Apache Spark based kernelized fuzzy clustering framework for single nucleotide polymorphism sequence analysis

This paper introduces a kernel based fuzzy clustering approach to deal with the non-linear separable problems by applying kernel Radial Basis Functions (RBF) which maps the input data space non-linearly into a high-dimensional feature space. Discovering clusters in the high-dimensional genomics data is extremely challenging for the bioinformatics researchers for genome analysis. To support the investigations in bioinformatics, explicitly on genomic clustering, we proposed high-dimensional kernelized fuzzy clustering algorithms based on Apache Spark framework for clustering of Single Nucleotide Polymorphism (SNP) sequences. The paper proposes the Kernelized Scalable Random Sampling with Iterative Optimization Fuzzy c-Means (KSRSIO-FCM) which inherently uses another proposed Kernelized Scalable Literal Fuzzy c-Means (KSLFCM) clustering algorithm. Both the approaches completely adapt the Apache Spark cluster framework by localized sub-clustering Resilient Distributed Dataset (RDD) method. Additionally, we are also proposing a preprocessing approach for generating numeric feature vectors for huge SNP sequences and making it a scalable preprocessing approach by executing it on an Apache Spark cluster, which is applied to real-world SNP datasets taken from open-internet repositories of two different plant species, i.e., soybean and rice. The comparison of the proposed scalable kernelized fuzzy clustering results with similar works shows the significant improvement of the proposed algorithm in terms of time and space complexity, Silhouette index, and Davies-Bouldin index. Exhaustive experiments are performed on various SNP datasets to show the effectiveness of proposed KSRSIO-FCM in comparison with proposed KSLFCM and other scalable clustering algorithms, i.e., SRSIO-FCM, and SLFCM.     

2016年研究生数学建模竞赛B题综述

对2016年全国研究生数学建模B题"具有遗传性疾病和性状的遗传位点分析"进行综述,包括命题的背景和目的,解题的方法和思路,研究生竞赛中的答题情况及问题分析.     

Factors Impacting Invader-Mediated Recognition of Double-Stranded DNA

The development of chemically modified oligonucleotides enabling robust, sequence-unrestricted recognition of complementary chromosomal DNA regions has been an aspirational goal for scientists for many decades. While several groove-binding or strand-invading probes have been developed towards this end, most enable recognition of DNA only under limited conditions (e.g., homopurine or short mixed-sequence targets, low ionic strength, fully modified probe strands). Invader probes, i.e., DNA duplexes modified with +1 interstrand zippers of intercalator-functionalized nucleotides, are predisposed to recognize DNA targets due to their labile nature and high affinity towards complementary DNA. Here, we set out to gain further insight into the design parameters that impact the thermal denaturation properties and binding affinities of Invader probes. Towards this end, ten Invader probes were designed, and their biophysical properties and binding to model DNA hairpins and chromosomal DNA targets were studied. A Spearman’s rank-order correlation analysis of various parameters was then performed. Densely modified Invader probes were found to result in efficient recognition of chromosomal DNA targets with excellent binding specificity in the context of denaturing or non-denaturing fluorescence in situ hybridization (FISH) experiments. The insight gained from the initial phase of this study informed subsequent probe optimization, which yielded constructs displaying improved recognition of chromosomal DNA targets. The findings from this study will facilitate the design of efficient Invader probes for applications in the life sciences.     

单体型装配问题及其算法

单核苷酸多态性(SNP)单体型装配问题就是从给定的来自某人染色体的SNP片段中去除错误,重构出尽可能与原来片段一致的单体型.这个问题有几个不同的模型最少片段去除(MFR)问题,最少SNP去除(MSR)问题以及最少错误纠正(MEC)问题.前两个问题的复杂性与算法已有一些学者研究过.第三个问题已被证明是NP完全问题,但这个问题的实际算法还没有.该文对MEC问题给出了一个分支定界算法,这个算法能得到问题的全局最优解.通过这个算法对实际数据的计算说明了MEC模型的合理性,即在一定条件下,通过修正最少的错误重构出的单体型确实是真实的单体型.由于分支定界算法对这样一个NP完全问题不能在可接受的时间内解规模较大的问题,文中又给出了求解MEC问题的两个基于动态聚类的算法,以便对规模较大的问题在可接受的时间内得到近似最优解.数值实际表明这两个算法很快,很有效.这两个算法总能得到与分支定界找到的全局最优解很接近的近似最优解.鉴于MEC问题是NP完全的,这两个算法是有效的、实际的算法.     

