GNU GPL Research Articles

Sipros Ensemble improves database searching and filtering for complex metaproteomics.

MotivationComplex microbial communities can be characterized by metagenomics and metaproteomics. However, metagenome assemblies often generate enormous, and yet incomplete, protein databases, which undermines the identification of peptides and proteins in metaproteomics. This challenge calls for increased discrimination of true identifications from false identifications by database searching and filtering algorithms in metaproteomics.ResultsSipros Ensemble was developed here for metaproteomics using an ensemble approach. Three diverse scoring functions from MyriMatch, Comet and the original Sipros were incorporated within a single database searching engine. Supervised classification with logistic regression was used to filter database searching results. Benchmarking with soil and marine microbial communities demonstrated a higher number of peptide and protein identifications by Sipros Ensemble than MyriMatch/Percolator, Comet/Percolator, MS-GF+/Percolator, Comet & MyriMatch/iProphet and Comet & MyriMatch & MS-GF+/iProphet. Sipros Ensemble was computationally efficient and scalable on supercomputers.Availability and implementationFreely available under the GNU GPL license at http://sipros.omicsbio.org.Supplementary information Supplementary data are available at Bioinformatics online.

KWIP: The k-mer weighted inner product, a de novo estimator of genetic similarity.

Modern genomics techniques generate overwhelming quantities of data. Extracting population genetic variation demands computationally efficient methods to determine genetic relatedness between individuals (or “samples”) in an unbiased manner, preferably de novo. Rapid estimation of genetic relatedness directly from sequencing data has the potential to overcome reference genome bias, and to verify that individuals belong to the correct genetic lineage before conclusions are drawn using mislabelled, or misidentified samples. We present the k-mer Weighted Inner Product (kWIP), an assembly-, and alignment-free estimator of genetic similarity. kWIP combines a probabilistic data structure with a novel metric, the weighted inner product (WIP), to efficiently calculate pairwise similarity between sequencing runs from their k-mer counts. It produces a distance matrix, which can then be further analysed and visualised. Our method does not require prior knowledge of the underlying genomes and applications include establishing sample identity and detecting mix-up, non-obvious genomic variation, and population structure. We show that kWIP can reconstruct the true relatedness between samples from simulated populations. By re-analysing several published datasets we show that our results are consistent with marker-based analyses. kWIP is written in C++, licensed under the GNU GPL, and is available from https://github.com/kdmurray91/kwip.

RegNet: an R package for network-based propagation of gene expression alterations.

Gene expression alterations and potentially underlying gene copy number mutations can be measured routinely in the wet lab, but it is still extremely challenging to quantify impacts of altered genes on clinically relevant characteristics to predict putative driver genes. We developed the R package regNet that utilizes gene expression and copy number data to learn regulatory networks for the quantification of potential impacts of individual gene expression alterations on user-defined target genes via network propagation. We demonstrate the value of regNet by identifying putative major regulators that distinguish pilocytic from diffuse astrocytomas and by predicting putative impacts of glioblastoma-specific gene copy number alterations on cell cycle pathway genes and patient survival. regNet is available for download at https://github.com/seifemi/regNet under GNU GPL-3. Supplementary data are available at Bioinformatics online.

Improved methods and resources for paramecium genomics: transcription units, gene annotation and gene expression

BackgroundThe 15 sibling species of the Paramecium aurelia cryptic species complex emerged after a whole genome duplication that occurred tens of millions of years ago. Given extensive knowledge of the genetics and epigenetics of Paramecium acquired over the last century, this species complex offers a uniquely powerful system to investigate the consequences of whole genome duplication in a unicellular eukaryote as well as the genetic and epigenetic mechanisms that drive speciation. High quality Paramecium gene models are important for research using this system. The major aim of the work reported here was to build an improved gene annotation pipeline for the Paramecium lineage.ResultsWe generated oriented RNA-Seq transcriptome data across the sexual process of autogamy for the model species Paramecium tetraurelia. We determined, for the first time in a ciliate, candidate P. tetraurelia transcription start sites using an adapted Cap-Seq protocol. We developed TrUC, multi-threaded Perl software that in conjunction with TopHat mapping of RNA-Seq data to a reference genome, predicts transcription units for the annotation pipeline. We used EuGene software to combine annotation evidence. The high quality gene structural annotations obtained for P. tetraurelia were used as evidence to improve published annotations for 3 other Paramecium species. The RNA-Seq data were also used for differential gene expression analysis, providing a gene expression atlas that is more sensitive than the previously established microarray resource.ConclusionsWe have developed a gene annotation pipeline tailored for the compact genomes and tiny introns of Paramecium species. A novel component of this pipeline, TrUC, predicts transcription units using Cap-Seq and oriented RNA-Seq data. TrUC could prove useful beyond Paramecium, especially in the case of high gene density. Accurate predictions of 3′ and 5′ UTR will be particularly valuable for studies of gene expression (e.g. nucleosome positioning, identification of cis regulatory motifs). The P. tetraurelia improved transcriptome resource, gene annotations for P. tetraurelia, P. biaurelia, P. sexaurelia and P. caudatum, and Paramecium-trained EuGene configuration are available through ParameciumDB (http://paramecium.i2bc.paris-saclay.fr). TrUC software is freely distributed under a GNU GPL v3 licence (https://github.com/oarnaiz/TrUC).

OMSim: a simulator for optical map data.

