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Whole-Exome Sequencing Data – Identifying Somatic Mutations

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Springer Handbook of Bio-/Neuroinformatics

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Abstract

The use of next-generation sequencing instruments to study hematological malignancies generates a tremendous amount of sequencing data. This leads to a challenging bioinformatics problem to store, manage, and analyze terabytes of sequencing data, often generated from extremely different data sources. Our project is mainly focused on sequence analysis of human cancer genomes, in order to identify the genetic lesions underlying the development of tumors. However, the automated detection procedure of somatic mutations and the statistical testing procedure to identify genetic lesions are still an open problem. Therefore, we propose a computational procedure to handle large-scale sequencing data in order to detect exonic somatic mutations in a tumor sample. The proposed pipeline includes several steps based on open-source software and the R language: alignment, detection of mutations, annotation, functional classification, and visualization of results. We analyzed Illumina whole-exome sequencing data from five leukemic patients and five paired controls plus one colon cancer sample and paired control. The results were validated by Sanger sequencing.

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Abbreviations

ANNOVAR:

annotation of genetic variants

BAM:

binary alignment format

BC:

blast crisis

BWA:

Burrows–Wheeler alignment

BWT:

Burrows–Wheeler transform

CIRCOS:

circular visualization of tabular data

CML:

chronic myeloid leukemia

CNV:

copy number variation

DNA:

deoxyribonucleic acid

IGV:

integrative genomics viewer

INDEL:

insertion or a deletion

IPA:

ingenuity pathway analysis

LOH:

loss of heterozygosity

LRT:

linear regression technique

PDGFR:

platelet-derived growth factor receptor

PML-RAR:

promyelocytic leukemia-retinoic acid receptor

Ph:

Philadelphia chromosome

R:

R programming language

RTA:

real time analyzer

SAM:

sequence alignment map

SAMtools:

tools for sequence alignment maps

SCS:

sequencing control software

SIFT:

sorts intolerant from tolerant

SNP:

single-nucleotide polymorphism

SNV:

single nucleotide variant

UCSC:

University of California Santa Cruz

aCGH:

array-comparative genomic hybridization

aCML:

atypical chronic myeloid leukemia

ddNTP:

dideoxynucleotide

gDNA:

genomic DNA

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Author information

Authors and Affiliations

  1. Department of Health Science, University of Milano-Bicocca, via Cadore, 48, 20900, Monza, (MB), Italy

    Roberta Spinelli

  2. Department of Health Science, University of Milano-Bicocca, via Cadore 48, 20900, Monza, (MB), Italy

    Rocco Piazza

  3. Department of Health Science, University of Milano-Bicocca, via Cadore 48, 20900, Monza, (MB), Italy

    Alessandra Pirola

  4. Department of Health Science, University of Milano Bicocca, via Cadore, 48, 20900, Monza, (MB), Italy

    Simona Valletta

  5. Department of Health Science, University Milano Bicocca, via Cadore 48, 20900, Monza, Italy

    Roberta Rostagno

  6. Department of Health Science, Università di Milano Bicocca, via Cadore 48, 20900, Monza, (MB), Italy

    Angela Mogavero

  7. Institut für Neuropathologie, Justus-Liebig-Universität, Aulweg 123, 35392, Gießen, Germany

    Manuela Marega

  8. Department of Health Science, University of Milano Bicocca, via Cadore, 48, 20900, Monza, (MB), Italy

    Hima Raman

  9. Department of Health Science, University of Milano Bicocca, via Cadore 48, 20900, Monza, Italy

    Carlo Gambacorti-Passerini

Authors
  1. Roberta Spinelli
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  2. Rocco Piazza
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  3. Alessandra Pirola
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  4. Simona Valletta
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  5. Roberta Rostagno
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  6. Angela Mogavero
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  7. Manuela Marega
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  8. Hima Raman
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  9. Carlo Gambacorti-Passerini
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Corresponding authors

Correspondence to Roberta Spinelli , Rocco Piazza , Alessandra Pirola , Simona Valletta , Roberta Rostagno , Angela Mogavero , Manuela Marega , Hima Raman or Carlo Gambacorti-Passerini .

Editor information

Editors and Affiliations

  1. KEDRI – Knowledge Engineering and Discovery Research Institute, Auckland University of Technology, 120 Mayoral Drive, 1010, Auckland, New Zealand

    Nikola Kasabov

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Spinelli, R. et al. (2014). Whole-Exome Sequencing Data – Identifying Somatic Mutations. In: Kasabov, N. (eds) Springer Handbook of Bio-/Neuroinformatics. Springer Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30574-0_25

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  • DOI: https://doi.org/10.1007/978-3-642-30574-0_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30573-3

  • Online ISBN: 978-3-642-30574-0

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