Implementing Higher－Order Gamma on a Massively Parallel computer－A Case study

Gamma is a kernel programming language with an elegant chemical reaction metaphor in whichprograms are described in terms of multiset rewriting. Gamma formalism allows one to describe analgorithm without introducing artificial sequentiality and leads to the derivation of a parallel solution to agiven problem naturally. However, the difficulty of incorporating control strategies makes Gamma not onlyhard for one to define any sophisticated approaches but also impossible to reach a decent level of efficiencyin any direct implementation. Recently, a higherorder multiset programming paradigm, named higher--order Gamma, is introduced by Metayer to alleviate these problems. In this paper, we investigate the possibility of implementing higherorder Gamma on Maspar, a massively data parallel computer. The results showthat a program written in higher--order Gamma can be transformed naturally toward an efficientimplementation on a real parallel machine.

Using Cluster Computers in Bioinformatics Research

In the last ten years, high-performance and massively parallel computing technology comes into a high speed developing phase and is used in all fields. The cluster computer systems are also being widely used for their low cost and high performance. In bioinformatics research, solving a problem with computer usually takes hours even days. To speed up research, high-performance cluster computers are considered to be a good platform. Moving into the new MPP (massively parallel processing) system, the original algorithm should be parallelized in a proper way. In this paper, a new parallelizing method of useful sequence alignment algorithm (Smith-Waterman) is designed based on its optimizing algorithm already exists. The result is gratifying.

Implementation of GAMMA on a Massively Parallel Computer

The GAMMA paradigm is recently proposed by Banatre and M6tayer to describe the systematic construction of parallel programs without introducing artificial sequentiality. This paper presents two synchronous execution models for GAMMA and discusses how to implement them on MasPar MP-1, a massively data parallel computer. The results show that GAMMA paradigm can be implemented very naturally on data parallel machines, and very high level language, such as GAMMA in which parallelism is left implicit, is suitable for specifying massively parallel applications.

A New Technique for Use in Culturing Prokaryotes Comprising the Mouse Intestinal Microbiome

The microbiome has a profound impact on host fitness. pH, oxygen, nutrients, or other factors such as food or pharmaceuticals, subject the microbiome to variations in the gastrointestinal tract. This variation is a cause for concern given dysbiosis of the microbiome is correlated with various disease states. Currently, much research relies on model organisms to study microbial communities since intact microbiomes are challenging to utilize. The objective of this study is to culture an explanted colon microbiome of 4 Balb/c mice to develop an in vitro tool for future microbiome studies. We cultured homogenates of the distal colons of 4 mice in trans-well culture dishes. These dishes were incubated for 24 hours in two different oxygen concentration levels and the pH was compared before and after incubation of the cultures. To analyze the integrity of the microbiome, we utilized massively paralleled DNA sequencing with 16S metagenomics to characterize fecal and colon samples to speculate whether future studies may utilize feces in constructing an in vitro microbial community to spare animal lives. We found that pH and familial relationships had a profound impact on community structure while oxygen did not have a significant influence. The feces and the colon were similar in community profiles, which lends credence to utilizing feces in future studies. The gut microbiome is of great interest and great importance for studies in a variety of different diseases. Many laboratories do not have access to germ-free mice, which is one optimal way to study mammalian microbiomes, but this technique allowed for the in vitro culturing of a majority of the prokaryotes isolated from the colons of mice. This may allow an alternative to study the interactions of this very diverse population of microorganisms without the need for germ-free conditions.

Novel Y-chromosome Short Tandem Repeat Variants Detected Through the Use of Massively Parallel Sequencing

Massively parallel sequencing （MPS） technology is capable of determining the sizes of short tandem repeat （STR） alleles as well as their individual nueleotide sequences. Thus, single nucleotide polymorphisms （SNPs） within the repeat regions of STRs and variations in the pattern of repeat units in a given repeat motif can be used to differentiate alleles of the same length. In this study, MPS was used to sequence 28 forensically-relevant Y-chromosome STRs in a set of 41 DNA samples from the 3 major U.S. population groups （African Americans, Caucasians, and Hispanics）. The resulting sequence data, which were analyzed with STRait Razor v2.0, revealed 37 unique allele sequence variants that have not been previously reported. Of these, 19 sequences were variations of documented sequences resulting from the presence of intra-repeat SNPs or alternative repeat unit patterns. Despite a limited sampling, two of the most frequently-observed variants were found only in African American samples. The remaining 18 variants represented allele sequences for which there were no published data with which to compare. These findings illustrate the great potential of MPS with regard to increasing the resolving power of STR typing and emphasize the need for sample population characterization of STR alleles.

