Galaxy workshop at the Winter School Igor Makunin
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1 Galaxy workshop at the Winter School 2016 Igor Makunin Winter school, UQ, July 6, 2016
2 Plan Overview of the Genomics Virtual Lab Introduce Galaxy, a web based platform for analysis nextgen sequencing data Workshop: RNA Seq analysis in Galaxy Tea break at 15:30 16:00 Igor Makunin UQ RCC Derek Benson UQ RCC Michal Lorenc QUT
3 Genomics Virtual Laboratory Analysis of nextgen sequencing data is a bottleneck (infrastructure, skills) Genomics Virtual Lab: take the IT out of Bioinformatics web based resources (biologists friendly) DIY bioinformatics environment (for geeks) GVL advantages: public resources (no charges to users) available immediately
4 GVL products and services Genomics Virtual Lab: genome.edu.au Info The main aim: facilitate the genomics research in Australia Galaxy: Tutorials and protocols (nextgen sequencing) Galaxy for tutorials: galaxy tut.genome.edu.au Galaxy for full scale analysis: galaxy qld.genome.edu.au roll your own Galaxy on the Australian government funded computer infrastructure (NeCTAR cloud) + ipython Notebook + RStudio Learn Use Get Deploy your own computer cluster (NeCTAR cloud) RStudio GenomeSpace
5 Galaxy: how does it look like Tools Top menu History Upload Working window
6 Galaxy: possibilities You can: analyze genome scale nextgen sequencing data without bash scripting work with big datasets, genomic regions, sequences etc. create and use Galaxy workflows (record steps of your analysis) share results and workflows with a user or make it available to anyone Private data: upload through the web interface ftp (for big datasets) transfer data between different Galaxy servers GenomeSpace Public data: UCSC Genome Browser EBA SRA Over 2,000 tools available through the Galaxy tool shed
7 Use: GVL GenomeSpace Data centric environment. Export or import data from different depositories
8 Use: local Galaxy qld server GVL Galaxy in Queensland: galaxy qld.genome.edu.au/galaxy Tools: BWA, bowtie2 Velvet (microbial genome assembly) Trinity (de novo transcript assembly) tophat2, RNA_STAR (RNA Seq) DESeq, edger, Cufflinks (differential gene expression) GATK2, variant detection tools Metagenomics tools MACS2, SPP (ChIP Seq) SAMtools Picard Local Blast+ search 100s users 1000s jobs per month 600 GB for Australian users Datasets: genome indices gene annotations
9 Bad user practice
10 Very bad user practice Do not delete jobs in fast succession!
11 Good user practice for Galaxy qld Read GVL FAQ page at genome.edu.au/help/faq Register with your institutional and get a bigger disk allocation. Save the results. The server does not have an external backup. Use ftp for big datasets it is faster. Galaxy recognises.gz compression. Do not store unneeded datasets. Delete temporary files such as SAM. Purge deleted datasets. Do not start many big jobs in parallel (BWA, bowtie, bowtie2, tophat2, velvet, trinity, rna_star). Create and use workflows for multi step analysis. Use small datasets to build a workflow. Specify the quality score encoding for FASTQ files.
12 FASTQ quality score ILLUMINA C32_FC:3:1:80:12/1 TAGCAGCACATCATGGTTTACATCGTATGCCGTCTT + IIHIDIIIIIIIIIIIIIHIHIIIIIDGIBGGGGGG Qual. = 40 Offset = = 73 ASCII(73): I
13 FASTQ quality score in Galaxy Many old illumina datasets have a proprietary data encoding (offset 64) Currently most NGS datasets use Sanger encoding (offset 33) Galaxy By default Galaxy assign fastq data type to uploaded FASTQ files. In this case the offset is not specified, and many tools do not recognize the data fastqillumina old illumina quality score encoding (offset 64, illumina 1.3+) fastqsanger new illumina 1.8+ / Sanger quality score encoding Nearly all modern NGS data use Sanger encoding (fastqsanger in Galaxy) Solution: specify a proper format, eg fastqsanger or fastqillumina, during the data upload change the format via Attributes > Datatype use NGS: QC and manipulation > FASTQ Groomer tool
14 Troubleshooting GVL FAQ page at genome.edu.au/help/faq Read the error report! Search for the error message. Report the error to the local Galaxy administrators.
15 Thank you! GVL site: Galaxy for tutorials: galaxy tut.genome.edu.au Galaxy Queensland: galaxy qld.genome.edu.au Contributors and participants:
16 Differential gene expression NextGen sequencing can be used for analysis of gene expression on a genome scale. Number of reads correlates with a transcript abundance. Gene expression Red 4 Brown 2 Green 1 mrna Library single end reads 5 vs 2
17 RNA Seq with the Cufflinks package Basic GVL Galaxy tutorial based on Trapnell et al. (2012) Nature Protocols Visualise alignments Data manipulation Galaxy workflow: create, edit, run
18 Setup for the workshop 1. Go to the GVL website: 2. Register on a personal GVL Galaxy The servers will be available for one week after the workshop.
19 Galaxy workflow History menu > Extract Workflow 1. Name the workflow 2. Uncheck all BAM files Keep the gene annotation file ensembl_dm3.chr4.gtf as input dataset Extracted workflows do not keep genome assembly for aligner tools. We will edit the workflow.
20 Workflow Edit 1. Delete one replicate per condition 2. Add Condition 1 input (or 2) in Annotation / Notes for tophat jobs 3. Check the assembly in tophat jobs 4. Rename the output in Filter Add Actions > Rename dataset 5. Save the workflow 6. Ran the workflow 7. Select FASTQ files from C1 and C2 (check the genome assembly) 8. Save the results into a new history
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