TY - JOUR
T1 - Computational characterization of cancer molecular profiles derived using next generation sequencing
AU - Oleksiewicz, Urszula
AU - Tomczak, Katarzyna
AU - Woropaj, Jakub
AU - Markowska, Monika
AU - Stȩpniak, Piotr
AU - Shah, Parantu K.
PY - 2015
Y1 - 2015
N2 - Our current understanding of cancer genetics is grounded on the principle that cancer arises from a clone that has accumulated the requisite somatically acquired genetic aberrations, leading to the malignant transformation. It also results in aberrent of gene and protein expression. Next generation sequencing (NGS) or deep sequencing platforms are being used to create large catalogues of changes in copy numbers, mutations, structural variations, gene fusions, gene expression, and other types of information for cancer patients. However, inferring different types of biological changes from raw reads generated using the sequencing experiments is algorithmically and computationally challenging. In this article, we outline common steps for the quality control and processing of NGS data. We highlight the importance of accurate and application-specific alignment of these reads and the methodological steps and challenges in obtaining different types of information. We comment on the importance of integrating these data and building infrastructure to analyse it. We also provide exhaustive lists of available software to obtain information and point the readers to articles comparing software for deeper insight in specialised areas. We hope that the article will guide readers in choosing the right tools for analysing oncogenomic datasets.
AB - Our current understanding of cancer genetics is grounded on the principle that cancer arises from a clone that has accumulated the requisite somatically acquired genetic aberrations, leading to the malignant transformation. It also results in aberrent of gene and protein expression. Next generation sequencing (NGS) or deep sequencing platforms are being used to create large catalogues of changes in copy numbers, mutations, structural variations, gene fusions, gene expression, and other types of information for cancer patients. However, inferring different types of biological changes from raw reads generated using the sequencing experiments is algorithmically and computationally challenging. In this article, we outline common steps for the quality control and processing of NGS data. We highlight the importance of accurate and application-specific alignment of these reads and the methodological steps and challenges in obtaining different types of information. We comment on the importance of integrating these data and building infrastructure to analyse it. We also provide exhaustive lists of available software to obtain information and point the readers to articles comparing software for deeper insight in specialised areas. We hope that the article will guide readers in choosing the right tools for analysing oncogenomic datasets.
KW - Next generation sequencing
UR - http://www.scopus.com/inward/record.url?scp=84981283772&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84981283772&partnerID=8YFLogxK
U2 - 10.5114/wo.2014.47137
DO - 10.5114/wo.2014.47137
M3 - Review article
C2 - 25691827
AN - SCOPUS:84981283772
SN - 1428-2526
VL - 1A
SP - A78-A91
JO - Wspolczesna Onkologia
JF - Wspolczesna Onkologia
ER -