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PSIchomics Shiny application for the integrated analysis of - - PowerPoint PPT Presentation

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PSIchomics Shiny application for the integrated analysis of alternative splicing from large transcriptomic datasets Nuno Agostinho Nuno Morais EuroBioC 6 Dec. 2016 laboratory 2016 2 Alternative Splicing Gene Exon 1 Exon 2 Exon 3

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PSIchomics 
 Shiny application for the integrated analysis of alternative splicing from large transcriptomic datasets

Nuno Morais laboratory Nuno Agostinho 6 Dec. 2016 EuroBioC 2016

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Introduction Workflow Case Study Testing Conclusions

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Alternative Splicing

Exon 1 Exon 2 Exon 3

Gene

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Introduction Workflow Case Study Testing Conclusions

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Alternative Splicing

Exon 1 Exon 2 Exon 3

Gene

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Introduction Workflow Case Study Testing Conclusions

Alternative Splicing

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Exon 1 Exon 2 Exon 3

Gene

  • Occurs in 95% of human multi-exon genes (Pan et al., 2009)
  • Involved in the control of many cellular processes (Oltean & Bates, 2014)
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Introduction Workflow Case Study Testing Conclusions

Alternative Splicing

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Studying alternative splicing changes may allow to identify prognostic factors and therapeutic targets

  • Occurs in 95% of human multi-exon genes (Pan et al., 2009)
  • Involved in the control of many cellular processes (Oltean & Bates, 2014)
  • Alternative splicing deregulation is linked with cancer development

(Oltean & Bates, 2014)

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Introduction Workflow Case Study Testing Conclusions

RNA Sequencing

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1 Exon 1 Exon 2 Exon 3 Extract RNA 3 Convert
 to DNA 2 Divide in fragments 4 Sequence DNA 5 Obtain reads 6 Map reads to DNA of reference Exon 2 Exon 3 Exon 1 Junction reads Exonic reads Reference DNA

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Introduction Workflow Case Study Testing Conclusions

Alternative Splicing Quantification

Alternative splicing annotation Junction read counts

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Percent Spliced-In (PSI) = inclusion reads inclusion + exclusion reads

Distribution of PSI values

0.4 0.1 0.2 0.3 0.5 0.6 0.7 0.8 0.9 1 2 4

Median: 0.82 Variance: 0.05 Median: 0.17 Variance: 0.06 Mann–Whitney U test's p-value (FDR): 2.28e-07

ACTN1 (exon 19)

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Introduction Workflow Case Study Testing Conclusions

Quantification and Analytical Tools

  • Many programs quantify, analyse and visualise alternative

splicing data

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MISO rMATS VAST-TOOLS SUPPA jSplice AltAnalyze SpliceSeq TIN SGSeq splicegear JunctionSeq DRIMSeq SeqGSEA spliceR DEXSeq Cufflinks FineSplice JuncBASE Splicing Compass

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Introduction Workflow Case Study Testing Conclusions

Quantification and Analytical Tools

  • Many programs quantify, analyse and visualise alternative

splicing data

  • No standard pipeline
  • Their problems range from…

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No user-friendly interfaces in most tools Time-consuming quantification of alternative splicing No incorporation of clinical information Over-simplistic analyses or focus in the quantification step

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Introduction Workflow Case Study Testing Conclusions

PSIchomics

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Quantify, analyse and visualise alternative splicing in cancer data Incorporate clinical information Modular architecture to easily modify and extend the program Visual and 
 command-line 
 interfaces

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Introduction Design decisions Implementation Testing Conclusions

  • Open-source, free and cross-platform functional language
  • Ideal for statistics, data manipulation and graphical

computation

  • Used by the scientific community

Choosing as the language

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  • Web app framework using R, HTML, CSS

and JavaScript

  • Reactive programming model (Excel-like

reactivity)

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Workflow

Introduction Workflow Case Study Testing Conclusions

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Introduction Workflow Case Study Testing Conclusions

Alternative Splicing Quantification

Alternative splicing annotation Junction read counts

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Percent Spliced-In (PSI) = inclusion reads inclusion + exclusion reads

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Introduction Workflow Case Study Testing Conclusions

! " #

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Alternative splicing annotation

  • Human (hg19 assembly) annotation is

available

  • Custom annotation files may be created
  • Alt. Splicing

Quantification Analyses and Visualisation Data Retrieval

Clinical data Junction read counts

  • Data is downloaded in-app using

Firebrowse web API

(data from human tumours)

The Cancer Genome Atlas

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Introduction Workflow Case Study Testing Conclusions

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!

  • Alt. Splicing

Quantification Analyses and Visualisation Data Retrieval

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Quantify 
 alternative splicing Retrieve TCGA data
 (optional)

Junction 
 read counts

  • Alt. splicing

annotation

provided or prepared by user

Percent Spliced-In (PSI) = inclusion reads inclusion + exclusion reads

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Introduction Workflow Case Study Testing Conclusions

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! " #

  • Alt. Splicing

Quantification Analyses and Visualisation Data Retrieval

Differential splicing analysis Gene, RNA and protein information Principal component analysis Survival analysis

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Introduction Workflow Case Study Testing Conclusions

  • Vast array of customisable and interactive plots
  • Features tooltips, zooming and plot exporting

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Survival curves Density plots

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  • Alt. Splicing

Quantification Analyses and Visualisation Data Retrieval

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Case Study

Introduction Workflow Case Study Testing Conclusions

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PCA: dimensionality reduction by selecting the main directions of variance

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Testing

Introduction Workflow Case Study Testing Conclusions

$ % &

Performance
 Benchmarking Continuous and
 Unit Testing Usability
 Testing

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Introduction Workflow Case Study Testing Conclusions

Breast cancer (1093 patients) Pan-kidney cohort (889 patients) Glioma cohort (676 patients) Liver cancer (371 patients) Running time (with default settings) 30s 1m 1m 30s 2m 2m 30s 3m 3m 30s 4m 4m 30s 5m 5m 30s 6m 6m 30s 2m 20s 2m 37s 2m 34s 2m 35s 35s 1m 20s 2m 2s 2m 39s 16s 33s 22s 47s

Load data Quantify AS (skipped exon) Differential analyses (Normal vs Tumour)

  • Common tumour types were selected from TCGA
  • Average time was collected over 10 consecutive runs

28 MacBook Pro 2011:
 i7 (8 cores), HDD and 8GB RAM

$ % &

Performance
 Benchmarking Continuous and
 Unit Testing Usability
 Testing

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Conclusions

Introduction Workflow Case Study Testing Conclusions

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Introduction Workflow Case Study Testing Conclusions

Conclusions

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6 minutes using processed data with the highest number of patients in TCGA Quantify, analyse and visualise alternative splicing in cancer data Incorporates clinical information Modular architecture to easily modify and extend the program Command-line and easy-to-use graphical interface

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Introduction Workflow Case Study Testing Conclusions

Future work

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' ( )

  • Extend available data sources
  • Quantify alternative splicing from raw data
  • Less dependence on processed data
  • Deploy to the web
  • No installation required
  • Always up-to-date
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GitHub Code hosting Bioconductor Biological R packages

PSIchomics

(MIT license)

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Thanks to you all!

Nuno Morais Lab André Falcão Ana Rita Grosso