SnpFilt: A pipeline for reference-free assembly-based identification of SNPs in bacterial genomes

De novo assembly of bacterial genomes from next-generation sequencing (NGS) data allows a reference-free discovery of single nucleotide polymorphisms (SNP). However, substantial rates of errors in genomes assembled by this approach remain a major barrier for the reference-free analysis of genome variations in medically important bacteria. The aim of this report was to improve the quality of SNP identification in bacterial genomes without closely related references. We developed a bioinformatics pipeline (SnpFilt) that constructs an assembly using SPAdes and then removes unreliable regions based on the quality and coverage of re-aligned reads at neighbouring regions. The performance of the pipeline was compared against reference-based SNP calling for Illumina HiSeq, MiSeq and NextSeq reads from a range of bacterial pathogens including Salmonella, which is one of the most common causes of food-borne disease. The SnpFilt pipeline removed all false SNP in all test NGS datasets consisting of paired-end Illumina reads. We also showed that for reliable and complete SNP calls, at least 40-fold coverage is required. Analysis of bacterial isolates associated with epidemiologically confirmed outbreaks using the SnpFilt pipeline produced results consistent with previously published findings. The SnpFilt pipeline improves the quality of de-novo assembly and precision of SNP calling in bacterial genomes by removal of regions of the assembly that may potentially contain assembly errors. SnpFilt is available from https://github.com/LanLab/SnpFilt.     

Application of SNPs with low minor allele frequencies in missing person identification (MPI) through kinship analysis of DNA mixtures

The need to identify a missing person (MP) through kinship analysis of DNA samples found at a crime scene has become increasingly prevalent. DNA samples from MPs can be severely degraded, contain little DNA and mixed with other contributors, which often makes it difficult to apply conventional methods in practice. This study developed a massively parallel sequencing–based panel that contains 1661 single-nucleotide polymorphisms (SNPs) with low minor allele frequencies (MAFs) (averaged at 0.0613) in the Chinese Han population, and the strategy for relationship inference from DNA mixtures comprising different numbers of contributors (NOCs) and of varying allele dropout probabilities. Based on the simulated dataset and genotyping results of 42 artificial DNA mixtures (NOC = 2–4), it was observed that the present SNP panel was sufficient for balanced mixtures when referenced to the closest relatives (parents/offspring and full siblings). When the mixture profiles suffered from dropout, incorrect assignments were markedly associated with relatedness, NOC and the dropout level. We, therefore, indicate that SNPs with low MAFs could be reliably interpreted for MP identification through the kinship analysis of complex DNA mixtures. Further studies should be extended to more possible scenarios to test the feasibility of this present approach.     

Application of magnetic and core–shell nanoparticles to determine enrofloxacin and its metabolite using laser induced fluorescence microscope

A unique analytical method using nanoparticles and laser-induced fluorescence microscopy (LIFM) was developed to determine enrofloxacin in this work. For sample pretreatment, two different kinds of particles, i.e., synthesized dye-doped core–shell silica nanoparticles and magnetic micro-particles (MPs), were used for fluorescent tagging and concentrating the enrofloxacin, respectively. The antibody of enrofloxacin was immobilized on the synthesized FITC-doped core–shell nanoparticles, and the enrofloxacin target was extracted by the MPs. At this moment, the average number of antibodies on each core–shell silica nanoparticle was ∼0.9, which was determined by the fluorescence ratiometric method. The described method was demonstrated for a meat sample to determine enrofloxacin using LIFM, and the result was compared with enzyme-linked immunosorbent assay (ELISA). The developed technique allowed the simplified analytical procedure, improved the detection limit about 54-fold compared to ELISA.     

