From Reads to Result Reference VS Denovo RNA Seq
Master the transition from raw sequencing data to biological insights using state-of-the-art RNA-Seq analysis pipelines. Discover how to assemble and quantify transcriptomes from scratch without a reference genome using AI-driven bioinformatics tools.
- 4.0/5
- English
- Updated Aug 2026
About this course
In modern life sciences, transcriptomics serves as a critical bridge between genetic potential and actual cellular function. This comprehensive training workflow from Dr. Omics Labs provides a masterclass on navigating the complexities of both reference-based and de novo RNA-Seq workflows. Participants will explore the technical nuances of handling high-throughput transcriptomic datasets when a reference genome is completely unavailable. The training focuses heavily on practical, career-oriented bioinformatics strategies, teaching you to run quality control, perform transcript assembly, and execute differential gene expression algorithms. By integrating machine learning methodologies with computational sequence modeling, this webinar removes the guesswork from parsing massive raw fastq reads. Attendees will leave equipped with the professional framework required to select the optimal pipeline for non-model organisms, accelerating genomic discoveries across biotechnology and medical sectors.
What you will learn
Skills you will gain
Certification
Available
Issued by Dr. OmicsCourse curriculum
1 moduleWhat you need to start
- A basic foundational knowledge of molecular biology, transcription processes, and RNA functionality.
- General familiarity with working in computational environments or data science concepts (prior coding expertise is helpful but not mandatory).
Who this course is for
- Bioinformaticians & Data Scientists: Looking to master specialized transcriptomic pipelines and comparative sequence analysis.
- Plant, Marine, and Ecological Researchers: Working with non-model organisms that lack high-quality reference genomes.
- Molecular Biologists & Geneticists: Eager to transition their benchwork background into hands-on computational biology.
- Biotech Professionals: Seeking to deploy advanced automated workflows for structural biomarker discovery.