ATLAS Sensitivity to Leptoquarks, W_R and Heavy Majorana Neutrinos in Final States with High-pt Dileptons and Jets with Early LHC Data at 14 TeV proton-proton collisions

Dilepton-jet final states are used to study physical phenomena not predicted by the standard model. The ATLAS discovery potential for leptoquarks and Majorana Neutrinos is presented using a full simulation of the ATLAS detector at the Large Hadron Collider. The study is motivated by the role of the leptoquark in the Grand Unification of fundamental forces and the see-saw mechanism that could explain the masses of the observed neutrinos. The analysis algorithms are presented, background sources are discussed and estimates of sensitivity and the discovery potential for these processes are reported.Comment: 6 pages, 16 figures, To be published in the proceedings of DPF-2009, Detroit, MI, July 2009, eConf C09072

A computational method for estimating the PCR duplication rate in DNA and RNA-seq experiments.

BackgroundPCR amplification is an important step in the preparation of DNA sequencing libraries prior to high-throughput sequencing. PCR amplification introduces redundant reads in the sequence data and estimating the PCR duplication rate is important to assess the frequency of such reads. Existing computational methods do not distinguish PCR duplicates from "natural" read duplicates that represent independent DNA fragments and therefore, over-estimate the PCR duplication rate for DNA-seq and RNA-seq experiments.ResultsIn this paper, we present a computational method to estimate the average PCR duplication rate of high-throughput sequence datasets that accounts for natural read duplicates by leveraging heterozygous variants in an individual genome. Analysis of simulated data and exome sequence data from the 1000 Genomes project demonstrated that our method can accurately estimate the PCR duplication rate on paired-end as well as single-end read datasets which contain a high proportion of natural read duplicates. Further, analysis of exome datasets prepared using the Nextera library preparation method indicated that 45-50% of read duplicates correspond to natural read duplicates likely due to fragmentation bias. Finally, analysis of RNA-seq datasets from individuals in the 1000 Genomes project demonstrated that 70-95% of read duplicates observed in such datasets correspond to natural duplicates sampled from genes with high expression and identified outlier samples with a 2-fold greater PCR duplication rate than other samples.ConclusionsThe method described here is a useful tool for estimating the PCR duplication rate of high-throughput sequence datasets and for assessing the fraction of read duplicates that correspond to natural read duplicates. An implementation of the method is available at https://github.com/vibansal/PCRduplicates

Fast individual ancestry inference from DNA sequence data leveraging allele frequencies for multiple populations.

BackgroundEstimation of individual ancestry from genetic data is useful for the analysis of disease association studies, understanding human population history and interpreting personal genomic variation. New, computationally efficient methods are needed for ancestry inference that can effectively utilize existing information about allele frequencies associated with different human populations and can work directly with DNA sequence reads.ResultsWe describe a fast method for estimating the relative contribution of known reference populations to an individual's genetic ancestry. Our method utilizes allele frequencies from the reference populations and individual genotype or sequence data to obtain a maximum likelihood estimate of the global admixture proportions using the BFGS optimization algorithm. It accounts for the uncertainty in genotypes present in sequence data by using genotype likelihoods and does not require individual genotype data from external reference panels. Simulation studies and application of the method to real datasets demonstrate that our method is significantly times faster than previous methods and has comparable accuracy. Using data from the 1000 Genomes project, we show that estimates of the genome-wide average ancestry for admixed individuals are consistent between exome sequence data and whole-genome low-coverage sequence data. Finally, we demonstrate that our method can be used to estimate admixture proportions using pooled sequence data making it a valuable tool for controlling for population stratification in sequencing based association studies that utilize DNA pooling.ConclusionsOur method is an efficient and versatile tool for estimating ancestry from DNA sequence data and is available from https://sites.google.com/site/vibansal/software/iAdmix

InPhaDel: integrative shotgun and proximity-ligation sequencing to phase deletions with single nucleotide polymorphisms.

