GLIOTRAIN ESRs attended the Transcriptomics and Single Cell RNA-Seq Analysis Course held at VIB in August 2018. Following the course, ESRs were asked to work together to review the event, which you can read below.
Day 1 ESR Report
The first day the course focussed on R and Linux command line, which are the preparation courses for bioinformatics beginners. ESRs learnt command line features, Linux file system commands, building and executing scripts. Using Rstudio they were taught to work with basic syntax, logical operators, variable assignment, script editor and making basic geometric plots (e.g. histogram, scatter plot, rectangles, etc.). All the courses included theory session and hands-on session (exercises), which provided students with a better view of bioinformatics.
Day 2 ESR Report
Today the course focussed on methods for RNA-seq and in particular Illumina. The workflow for analyzing RNA-seq data starts with Quality control of the sequences using the FASTQC software which gives an overview of the characteristics of the sequences, and in particular "per base sequencing quality", "per sequence quality scores", "per tile sequence quality", and "over-represented sequences". ESRs learnt how to improve the quality of the data using Trimmomatic. Finally, the use of mapping in order to be able to map the reads to a genome of reference was reviewed. This involved the software STAR, SAMTOOLS, RSEQC, IVG. Subsequently, in a "hands-on" element of the workshop, these methods were applied using datasets provided by VIB.
Day 3 ESR Report
Being exposed for the first time to huge data analysis and bioinformatics was an interesting chance for the ESRs to understand the basics of using programs like R Studio to analyse the differential expressions of data sets. Thus, the third day of the summer school started with an introduction of the command lines that could be used in R Studio. The lectures focused on the command lines that could be used in R Studio and how data could be analysed and the results plotted. Following the R Studio session, ESRs were referred to introductory information about the analysis of variants in the context of gene expression measured in tissues, which has been known to have a big impact in health and disease. By studying such variants quantitatively it may be possible to explain the behaviour of glioblastoma tumour cells in the diseased individuals.
Day 4 ESR Report
Mike Stubbington, staff computational biologist from 10x Genomics, introduced ESRs to single cell RNA-sequencing (scRNAseq). In particular, he explained both the experimental and computational analysis pipeline, providing us different options and examples. In addition, ESRs individually followed the Loupe Cell Browser gene expression tutorial provided by 10x Genomics, in order to identify significant genes and functional cell (sub)types within a real-world dataset. In the afternoon, ESRs were introduced to scRNAseq data analysis using Seurat pipeline, exploited for quality control using tSNE plots, PCA and heatmaps. Moreover, the course introduced another package called Cellranges that converts BCL files (from the sequencer) to FASTQ files for the analysis.
Day 5 ESR Report
Today was focussed on Trajectory analysis, SCENIC, Omics data integration, followed by a question and answer session about integrating RNA seq analysis into individual experiment design.
Trajectory analysis describes the course of a measured variable over age or time. This analytical technique allows us to create a trajectory to visualise clusters of genes, enabling us to predict and visualize specific genes of interest. SCENIC is a workflow in R to infer gene regulatory networks and identify cell states from single-cell RNA-seq data. During the practical workshop, ESRs explored the uses of SCENIC with particular interest in providing critical biological insights into the mechanisms driving cellular heterogeneity. The final session focused on Omics data integration. Two speakers explained the stages involved in integrating functional genomics data and from this, integrating RNA-seq with other omics data.
Day 6 ESR Report
On the final day, ESRs spent the day analysing their individual Bulk RNA-seq or Single cell RNA-Seq datasets. This session was extremely helpful, combining the knowledge and techniques learnt throughout the week to successfully troubleshoot and produce analysed data.