DNA identification of compromised samples with massive parallel sequencing

Genetic profiling is a standard procedure for human identification,i.e.in criminal cases and mass disasters,and has been proven to be an important part in the process in the repatriation of victims to their relatives.In the event of a catastrophe whether it be a natural disaster,terror attack or accident,fatalities of many nationalities may be a consequence and international collaboration becomes necessary.Current DNA techniques used on a routine basis at forensic laboratories world-wide are very useful,and results reported from different labs are compared,making it possible to be matched in order to declare the identification of a victim.Statistical calculations of possibilities of a random match are achievable since population data from many parts of the world are available.However,decomposition and degradation of the remains are not uncommon in the aftermath of a catastrophe and hence it may be difficult to retrieve detailed DNA profiles from such samples.Massive parallel sequencing(MPS)is a technique capable of producing a vast amount of DNA sequence data in a high-through put manner,and panels of single nucleotide polymorphism(SNP)markers allow the amplification of small DNA fragments,often seen in compromised samples.Here,we report the results from a set of 10 samples from missing person identification cases,analyzed with an MPS based method comprising 131 SNP markers and compared with direct reference material or buccal swab samples collected from relatives of the deceased.We assess the weight of evidence of a match by statistical calculation.Furthermore,we compare results reported on different platforms using different SNP panels,and conclude that more work has to be done if results from missing person identification cases analyzed on MPS with SNP panels at different laboratories are to be fully reliable and thus comparable.

Massively parallel sequencing of 231 autosomal SNPs with a custom panel:a SNP typing assay developed for human identification with Ion Torrent PGM

The custom-designed single nucleotide polymorphism(SNP)panel amplified 231 autosomal SNPs in one PCR reaction and subsequently sequenced with massively parallel sequencing(MPS)technology and Ion Torrent personal genome machine(PGM).SNPs were chosen from SNPforID,IISNP,HapMap,dbSNP,and related published literatures.Full concordance was obtained between available MPS calling and Sanger sequencing with 9947A and 9948 controls.Ten SNPs(rs4606077,rs334355,rs430046,rs2920816,rs4530059,rs1478829,rs1498553,rs7141285,rs12714757 and rs2189011)with low coverage or heterozygote imbalance should be optimized or excluded from the panel.Sequence data had sufficiently high coverage and gave reliable SNP calling for the remaining 221 loci with the custom MPS-SNP panel.A default DNA input amount of 10 ng per reaction was recommended by Ampliseq technology but sensitivity testing revealed positive results from as little as 1 ng input DNA.Mixture testing with this panel is possible through analysis of the F MAR(frequency of major allele reads)values at most loci with enough high coverage depth and low level of sequencing noise.These results indicate the potential advantage of the custom MPS-SNP assays and Ion Torrent PGM platform for forensic study.

Progress and Challenges in High Performance Computer Technology

High performance computers provide strategic computing power in the construction of national economy and defense, and become one of symbols of the country＇s overall strength. Over 30 years, with the supports of governments, the technology of high performance computers is in the process of rapid development, during which the computing performance increases nearly 3 million times and the processors number expands over 10 hundred thousands times. To solve the critical issues related with parallel efficiency and scalability, scientific researchers pursued extensive theoretical studies and technical innovations. The paper briefly looks back the course of building high performance computer systems both at home and abroad, and summarizes the significant breakthroughs of international high performance computer technology. We also overview the technology progress of China in the area of parallel computer architecture, parallel operating system and resource management, parallel compiler and performance optimization, environment for parallel programming and network computing. Finally, we examine the challenging issues, ＂memory wall＂, system scalability and ＂power wall＂, and discuss the issues of high productivity computers, which is the trend in building next generation high performance computers.

Large-scale branch contingency analysis through master/slave parallel computing

Contingency analysis(CA)requires fast execution time for real-time power system operations.Because CA problems can naturally be divided into separate subtasks,parallel computing helps to speed up the computation time.This paper proposes a master/slave parallel computing architecture and studies the computation of CA in a large-scale power system through high performance computing,adopting a message passing interface for implementation.In particular,although the execution time of CA varies,there is a tradeoff between having an imbalanced workload and"paying"a synchronization penalty for parallel computing:either factor blocks the progress of scalability.The proposed layered dynamic scheduling method is effective to tackle the challenge of high synchronization cost and workload imbalance and have the potential to further scale for the N-2 contingency analysis.

