Optimal haplotype assembly from high-throughput mate-pair reads

@article{Kamath2015OptimalHA,
  title={Optimal haplotype assembly from high-throughput mate-pair reads},
  author={Govinda M. Kamath and Eren Sasoglu and David Tse},
  journal={2015 IEEE International Symposium on Information Theory (ISIT)},
  year={2015},
  pages={914-918}
}
  • G. Kamath, Eren Sasoglu, David Tse
  • Published 6 February 2015
  • Biology, Mathematics, Computer Science
  • 2015 IEEE International Symposium on Information Theory (ISIT)
Humans have 23 pairs of homologous chromosomes. The homologous pairs are identical except on certain documented positions called single nucleotide polymorphisms (SNPs). A haplotype of an individual is the pair of sequences of SNPs on the two homologous chromosomes. In this paper, we study the problem of inferring haplotypes of individuals from mate-pair reads of their genome. We give a simple formula for the coverage needed for haplotype assembly, under a generative model. The analysis here… 
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References

SHOWING 1-8 OF 8 REFERENCES
Optimal Haplotype Assembly from High-Throughput Mate-Pair Reads
TLDR
This paper gives a simple formula for the coverage needed for haplotype assembly, under a generative model, and leverages connections of this problem with decoding convolutional codes.
Haplotype assembly: An information theoretic view
TLDR
The focus of this paper is on determining the required number of reads for reliable haplotype reconstruction, and both the necessary and sufficient conditions are presented with order-wise optimal bounds.
Optimal algorithms for haplotype assembly from whole-genome sequence data
TLDR
A dynamic programming algorithm is proposed that is able to assemble the haplotypes optimally with time complexity O(m × 2k × n), where m is the number of reads, k is the length of the longest read and n is the total number of SNPs in the haplotype.
Data Processing of Nextera Mate Pair Reads on Illumina Sequencing Platforms
  • 2012
Mate pair sequencing enables the generation of libraries with insert sizes in the range of several kilobases (Kb). As such, aligned mate pair datasets can inform on genomic regions separated by
The Database of Short Genetic Variation (dbSNP)
TLDR
Sequence variation is of scientific interest to population geneticists, genetic mappers, and those investigating relationships among variation and phenotype, from a variation with a single allele to a variation that is highly polymorphic.
Haplotype phasing: existing methods and new developments
TLDR
The haplotype phasing methods that are available are assessed, focusing in particular on statistical methods, and the practical aspects of their application are discussed, and recent developments that may transform this field are described.
Elements of Information Theory
TLDR
The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Convolutional Codes and 'Their Performance in Communication Systems