Introduction to Next Generation Sequencing (NGS) Data Analysis and Pathway Analysis. Jenny Wu
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1 Introduction to Next Generation Sequencing (NGS) Data Analysis and Pathway Analysis Jenny Wu
2 Outline Introduction to NGS data analysis in Cancer Genomics NGS applications in cancer research Typical NGS workflows and pipeline Open source software with GUI Pathway Analysis and Software Pathway Analysis goals and concepts Commercial and open source pathway analysis software Data analysis resources Summary
3 Next Generation Sequencing Massively Parallel Sequencing: One can generate hundreds of millions of short sequences (up to 250bp) in a single run in a short period of time with low per base cost. Illumina/Solexa GA II, HiSeq 2500, 3000,X Roche/454 FLX, Titanium Life Technologies/Applied Biosystems SOLiD Reviews: Michael Metzker (2010) Nature Reviews Genetics 11:31 Quail et al (2012) BMC Genomics Jul 24;13:341.
4 NGS in Cancer Genomics Shyr et al.2013
5 Data Analysis in the bottleneck Informatics (wall.hms.harvard.edu)
6 Basic NGS Workflow Isolation of material PCR amplification End repair, size selection Library QC Cluster generation Instrument operation QC and pipeline analysis Data interpretation Olson et al.
7 High Throughput Data Analysis Overview Olson et al.
8 Many Analysis Pipelines Start with Read Mapping Typical Data Analysis Pipelines Genotyping (GATK) RNA-seq (Tuxedo)
9 Cancer NGS Data Analysis Pipeline-Software Raw reads FASTQC, FASTXtoolkit, Trimmomatic Analysis-ready reads BWA, STAR Visualization (IGV, IGB, USCS GB ) Mapped reads Data Task Software
10 Cancer NGS Application Specific Software Mapped reads SomaticSniper, VarScan2, mutect freebayes, Pindel, CNVnator Cufflinks, MISO DESeq2,GATK MACS2, SISSRs Bismark, BS Seeker
11 Open Source Software with GUI Galaxy: Web based platform for analysis of large datasets GENE-E: java based matrix visualization and analysis platform; includes heatmap, clustering, filtering etc.
12 Commercial software for NGS analysis Easy to use, no command line skills required Usually platform independent Little to no learning curve o Limited flexibility o Harder to publish
13 Outline Introduction to NGS data analysis in Cancer Genomics NGS applications in cancer research Typical NGS workflows and pipeline Open source software with GUI Pathway Analysis and Software Pathway Analysis goals and concepts Commercial and open source pathway analysis software Data analysis resources Summary
14 Why Pathway Analysis Logical next step in any high throughput experiments Goal: to characterize biological meaning of the joint changes in gene expression Why? Often group of genes doing related functions are changed
15 Pathway and Network Analysis Pathway Analysis Methods: Functional category over representation: discrete test for significance (BiNGO, David, IPA etc) Continuous test (GSEA, PAGE) Signaling Pathway Impact Analysis (ipathway Guide) Network Analysis: (WGCNA, Cytoscape etc)
16 Functional Category Enrichment Discrete tests: enrichment for groups in gene lists Select gene list at some predefined cutoff For each gene list and functional category cross-tabulate to get a 2X2 contingency table Test for significance using Fisher s exact test FDR correction for multiple hypothesis testing In the pathway Not in the pathway Differentially expressed Not differentially expressed total a b a+b c d c+d total a+c b+d n
17 Functional Categories in Pathway Analysis Gene Ontology Biological Process Molecular Function Cellular Localization Pathway Databases KEGG BioCarta Broad Institute (MSigDB) Commercial knowledge bases such as IPA Other Transcription factor targets Protein complexes Self-Defined
18 Commerical and Open Source Pathway Analysis Software
19 Ingenuity Pathway Analysis Tool
20 IPA Input file
21 IPA results page
22 Resources in NGS data analysis Public forums: Computational resources available at UCI: HPC: open source software CLCbio, IPA, JMP Genomics
23 Summary NGS technologies are transforming cancer research. Data analysis is a crucial part in NGS applications Pathway analysis concepts and software Data analysis resources Thank you!
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