A Survey on Parallel Computing and its Applications in Data-Parallel Problems Using GPU Architectures

Parallel computing has become an important subject in the field of computer science and has proven to be critical when researching high performance solutions.The evolution of computer architectures(multi-core and many-core)towards a higher number of cores can only confirm that parallelism is the method of choice for speeding up an algorithm.In the last decade,the graphics processing unit,or GPU,has gained an important place in the field of high performance computing(HPC)because of its low cost and massive parallel processing power.Super-computing has become,for the first time,available to anyone at the price of a desktop computer.In this paper,we survey the concept of parallel computing and especially GPU computing.Achieving efficient parallel algorithms for the GPU is not a trivial task,there are several technical restrictions that must be satisfied in order to achieve the expected performance.Some of these limitations are consequences of the underlying architecture of the GPU and the theoretical models behind it.Our goal is to present a set of theoretical and technical concepts that are often required to understand the GPU and its massive parallelism model.In particular,we show how this new technology can help the field of computational physics,especially when the problem is data-parallel.We present four examples of computational physics problems;n-body,collision detection,Potts model and cellular automata simulations.These examples well represent the kind of problems that are suitable for GPU computing.By understanding the GPU architecture and its massive parallelism programming model,one can overcome many of the technical limitations found along the way,design better GPU-based algorithms for computational physics problems and achieve speedups that can reach up to two orders of magnitude when compared to sequential implementations.

Getting started in mapping-by-sequencing

Next-generation sequencing （NGS） technologies allow the cost-effective sequencing of whole genomes and have expanded the scope of genomics to novel applications, such as the genome-wide characterization of intraspecific polymorphisms and the rapid mapping and identification of point mutations. Next-generation sequencing platforms, such as the Illumina HiSeq2ooo platform, are now commercially available at affordable prices and routinely produce an enormous amount of sequence data, but their wide use is often hindered by a lack of knowledge on how to manipulateand process the information produced. In this review, we focus on the strategies that are available to geneticists who wish to incorporate these novel approaches into their research but who are not familiar with the necessary bioinformatic concepts and computational tools. In particular, we comprehensively summarize case studies where the use of NGS technologies has led to the identification of point mutations, a strategy that has been dubbed ＂mapping-by-sequencing＇, and review examples from plants and other model species such as Caenorhabditis elegans, Saccharomyces cerevisiae, and Drosophila mela- nogaster. As these technologies are becoming cheaper and more powerful, their use is also expanding to allow mutation identification in species with larger genomes, such as many crop plants.

Next generation sequencing of Y-STRs in father-son pairs and comparison with traditional capillary electrophoresis

To evaluate the promising advantages of massively parallel sequencing(MPS)in our casework,we analysed a total of 33 Y-chromosomal short tandem repeats(Y-STRs)with traditional capillary electrophoresis(CE)and 25 Y-STRs using the newer MPS technology.We studied the outcome of both technologies in 64 father-son pairs using stock and custom-designed kits.Current MPS technology confirmed the 13 mutational events observed with CE and improved our understanding of the complex nature of STR mutations.By detecting isometric sequence variants between unrelated males,we show that sequencing Y-STRs using MPS can boost discrimination power.

REVA as A Well-curated Database for Human Expressionmodulating Variants

More than 90%of disease-and trait-associated human variants are noncoding.By systematically screening multiple large-scale studies,we compiled REVA,a manually curated database for over 11.8 million experimentally tested noncoding variants with expression-modulating potentials.We provided 2424 functional annotations that could be used to pinpoint the plausible regulatory mechanism of these variants.We further benchmarked multiple state-of-the-art computational tools and found that their limited sensitivity remains a serious challenge for effective large-scale analysis.REVA provides high-quality experimentally tested expression-modulating variants with extensive functional annotations,which will be useful for users in the noncoding variant community.REVA is freely available at http://reva.gao-lab.org.