East Asian mtDNA haplogroup determination in Koreans: haplogroup-level coding region SNP analysis and subhaplogroup-level control region sequence analysis

The present study analyzed 21 coding region SNP markers and one deletion motif for the determination of East Asian mitochondrial DNA (mtDNA) haplogroups by designing three multiplex systems which apply single base extension methods. Using two multiplex systems, all 593 Korean mtDNAs were allocated into 15 haplogroups: M, D, D4, D5, G, M7, M8, M9, M10, M11, R, R9, B, A, and N9. As the D4 haplotypes occurred most frequently in Koreans, the third multiplex system was used to further define D4 subhaplogroups: D4a, D4b, D4e, D4g, D4h, and D4j. This method allowed the complementation of coding region information with control region mutation motifs and the resultant findings also suggest reliable control region mutation motifs for the assignment of East Asian mtDNA haplogroups. These three multiplex systems produce good results in degraded samples as they contain small PCR products (101-154 bp) for single base extension reactions. SNP scoring was performed in 101 old skeletal remains using these three systems to prove their utility in degraded samples. The sequence analysis of mtDNA control region with high incidence of haplogroup-specific mutations and the selective scoring of highly informative coding region SNPs using the three multiplex systems are useful tools for most applications involving East Asian mtDNA haplogroup determination and haplogroup-directed stringent quality control.     

General refinement strategy for magnetic structures using spherical neutron polarimetry and representation analysis

Spherical neutron polarimetry (SNP) is a powerful technique for the determination of magnetic structures which may otherwise be intractable. The complexity of the neutron scattering process and the large number of different possible trial structures typically leads to refinements based on a simple trial and error generation of possible models and a possible failure to explore valid possible models. The combination of the model symmetry types determined from representational analysis and reverse-Monte Carlo refinement creates a generalized refinement strategy for SNP data that allows refinement in terms of symmetry adapted modes built up from the basis vectors that describe the orientations of the magnetic moments on the different magnetic sites, and those of the different domains that are possible in a sample: spin (S)-domains and K-domains. This methodology typically leads to a large reduction in the number of refined parameters as well as the rigorous inclusion of any symmetry related domains. In combination with reverse-Monte Carlo refinement algorithms a general strategy for refining complex magnetic structures can be created. We present an example of a frustrated magnetic structure that have been determined using this approach Er₂Ti₂O₇.     

A new set of DIP‐SNP markers for detection of unbalanced and degraded DNA mixtures

Unbalanced and degraded mixtures (UDM) are frequently encountered during forensic DNA analysis. For example, forensic DNA units regularly encounter DNA mixture signal where the DNA signal from the alleged offender is masked or swamped by high quantities of DNA from the victim. Our previous data presented a new kind of DNA markers that composed of a deletion/insertion polymorphism (DIP) and a SNP and we termed this new kind of microhaplotypes DIP‐SNP (combination of DIP and SNP). Since such markers could be designed short enough for degraded DNA amplification, we hypothesized that DIP‐SNP markers are applicable for typing of UDM. In this study, we developed a new set of DIP‐SNPs with short amplicons which were complement to our prior developed system. The multiplex PCR and SNaPshot assay were established for 20 DIP‐SNPs in a Chinese Han population. The DIP‐SNPs were capable of detecting the minor contributor's allele in home‐made DNA mixture with sensitivities from 1:100 to 1:1000 with a total of 1 –10 ng input DNA. Moreover, this system successfully typed the degraded DNA whether it came from the single source or mixture samples. In Chinese population, the system showed an average informative value of 0.293 and combined informative value of 0.998363862. Our results demonstrated that DIP‐SNPs may serve as a valuable tool in detection of UDM in forensic medicine.