Journal article

Inferring copy number and genotype in tumour exome data

Kaushalya C Amarasinghe, Jason Li, Sally M Hunter, Georgina L Ryland, Prue A Cowin, Ian G Campbell, Saman K Halgamuge

BMC GENOMICS | BMC | Published : 2014

DOI: 10.1186/1471-2164-15-732

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Related Projects (1)

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NEAR UNSUPERVISED LEARNING FOR EARLY DISCOVERY OF NOVEL PATTERNS: METHODS, SCALABILITY AND LABEL DEPENDABILITY

This project aims to predict the unknown class labels using the existing small number of class labels. The outcomes of the project have dire..

Grants

Awarded by Australian Research Council

Funding Acknowledgements

This work is partially funded by Australian Research Council (grant DP1096296). KCA was funded by The University of Melbourne MIFRS and MIRS scholarships.

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Keywords

Computational Biology
Exome
Life Sciences & Biomedicine
Accurate
Capture
Humans
Mutations
Algorithms Chromosome Aberrations Computational Biology/methods *dna Copy Number Variations *exome Female Genomics/methods *genotype Genotyping Techniques High-Throughput Nucleotide Sequencing Humans Loss of Heterozygosity Neoplasms/*genetics Ovarian Neoplasms/genetics Polymorphism, Single Nucleotide Polyploidy Reproducibility of Results Sensitivity and Specificity
Female
Dna Copy Number Variations
Genomics
Polyploidy
Ovarian Neoplasms
Chromosome Aberrations
Reproducibility of Results
Neoplasms
Algorithms
Breast
Biotechnology & Applied Microbiology
Discovery
Hidden Markov-Models
Science & Technology
Identification
High-Throughput Nucleotide Sequencing
Sensitivity and Specificity
Cancer
Heterozygosity
Genotype
Genotyping Techniques
Genetics & Heredity
Loss of Heterozygosity
Polymorphism, Single Nucleotide