
• To provide a cost- and time-efficient workflow for transcriptome analysis.
• To generate quantitative information for transcript analysis and facilitate comparative studies.

Main Methods:

• Developed Alignator, a software tool for analyzing long RNA reads.
• Utilized FASTQ files and an Ensembl cDNA database as input.
• Implemented a mapping process to align sequenced RNA reads to a reference database.

Main Results:

• Alignator successfully maps long RNA reads.
• The tool generates quantitative expression information for each transcript.
• Output includes a table for comparative analysis of sequenced and aligned RNA.

Conclusions:

• Alignator offers a rapid, user-friendly solution for long RNA read transcriptome analysis.
• The tool enhances quantitative analysis and facilitates comparative transcriptomics.
• Alignator addresses the need for efficient, accessible RNA sequencing data analysis tools.