Next Generation Sequencing Data Analysis with BioHPC. Updated for

Transcription

1 Next Generation Sequencing Data Analysis with BioHPC 1 Updated for

2 Next Generation Sequencing Genomic, transcriptomic sequencing now commonplace in projects. Now very cheap! UTSW McDermott Core typical pricing: Whole Genome PE100 $7,500 Whole Transcriptome PE100 $875 Most common experiment across the University: Use RNA-Seq to identify gene expression changes in response to a stimulus / caused by a disease. Let s focus on this today but you can do other things on our systems! 2

3 Typical RNA Seq Workflow A B Prepare/ Obtain Samples for different conditions Extract RNA and prepare library for sequencing Run library on Illumina sequencer Obtain short-read sequences 3

4 Typical RNA Seq Workflow Data Analysis Check quality and/or filter reads Align to the genome or transcriptome Quantify transcript abundance across conditions Identify significant differences in expression between conditions 4

5 Why Use BioHPC? Powerful processing and lots of storage! 72 x 32/48 core nodes to run mapping that can take days on a PC. >1Petabyte of storage. No need to shuffle data between drives when working on large projects. Storage is fast. Best at the things NGS analysis does most (accessing large files sequentially) Tools to help you! NGS Pipeline Galaxy Batch Scripts Standard workflows with little effort. Best for beginners. Powerful environment with many tools, workflow designer. Various NGS tools available as modules on the cluster, for expert users. 5

6 But the sequencing core does it for me. This is NOT an attempt to replace comprehensive services that a sequencing core provides, where data analysis is performed as part of the sequencing service. But Now common to need to integrate existing public data into projects Common to obtain data from collaborators, outside facilities Labs often have students/postdocs who have received NGS analysis training More flexibility many tools available to create complex pipelines Use our services with caution. You *should* have a basic understanding of the limitations of the techniques. 6

7 Option 1 - BioHPC NGS Pipeline BioHPC Portal -> Cloud Services -> NGS Pipeline (ngs.biohpc.swmed.edu) Common workflows, made easy. Currently RNA-SEQ Differential Expression Analysis 7

8 Option 2 - BioHPC Galaxy Service BioHPC Portal -> Cloud Services -> Galaxy (galaxy.biohpc.swmed.edu) Reproducible workflows, with many available tools, via the web. Widely used by many institutions. 8

9 Option 3 - Modules and Sequence Data / Indices module avail /project/apps_database/igenomes Common NGS tools and Illumina igenome databases are available on the cluster Experts can write their own pipelines using cluster sbatch jobs 9

10 Today we are going to Follow a simple and real-world RNA-SEQ differential expression analysis using: The BioHPC NGS Pipeline BioHPC Galaxy Service Try it out with your own data! biohpc-help@utsouthwestern.edu with questions Bring your problems to the BioHPC drop-in coffee session next week! 10

11 Example 1 Brain vs Adrenal A toy example I can show you in real time (hopefully!) 75,000 reads from chr19, extracted from a larger study 2 Conditions brain tissue vs adrenal tissue What s the difference in expression for the limited number of transcripts we can see in this data? Courtesy Galaxy Project, Illumina Body Map: 11

12 Example 2 HIF1α, HIF2α Single and Double sirna knock-down in MCF7 Cells A real study from a lab I used to work in. Public data downloaded via EMBL-EBI ArrayExpress. Extensive regulation of the non coding transcriptome by hypoxia: role of HIF in releasing paused RNApol2 Hani Choudhry, Johannes Schödel, Spyros Oikonomopoulos, Carme Camps, Steffen Grampp, Adrian L Harris, Peter J Ratcliffe, Jiannis Ragoussis, David R Mole DOI /embr Published online EMBO reports (2014) 15, We ll take 4 conditions, all samples MCF7 cells subjected to hypoxia: Control (scrambled sirna) HIF1A knock-down by sirna HIF2A knock-down by sirna HIF1A + HIF2A double knock-down by sirna 2 replicates for each condition. Illumina HiSeq platform. 12

13 13 TopHat / Cufflinks Pipeline

14 NGS Pipeline Demo See Handouts 14

15 Galaxy Demo See Handouts 15

16 Acknowledgements NGS Pipeline Developed by Yi Du in conjunction with CRI, Zhiyu Zhao. Galaxy Many thanks to John Chilton, Martin Chech, Nicola Soranzo, Andrew Robinson, Dannon Baker for assistance incorporating BioHPC required changes into the Galaxy project. 16