RNA-Seq tutorial materials - slides, training data, code lines Training materials -

ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR458/ERR458500/ERR458500.fastq.gz

ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR458/ERR458501/ERR458501.fastq.gz

ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR458/ERR458502/ERR458502.fastq.gz

ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR458/ERR458493/ERR458493.fastq.gz

ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR458/ERR458494/ERR458494.fastq.gz

ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR458/ERR458495/ERR458495.fastq.gz

curl -O http://downloads.yeastgenome.org/sequence/S288C_reference/orf_dna/orf_coding.fasta.gz

https://beta.etherpad.org/p/H9l6EdbQfR

TENTATIVE CURRICULUM

RNA-Seq workshop Otago

Linux for Bioinformatics Introduction to the command line and important commands Combining commands by piping and redirection Introduction to bioinformatics file formats (e.g. FASTA, BED, VCF, WIG) and databases (e.g. UCSC, ENSEMBL) Usage of important bioinformatics toolkits (BEDtools, UCSCtools) Introduction to R Creating virtual labs with Aleksandra Pawlik 1.5 Genomics of RNA-Seq analysis Basics of experiment design with Erica Todd Best practices and tips and tricks for TruSeq stranded total RNA library preparation (Aaron?) Best practices of sequencing library validation

2. Introduction to NGS data analysis Introduction to sequencing technologies from a data analysts view Raw sequence files (FASTQ format) Preprocessing of raw reads: quality control (FastQC), adapter clipping, quality trimming Introduction to read mapping (Alignment methods, Mapping heuristics) Read mapping (BWA, Bowtie2, STAR, hisat2) Mapping output (SAM/BAM format) Usage of important NGS toolkits (samtools, BEDtools) Mapping statistics Visualization of mapped reads (IGV, UCSC, Tablet) Training material could be taken from here: ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR458/ (yeast data, 2 conditions (mt,mt,mt, wt,wt,wt) Alternative dataset is here: https://zenodo.org/record/61765#.We6iIBOCzVE

3. RNA-seq Data Analyses Understand split-read mapping Run different split-read mappers (tophat, hisat2, STAR) Understand the Tuxedo Suite (cufflinks, cuffcompare, cuffmerge, cuffdiff, etc.) Predict new transcripts/isoforms using cufflinks/cuffmerge Quantify exons/genes/transcripts Predict Differential exon usage using DEXseq/DEXSeq2 Differential gene expression using DEseq/DEseq2 Map or pseudomap? Differential isoform expression using cuffdiff

4. Representing you results

Ggplot2 Gviz Types of vizual data representation Making reports with knitr and Rmarkdown

We will be using an instance of Genomics Virtual Lab which will run on the University of Auckland NeCTAR Node - supported by the Centre for eResearch.

• NeCTAR (National eResearch Collaboration Tools and Resources) is a federated research cloud hosted in 7 Australian institutions, and is now a pilot service at University of Auckland.
• NeCTAR provides virtual computing resources, virtual labs (such as the one used in this workshop), scientific clouds, and collaborative workflows to assist researchers.
• If you are a postgraduate or staff researcher at UoA and would like to get on board (free of charge), please contact Centre for eResearch Staff: [email protected]