Sequencing of human identification markers in an Uyghur population using the MiSeq FGx^(TM) Forensic Genomics System

Massively parallel sequencing(MPS)offers a useful alternative to capillary electrophoresis(CE)based analysis of human identification markers in forensic genetics.By sequencing short tandem repeats(STRs)instead of determining the fragment lengths by CE,the sequence variation within the repeat region and the flanking regions may be identified.In this study,we typed 264 Uyghur individuals using the MiSeq FGx^(^(TM)) Forensic Genomics System and Primer Mix A of the ForenSeq^(^(TM)) DNA Signature Prep Kit that amplifies 27 autosomal STRs,25 Y-STRs,seven X-STRs,and 94 HID-SNPs.STRinNGS v.1.0 and GATK 3.6 were used to analyse the STR regions and HID-SNPs,respectively.Increased allelic diversity was observed for 33 STRs with the PCR-MPS assay.The largest increases were found in DYS389II and D12S391,where the numbers of sequenced alleles were 3–4 times larger than those of alleles determined by repeat length alone.A relatively large number of flanking region variants(28 SNPs and three InDels)were observed in the Uyghur population.Seventeen of the flanking region SNPs were rare,and 12 of these SNPs had no accession number in dbSNP.The combined mean match probability and typical paternity index based on 26 sequenced autosomal STRs were 3.85E36 and 1.49Eþ16,respectively.This was 10000 times lower and 1000 times higher,respectively,than the same parameters calculated from STR repeat lengths.

Mitochondrial genome sequencing with short overlapping amplicons on MiSeq FGx system

With the development and maturation of massively parallel sequencing(MPS)technology,the mitochondrial genome(mitogenome)sequencing is increasingly applied in the forensic field.In this study,we employed the strategy of short overlapping amplicons for the whole mitogenome,library preparation with tagmentation using the Nextera®XT DNA Library Preparation Kit,sequencing on the MiSeq FGxTM Forensic Genomics System and analyzing data using the mitochondrial(mtDNA)MSR Plug-in and the mtDNA Variant Analyzer.A total of 27 libraries and 56 libraries were sequenced in a run using MiSeq Reagent Kit v2 and v3,respectively.Results showed more than 1800×of averaged depth of coverage(DoC)at each position.Concordant haplotypes of 9947 A and 2800 M were obtained at 32 variants.Cross-reactivity was observed with 1 ng primate DNA and 10 ng non-primate DNA but could be easily distinguished.Full and accurate variants were obtained from at least 50 pg input DNA and from minor contributors between 19:1 and 1:19 mixed ratios with known reference profiles.More than 86%variants were detected from≥200-bp degraded samples but its haplotype was assigned to more ancestral haplogroup.Further,a total of 3962 variants were observed at 613 nucleotide positions from 103 Xibe mitogenomes with 25:1 ratio of transitions to transversions.Two new transversions(C13735A and A14755C)and two tri-alleles at nps 9824 and 16092 were identified.There were 103 unique mitogenome haplotypes from 103 Chinese Xibe that were assigned to 79 haplogroups.Haplogroup D was the preponderant top-level haplogroup in Xibe followed by F,B,M,A,N,G,C,Z,Y,HV and J.Random match probability(RMP)and haplotype diversity(HD)of the whole mitogenome was calculated as 0.0097 and 1.0000,respectively.Compared with HVS-I only,RMP decreased 33.56%,while the number of haplotypes and HD increased 15.73%and 0.49%,respectively.Principal component analysis(PCA)showed that Xibe was clustered to East and Southeast Asian.As a whole,this MPS strategy is suitable for the whole mitogenome sequencing especially for degraded samples and can facilitate generating mitogenome data to support the routine application in forensic sciences.EMP00726 is the first whole mitogenome dataset from Xibe contributed to the EMPOP.

Recent Developments in Forensic DNA Typing

The field of forensic DNA typing,often referred to as“DNA fingerprinting,”has evolved and expanded considerably since its beginnings in the mid-1980s.Originally,forensic DNA typing was primarily used for individual identification and criminal investigations,but it has evolved into a versatile discipline with a wide range of applications.This article addresses the growing scope of forensic genetics,which includes advances in DNA sequencing technologies,mixture analysis,body fluid identification,phenotypic profiling,forensic genealogy,microbiological analysis,exploration of novel markers,and ethical and legal considerations.These developments have enabled the analysis of difficult samples and provided comprehensive insights into the origins of biological evidence.In an ever-evolving landscape,forensic genetics continues to shape the future of forensic science by providing new tools and techniques that help deliver justice in an increasingly complex world.