Haplotype reconstruction from SNP fragments by minimum error correction
نویسندگان
چکیده
MOTIVATION Haplotype reconstruction based on aligned single nucleotide polymorphism (SNP) fragments is to infer a pair of haplotypes from localized polymorphism data gathered through short genome fragment assembly. An important computational model of this problem is the minimum error correction (MEC) model, which has been mentioned in several literatures. The model retrieves a pair of haplotypes by correcting minimum number of SNPs in given genome fragments coming from an individual's DNA. RESULTS In the first part of this paper, an exact algorithm for the MEC model is presented. Owing to the NP-hardness of the MEC model, we also design a genetic algorithm (GA). The designed GA is intended to solve large size problems and has very good performance. The strength and weakness of the MEC model are shown using experimental results on real data and simulation data. In the second part of this paper, to improve the MEC model for haplotype reconstruction, a new computational model is proposed, which simultaneously employs genotype information of an individual in the process of SNP correction, and is called MEC with genotype information (shortly, MEC/GI). Computational results on extensive datasets show that the new model has much higher accuracy in haplotype reconstruction than the pure MEC model.
منابع مشابه
Minimum Conflict Individual Haplotyping from SNP Fragments and Related Genotype
The Minimum Error Correction (MEC) is an important model for haplotype reconstruction from SNP fragments. However, this model is effective only when the error rate of SNP fragments is low. In this paper, we propose a new computational model called Minimum Conflict Individual Haplotyping (MCIH) as an extension to MEC. In contrast to the conventional approaches, the new model employs SNP fragment...
متن کاملEnhanced Evolutionary and Heuristic Algorithms for Haplotype Reconstruction Problem Using Minimum Error Correction Model
Construction of two haplotypes from a set of Single Nucleotide Polymorphism (SNP) fragments is referred to as haplotype reconstruction problem. One of the most important computational models for this problem is Minimum Error Correction (MEC). Since MEC is an NP-hard problem, here we propose a heuristic algorithm for haplotype reconstruction problem. The algorithm is Particle Swarm Optimization ...
متن کاملFastHap: fast and accurate single individual haplotype reconstruction using fuzzy conflict graphs
MOTIVATION Understanding exact structure of an individual's haplotype plays a significant role in various fields of human genetics. Despite tremendous research effort in recent years, fast and accurate haplotype reconstruction remains as an active research topic, mainly owing to the computational challenges involved. Existing haplotype assembly algorithms focus primarily on improving accuracy o...
متن کاملHMEC: A Heuristic Algorithm for Individual Haplotyping with Minimum Error Correction
Haplotype is a pattern of single nucleotide polymorphisms (SNPs) on a single chromosome. Constructing a pair of haplotypes from aligned and overlapping but intermixed and erroneous fragments of the chromosomal sequences is a nontrivial problem. Minimum error correction approach aims to minimize the number of errors to be corrected so that the pair of haplotypes can be constructed through consen...
متن کاملUsing Harmony Clustering for Haplotype Reconstruction from SNP fragments
Single Nucleotide Polymorphisms (SNPs), a single DNA base varying from one individual to another, are believed to be the most frequent form responsible for genetic differences. Haplotypes have more information for disease-associating than individual SNPs or genotypes; it is substantially more difficult to determine haplotypes through experiments. Hence, computational methods that can reduce the...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Bioinformatics
دوره 21 10 شماره
صفحات -
تاریخ انتشار 2005