• Corpus ID: 16875610

Screening and merging algorithm for the detection of copy-number alterations

@article{Pinheiro2017ScreeningAM,
  title={Screening and merging algorithm for the detection of copy-number alterations},
  author={Murilo S. Pinheiro and Benilton S. Carvalho and Alu'isio S. Pinheiro},
  journal={arXiv: Applications},
  year={2017}
}
We call change-point problem (CPP) the identification of changes in the probabilistic behavior of a sequence of observations. Solving the CPP involves detecting the number and position of such changes. In genetics the study of how and what characteristics of a individual's genetic content might contribute to the occurrence and evolution of cancer has fundamental importance in the diagnosis and treatment of such diseases and can be formulated in the framework of chage-point analysis. In this… 

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TLDR
This study proposes the Screening and Ranking algorithm (SaRa) which can detect CNVs fast and accurately with complexity down to O(n), and characterize theoretical properties and present numerical analysis for the algorithm.
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TLDR
QuantiSNP is a novel algorithm for high-resolution CNV/aneuploidy detection with application to clinical genetics, cancer and disease association studies and it is believed that the OB-HMM framework has widespread applicability in genomic research.
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TLDR
PennCNV, a hidden Markov model (HMM) based approach, is presented for kilobase-resolution detection of CNVs from Illumina high-density SNP genotyping data, demonstrating the feasibility of whole-genome fine-mapping ofCNVs via high- density SNP genotypesing.
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TLDR
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Change-point Problem and Regression: An Annotated Bibliography
The problems of identifying changes at unknown times and of estimating the location of changes in stochastic processes are referred to as “the change-point problem” or, in the Eastern literature, as
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TLDR
This work considers the problem of detecting multiple changepoints in large data sets and introduces a new method for finding the minimum of such cost functions and hence the optimal number and location of changepoints that has a computational cost which is linear in the number of observations.
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TLDR
This work proposes a new technique, called wild binary segmentation (WBS), for consistent estimation of the number and locations of multiple change-points in data, and proposes two stopping criteria for WBS: one based on thresholding and the other based on what is termed the `strengthened Schwarz information criterion'.
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TLDR
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TLDR
A hidden Markov model-based method to identify LOH from unpaired tumor samples, taking into account SNP intermarker distances, SNP-specific heterozygosity rates, and the haplotype structure of the human genome is described.
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