support whole-exome sequencing experiments design and data - - PowerPoint PPT Presentation

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support whole-exome sequencing experiments design and data - - PowerPoint PPT Presentation

Jul 21, 2023 256 likes •421 views

An integrated annotation system to support whole-exome sequencing experiments design and data management Ivan Limongelli, Angelo Nuzzo, Annalisa Vetro, Erika Della Mina, Roberto Ciccone, Orsetta Zuffardi, Riccardo Bellazzi IRCCS C. Mondino,

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UNIVERSITÀ DI PAVIA

An integrated annotation system to support whole-exome sequencing experiments design and data management

Ivan Limongelli, Angelo Nuzzo, Annalisa Vetro, Erika Della Mina, Roberto Ciccone, Orsetta Zuffardi, Riccardo Bellazzi

IRCCS C. Mondino, Pavia Dipartimento di Genetica Medica Dipartimento di Informatica e Sistemistica

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Exome Sequencing – Analysis Workflow

Primary Analysis Nucleotide sequences (short reads) Reads Mapping Mapping Analysis

Reference genome sequence

?

Secondary Analysis

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Exome Sequencing – Secondary Analysis

SNVs Short In-dels

  • Variants Detection
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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Variants Annotation

chr1 , 153170600 , A>G , NM_015383, NBPF14, I >R , ….

Does this variant affect the product (protein structure and function) coded in this region?

Public bio-databases

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Variants Prediction

  • Some open tools addressing this aim:
  • Polyphen2, Mutation Taster , SIFT, Annovar,

Sequence variant Analyzer

  • Suitable for loss-of-function mutations
  • Score assignment to each mutation

corresponding to its probability to damage protein

  • Principally based on type of amino acid

substitution, conservation across species, polymorphisms databases

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Data management

  • Some considerations
  • Illumina GAIIx platform: max 8 whole-exome

samples sequenced in each experiment

  • 13-18K variants per sample (SNVs/Indels) are

detected, but about 95% of them are common variants

  • Needs
  • I would like to easily perform cross-samples

and cross-experiments analysis

  • I would NOT like to annotate and predict

changes again for previously (already annotated) identified variants

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Data management

Output by software device manufacturer

Pipeline 1 Pipeline 2 Pipeline N ….

MiddelWare

(data uploads)

DB

Applications Module

  • omics DB

Functional prediction Tools

Synchronising

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Data management

Step 1: create experiment Step 1: create experiment

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Data management

Step 2: choose experiment to add a sample

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Data management

Step 3: create sample Step 4: upload mutation data for that sample

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Data management

Step 5: select cases/controls

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Data management

Step 5: filtering parameters setup

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Data management

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Data management

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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

Secondary Analysis – Data management

  • Current prototype implementation

allows to:

  • Store experiments and samples data
  • Store identified variants (SNVs/Indels) and

their reliability parameters (VCF 4.0 currently supported)

  • Annotate variants
  • Predict their probability to damage protein

and store results (Polyphen2, Mutation Taster, SIFT)

  • Control-case studies modelling
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Angelo Nuzzo IIT@SEMM, Milan, 2011 NETTAB, Pavia, 2011 Ivan Limongelli

The end.. Thank you for your attention!