RNA-seq Analyses in non-model organisms



18th-22nd November 2024


To foster international participation, this course will be held online




Course overview

RNA-Seq technology has been transformative in our ability to explore gene content and gene expression in all realms of biology, and de novo transcriptome assembly has enabled opportunities to expand transcriptome analysis to non-model organisms. This workshop provides an overview of modern applications of transcriptome sequencing and popular tools and algorithms for exploring transcript reconstruction and expression analysis in a genome-free manner, leveraging the Trinity software and analysis framework. Attendees will perform quality assessment of Illumina RNA-Seq data, assemble a transcriptome using, among others, Trinity, quantify transcript expression, leverage Bioconductor tools for differential expression analysis, and apply Trinotate to functionally annotate transcripts. In parallel to the short-read assembly, participants will use 3rd generation sequencing data (PacBio IsoSeq) to perform a hybrid long-read short-read assembly, then compare the assemblies together. Additional methods will then be explored for characterizing the assembled transcriptome and revealing biological findings.

Intended audience

This workshop is aimed primarily at biologist researchers that have basic bioinformatics skills (basic knowledge of the linux command line interface is a must, basic knowledge of the R environment and language is strongly recommended) and are pursuing RNA-Seq projects in non-model organisms. Attendees will gain skills needed to successfully approach transcriptome sequencing, de novo transcriptome assembly, expression analysis, and functional annotation as applied to organisms lacking a high quality reference genome sequence. Attendees are also invited to bring a subset of their own data. Familiarity with Linux and R is essential for benefitting from the workshop.


Teaching format

The workshop will be delivered over the course of four and a half days, with each session entailing lectures followed by practical hands-on sessions. Most computing will be done on the cloud and attendees will use their own laptop computers with the Google Chrome web browser providing all the necessary interfaces to the cloud computing environment, including the linux command terminal. Attendees can also use the native terminal emulator of their Operating System (and ssh). This works natively for Linux, MAC and Windows 10 and 11. For Windows 7 users, installing Visual Studio Code (alternatively MobaXterm) is recommended.

Assumed background for the participants

Basic experience with the linux command-line is essential. Experience with the execution of bioinformatics tools using the linux command line will be helpful. Experience with the R environment and running R code (not writing!) also. No programming or scripting knowledge is required (but some is helpful). As a matter of fact, being able to write short bash scripts is one of the learning objectives.


Session content

Monday – Classes from 2-8 pm Berlin time - High Throughput Sequencing, 2nd generation

    14:00 - 14:30 - Welcome to the course!
    Daily Learning Objectives
    14:30 - 15:10 - High Throughput Sequencing Lecture
    15:10 - 15:30 - Data Preprocessing Workflow Lecture
    15:30 - 16:30 - Data pre-processing discussion
    16:30 - 17:00 - Data description
    17:10 - 19:40 - Hands-on practical data pre-processing
    19:40 - 20:00 - Feedback and Daily Assessment

Monday – Classes from 2-8 pm Berlin time -  NGS data de-novo transcriptome assembly

    Daily Learning Objectives
    14:00 - 14:30 - Revision session
    14:30 - 16:30 - Hands-on practical data pre-processing
    Input QC tutorial
    16:30 - 19:40 - De-novo transcriptome assembly lecture and tutorial
    Input Transcriptome Assembly
    19:40 - 20:00 - Feedback and Daily Assessment

Wednesday – Classes from 2-8 pm Berlin time - Third(!) generation sequencing, de-novo transcriptome assembly, assessment and evalutation

    14:00 - 14:40 - De-novo transcriptome assembly lecture and tutorial
    Input Transcriptome Assembly
    - Data description
    Daily Learning Objectives
    14:40 - 15:00 - Revision session
    15:00 - 15:20 - De-novo transcriptome assembly lecture - 3rd generation sequencing!
    15:20 - 16:00 - De-novo transcriptome assembly - revisited
    16:10 - 17:40 - Assembly evaluation
    Transcriptome evaluation
    17:40 - 19:40 - Functional annotation
    Transcriptome annotation
    19:40 - 20:00 - Feedback and Daily Assessment

Thursday – Classes from 2-8 pm Berlin time -  Transcript quantification and Differential Expression

    14:00 - 14:30 Transcriptome annotation
    Daily Learning Objectives
    14:30 - 15:00 - Revision session
    15:00 - 15:30 - Pseudo-alignment
    15:30 - 16:30 - R refresher and data science teaser
    16:30 - 19:15 - Exploratory Data Analysis (a.k.a. Biological Quality Assessment)
    19:15 - 19:40 - Git crash course
    19:40 - 20:00 - Feedback and Daily Assessment

Friday – Classes from 2-8 pm Berlin time -  Differential expression analysis

    Daily Learning Objectives
    14:10 - 15:00 - Exploratory Data Analysis (a.k.a. Biological Quality Assessment)
    15:00 - 15:45 - Git crash course
    15:45 - 19:00 - Differential Expression analysis
    19:00 - 20:00 - Final discussion session and Feedback


Dr. Nicolas Delhomme









Dr. Kristina Benevides



Cost overview

Package 1

530 €

Cancellation Policy:


> 30  days before the start date = 30% cancellation fee

< 30 days before the start date= No Refund.


Physalia-courses cannot be held responsible for any travel fees, accommodation or other expenses incurred to you as a result of the cancellation.