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Incorporating computational resources in a cancer research program

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Abstract

Recent technological advances have transformed cancer genetics research. These advances have served as the basis for the generation of a number of richly annotated datasets relevant to the cancer geneticist. In addition, many of these technologies are now within reach of smaller laboratories to answer specific biological questions. Thus, one of the most pressing issues facing an experimental cancer biology research program in genetics is incorporating data from multiple sources to annotate, visualize, and analyze the system under study. Fortunately, there are several computational resources to aid in this process. However, a significant effort is required to adapt a molecular biology-based research program to take advantage of these datasets. Here, we discuss the lessons learned in our laboratory and share several recommendations to make this transition effective. This article is not meant to be a comprehensive evaluation of all the available resources, but rather highlight those that we have incorporated into our laboratory and how to choose the most appropriate ones for your research program.

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Abbreviations

AP-MS:

Affinity purification coupled to mass spectrometry

ENCODE:

Encyclopedia of DNA Elements

FANTOM:

Functional Annotation of the Mammalian Genome

HCIP:

High-confidence interacting proteins

ICGC:

The International Cancer Genomics Consortium

MIAME:

Minimal information about microarray experiments

NSAF:

Normalized spectral abundance factor

pSNVs:

Single-nucleotide variants in phosphorylation sites

SAINT:

Significance analysis of interactome

TCGA:

The Cancer Genome Atlas

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Acknowledgments

Work in the Monteiro Lab is funded by NIH awards U19 CA148112 (GAME-ON consortium), U01 CA116167, R21 CA184996 (to N.W.) and by awards from the Moffitt Foundation, from the Department of Defense National Functional Genomics Center, and from the Anna Valentine Cancer Fund.

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Authors and Affiliations

  1. Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, 12902 Magnolia Drive, Tampa, FL, 33612, USA

    Nicholas T. Woods, Ankita Jhuraney & Alvaro N. A. Monteiro

  2. Department of Oncological Sciences, Morsani College of Medicine, University of South Florida, Tampa, FL, USA

    Nicholas T. Woods

  3. Cancer Biology Ph.D. Program, University of South Florida, Tampa, FL, USA

    Ankita Jhuraney

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  1. Nicholas T. Woods
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  2. Ankita Jhuraney
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Correspondence to Alvaro N. A. Monteiro.

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Woods, N.T., Jhuraney, A. & Monteiro, A.N.A. Incorporating computational resources in a cancer research program. Hum Genet 134, 467–478 (2015). https://doi.org/10.1007/s00439-014-1496-3

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