5,932 research outputs found
Minimum error correction-based haplotype assembly: considerations for long read data
The single nucleotide polymorphism (SNP) is the most widely studied type of
genetic variation. A haplotype is defined as the sequence of alleles at SNP
sites on each haploid chromosome. Haplotype information is essential in
unravelling the genome-phenotype association. Haplotype assembly is a
well-known approach for reconstructing haplotypes, exploiting reads generated
by DNA sequencing devices. The Minimum Error Correction (MEC) metric is often
used for reconstruction of haplotypes from reads. However, problems with the
MEC metric have been reported. Here, we investigate the MEC approach to
demonstrate that it may result in incorrectly reconstructed haplotypes for
devices that produce error-prone long reads. Specifically, we evaluate this
approach for devices developed by Illumina, Pacific BioSciences and Oxford
Nanopore Technologies. We show that imprecise haplotypes may be reconstructed
with a lower MEC than that of the exact haplotype. The performance of MEC is
explored for different coverage levels and error rates of data. Our simulation
results reveal that in order to avoid incorrect MEC-based haplotypes, a
coverage of 25 is needed for reads generated by Pacific BioSciences RS systems.Comment: 17 pages, 6 figure
Haplotype Assembly: An Information Theoretic View
This paper studies the haplotype assembly problem from an information
theoretic perspective. A haplotype is a sequence of nucleotide bases on a
chromosome, often conveniently represented by a binary string, that differ from
the bases in the corresponding positions on the other chromosome in a
homologous pair. Information about the order of bases in a genome is readily
inferred using short reads provided by high-throughput DNA sequencing
technologies. In this paper, the recovery of the target pair of haplotype
sequences using short reads is rephrased as a joint source-channel coding
problem. Two messages, representing haplotypes and chromosome memberships of
reads, are encoded and transmitted over a channel with erasures and errors,
where the channel model reflects salient features of high-throughput
sequencing. The focus of this paper is on the required number of reads for
reliable haplotype reconstruction, and both the necessary and sufficient
conditions are presented with order-wise optimal bounds.Comment: 30 pages, 5 figures, 1 tabel, journa
Boosting Haplotype Inference with Local Search
Abstract. A very challenging problem in the genetics domain is to infer haplotypes from genotypes. This process is expected to identify genes affecting health, disease and response to drugs. One of the approaches to haplotype inference aims to minimise the number of different haplotypes used, and is known as haplotype inference by pure parsimony (HIPP). The HIPP problem is computationally difficult, being NP-hard. Recently, a SAT-based method (SHIPs) has been proposed to solve the HIPP problem. This method iteratively considers an increasing number of haplotypes, starting from an initial lower bound. Hence, one important aspect of SHIPs is the lower bounding procedure, which reduces the number of iterations of the basic algorithm, and also indirectly simplifies the resulting SAT model. This paper describes the use of local search to improve existing lower bounding procedures. The new lower bounding procedure is guaranteed to be as tight as the existing procedures. In practice the new procedure is in most cases considerably tighter, allowing significant improvement of performance on challenging problem instances.
NGS Based Haplotype Assembly Using Matrix Completion
We apply matrix completion methods for haplotype assembly from NGS reads to
develop the new HapSVT, HapNuc, and HapOPT algorithms. This is performed by
applying a mathematical model to convert the reads to an incomplete matrix and
estimating unknown components. This process is followed by quantizing and
decoding the completed matrix in order to estimate haplotypes. These algorithms
are compared to the state-of-the-art algorithms using simulated data as well as
the real fosmid data. It is shown that the SNP missing rate and the haplotype
block length of the proposed HapOPT are better than those of HapCUT2 with
comparable accuracy in terms of reconstruction rate and switch error rate. A
program implementing the proposed algorithms in MATLAB is freely available at
https://github.com/smajidian/HapMC
The EM Algorithm and the Rise of Computational Biology
In the past decade computational biology has grown from a cottage industry
with a handful of researchers to an attractive interdisciplinary field,
catching the attention and imagination of many quantitatively-minded
scientists. Of interest to us is the key role played by the EM algorithm during
this transformation. We survey the use of the EM algorithm in a few important
computational biology problems surrounding the "central dogma"; of molecular
biology: from DNA to RNA and then to proteins. Topics of this article include
sequence motif discovery, protein sequence alignment, population genetics,
evolutionary models and mRNA expression microarray data analysis.Comment: Published in at http://dx.doi.org/10.1214/09-STS312 the Statistical
Science (http://www.imstat.org/sts/) by the Institute of Mathematical
Statistics (http://www.imstat.org
Populations in statistical genetic modelling and inference
What is a population? This review considers how a population may be defined
in terms of understanding the structure of the underlying genetics of the
individuals involved. The main approach is to consider statistically
identifiable groups of randomly mating individuals, which is well defined in
theory for any type of (sexual) organism. We discuss generative models using
drift, admixture and spatial structure, and the ancestral recombination graph.
These are contrasted with statistical models for inference, principle component
analysis and other `non-parametric' methods. The relationships between these
approaches are explored with both simulated and real-data examples. The
state-of-the-art practical software tools are discussed and contrasted. We
conclude that populations are a useful theoretical construct that can be well
defined in theory and often approximately exist in practice
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