Transcriptome Analysis for Non-Model Organisms

PrerequisitesNew

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 course 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.

Attendees will perform quality assessment and upstream analysis of both Illumina and long reads single molecule sequencing data; the derived transcriptomes will be compared, annotated and used as reference for quantifying transcript expression, leveraging on Bioconductor tools for differential expression analysis. Additional methods will be explored for characterising the assembled transcriptome and revealing biological findings.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

• Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
• Please be aware that these courses are only free for registered University of Cambridge students. All other participants will be charged a registration fee in some form. Registration fees and further details regarding the charging policy are available here.
• Further details regarding eligibility criteria are available here

• This workshop is aimed primarily at researchers that have basic bioinformatics skills and are pursuing RNA-Seq projects in non-model organisms.
• Basic experience of command line UNIX. Sufficient UNIX experience might be obtained from the following UNIX tutorial
• Basic knowledge of the R syntax. We recommend either attending Introduction to R for biologists, or working through the materials of the now discontinued An Introduction to Solving Biological Problems with R or Data Carpentry in R courses before attending this course.

Number of sessions: 3

Bioinformatics, Functional genomics, Data visualisation, Transcriptomics, Data handling, Data mining, RNA-seq

After this course you should be able to:

• Understand the challenges associated with long read data
• Compare assemblies derived from Illumina and third generation sequencing data
• Perform pseudo-mapping and quantification of expression using state of the art solutions
• Utilise some of the tools available in Bioconductor for differential expression analysis
• Produce a functionally annotated list of differentially expressed genes

During this course you will learn about:

• The use of third generation sequencing for transcript reconstruction and expression analysis in non-model organisms
• de novo assembly, assembly QC and expression quantitation
• Differential expression analysis using Bioconductor
• Functional annotation and functional enrichment studies

Presentations, demonstrations and practicals

• Free for registered University of Cambridge students
• £ 50/day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 50/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 100/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

2.5

Once a year

• Introduction to R for Biologists (IN-PERSON)
• CRUK: Data Carpentry in R
• Analysis of bulk RNA-seq data (IN-PERSON)
• Analysis of single cell RNA-seq data (IN-PERSON)
• Analysis of DNA Methylation using Sequencing (IN-PERSON)