Phasing of single nucleotide (SNV), and structural variations into chromosome-wide haplotypes in humans has been challenging, and required either trio sequencing or restricting phasing to population-based haplotypes. Selvaraj et al demonstrated single individual SNV phasing is possible with proximity ligated (HiC) sequencing. Here, we demonstrate HiC can phase structural variants into phased scaffolds of SNVs. Since HiC data is noisy, and SV calling is challenging, we applied a range of supervised classification techniques, including Support Vector Machines and Random Forest, to phase deletions. Our approach was demonstrated on deletion calls and phasings on the NA12878 human genome. We used three NA12878 chromosomes and simulated chromosomes to train model parameters. The remaining NA12878 chromosomes withheld from training were used to evaluate phasing accuracy. Random Forest had the highest accuracy and correctly phased 86% of the deletions with allele-specific read evidence. Allele-specific read evidence was found for 76% of the deletions. HiC provides significant read evidence for accurately phasing 33% of the deletions. Also, eight of eight top ranked deletions phased by only HiC were validated using long range polymerase chain reaction and Sanger. Thus, deletions from a single individual can be accurately phased using a combination of shotgun and proximity ligation sequencing. InPhaDel software is available at: http://l337x911.github.io/inphadel/

Enterprise Resource Planning Driving Human Resource Management

Enterprise Resource Planning (ERP) Systems exist to create effective organizations but measurement of this is difficult. It exists as a driving force to the modern Human resource management in the Organizations . ERP helped in making H uman resour ce Management processes simpler , smarter and efficient with quick avai lability of decision making data . In this article at the first, we will review the ERP and after that we will analyze its impact on the various aspe cts of Human Resource Management and how These functions can be made perform better with the ER

PROSPECTS OF LEPTOQUARK DISCOVERYWITH ATLAS AT THE LHC

Final states with high-pT leptons and jets are predicted by many Beyond the StandardModel (BSM) scenarios including leptoquarks, Left-Right Symmetry, various implementationsof Grand Unification Theory (GUT), and other models. Such theoretical models extendthe application of Quantum Field Theory to energies far above the Electroweak SymmetryBreaking (EWSB) energy scale and seek to provide a much more elegant and symmetricdescription of the fundamental forces. The implications of such models include possible answersto the origins of flavor, CP violation, baryogenesis, and other fundamental questionsbeyond EWSB.This dissertation describes the study of leptoquarks in dielectron-jets final states inproton-proton collisions at a center of mass energy of 14 TeV using ATLAS apparatus at theLarge Hadron Collider at CERN. The presented analysis is based on fully-simulated datasamples that contain two or more high-pT electron candidates and jets for an integratedluminosity of 100 / pb . Signal event selection, analysis algorithms, and suppression of SMbackgrounds are discussed. ATLAS can discover leptoquarks up to masses of 565 GeV at100 / pb for a branching ratio = 1 at a 5 sigma significance level

Designing deep sequencing experiments: detecting structural variation and estimating transcript abundance

Abstract Background Massively parallel DNA sequencing technologies have enabled the sequencing of several individual human genomes. These technologies are also being used in novel ways for mRNA expression profiling, genome-wide discovery of transcription-factor binding sites, small RNA discovery, etc. The multitude of sequencing platforms, each with their unique characteristics, pose a number of design challenges, regarding the technology to be used and the depth of sequencing required for a particular sequencing application. Here we describe a number of analytical and empirical results to address design questions for two applications: detection of structural variations from paired-end sequencing and estimating mRNA transcript abundance. Results For structural variation, our results provide explicit trade-offs between the detection and resolution of rearrangement breakpoints, and the optimal mix of paired-read insert lengths. Specifically, we prove that optimal detection and resolution of breakpoints is achieved using a mix of exactly two insert library lengths. Furthermore, we derive explicit formulae to determine these insert length combinations, enabling a 15% improvement in breakpoint detection at the same experimental cost. On empirical short read data, these predictions show good concordance with Illumina 200 bp and 2 Kbp insert length libraries. For transcriptome sequencing, we determine the sequencing depth needed to detect rare transcripts from a small pilot study. With only 1 Million reads, we derive corrections that enable almost perfect prediction of the underlying expression probability distribution, and use this to predict the sequencing depth required to detect low expressed genes with greater than 95% probability. Conclusions Together, our results form a generic framework for many design considerations related to high-throughput sequencing. We provide software tools http://bix.ucsd.edu/projects/NGS-DesignTools to derive platform independent guidelines for designing sequencing experiments (amount of sequencing, choice of insert length, mix of libraries) for novel applications of next generation sequencing