MotivationThe Bionano Genomics platform allows for the optical detection of short sequence patterns in very long DNA molecules (up to 2.5 Mbp). Molecules with overlapping patterns can be assembled to generate a consensus optical map of the entire genome. In turn, these optical maps can be used to validate or improve de novo genome assembly projects or to detect large-scale structural variation in genomes. Simulated optical map data can assist in the development and benchmarking of tools that operate on those data, such as alignment and assembly software. Additionally, it can help to optimize the experimental setup for a genome of interest. Such a simulator is currently not available.ResultsWe have developed a simulator, OMSim, that produces synthetic optical map data that mimics real Bionano Genomics data. These simulated data have been tested for compatibility with the Bionano Genomics Irys software system and the Irys-scaffolding scripts. OMSim is capable of handling very large genomes (over 30 Gbp) with high throughput and low memory requirements.Availability and implementationThe Python simulation tool and a cross-platform graphical user interface are available as open source software under the GNU GPL v2 license (http://www.bioinformatics.intec.ugent.be/omsim).Supplementary information Supplementary data are available at Bioinformatics online.

A method for learning a sparse classifier in the presence of missing data for high-dimensional biological datasets.

This work addresses two common issues in building classification models for biological or medical studies: learning a sparse model, where only a subset of a large number of possible predictors is used, and training in the presence of missing data. This work focuses on supervised generative binary classification models, specifically linear discriminant analysis (LDA). The parameters are determined using an expectation maximization algorithm to both address missing data and introduce priors to promote sparsity. The proposed algorithm, expectation-maximization sparse discriminant analysis (EM-SDA), produces a sparse LDA model for datasets with and without missing data. EM-SDA is tested via simulations and case studies. In the simulations, EM-SDA is compared with nearest shrunken centroids (NSCs) and sparse discriminant analysis (SDA) with k-nearest neighbors for imputation for varying mechanism and amount of missing data. In three case studies using published biomedical data, the results are compared with NSC and SDA models with four different types of imputation, all of which are common approaches in the field. EM-SDA is more accurate and sparse than competing methods both with and without missing data in most of the experiments. Furthermore, the EM-SDA results are mostly consistent between the missing and full cases. Biological relevance of the resulting models, as quantified via a literature search, is also presented. A Matlab implementation published under GNU GPL v.3 license is available at http://web.mit.edu/braatzgroup/links.html . braatz@mit.edu. Supplementary data are available at Bioinformatics online.

EmMAW: computing minimal absent words in external memory.

The biological significance of minimal absent words has been investigated in genomes of organisms from all domains of life. For instance, three minimal absent words of the human genome were found in Ebola virus genomes. There exists an O(n) -time and O(n) -space algorithm for computing all minimal absent words of a sequence of length n on a fixed-sized alphabet based on suffix arrays. A standard implementation of this algorithm, when applied to a large sequence of length n , requires more than 20 n bytes of RAM. Such memory requirements are a significant hurdle to the computation of minimal absent words in large datasets. We present emMAW, the first external-memory algorithm for computing minimal absent words. A free open-source implementation of our algorithm is made available. This allows for computation of minimal absent words on far bigger data sets than was previously possible. Our implementation requires less than 3 h on a standard workstation to process the full human genome when as little as 1 GB of RAM is made available. We stress that our implementation, despite making use of external memory, is fast; indeed, even on relatively smaller datasets when enough RAM is available to hold all necessary data structures, it is less than two times slower than state-of-the-art internal-memory implementations. https://github.com/solonas13/maw (free software under the terms of the GNU GPL). alice.heliou@lix.polytechnique.fr or solon.pissis@kcl.ac.uk. Supplementary data are available at Bioinformatics online.

Astrometry with A-Track Using Gaia DR1 Catalogue

AbstractIn this work, we built all sky index files from Gaia DR1 catalogue for the high-precision astrometric field solution and the precise WCS coordinates of the moving objects. For this, we used build-astrometry-index program as a part of astrometry.net code suit. Additionally, we added astrometry.net's WCS solution tool to our previously developed software which is a fast and robust pipeline for detecting moving objects such as asteroids and comets in sequential FITS images, called A-Track. Moreover, MPC module was added to A-Track. This module is linked to an asteroid database to name the found objects and prepare the MPC file to report the results. After these innovations, we tested a new version of the A-Track code on photometrical data taken by the SI-1100 CCD with 1-meter telescope at TÜBİTAK National Observatory, Antalya. The pipeline can be used to analyse large data archives or daily sequential data. The code is hosted on GitHub under the GNU GPL v3 license.

Activity computer program for calculating ion irradiation activation

A computer program, Activity, was developed to predict the activity and gamma lines of materials irradiated with an ion beam. It uses the TENDL (Koning and Rochman, 2012) [1] proton reaction cross section database, the Stopping and Range of Ions in Matter (SRIM) (Biersack et al., 2010) code, a Nuclear Data Services (NDS) radioactive decay database (Sonzogni, 2006) [2] and an ENDF gamma decay database (Herman and Chadwick, 2006) [3]. An extended version of Bateman’s equation is used to calculate the activity at time t, and this equation is solved analytically, with the option to also solve by numeric inverse Laplace Transform as a failsafe. The program outputs the expected activity and gamma lines of the activated material.Program summaryProgram title: ActivityCatalogue identifier: AFBS_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AFBS_v1_0.htmlProgram obtainable from: CPC Program Library, Queen’s University, Belfast, N. IrelandLicensing provisions: GNU GPL v3No. of lines in distributed program, including test data, etc.: 688828No. of bytes in distributed program, including test data, etc.: 71056048Distribution format: tar.gzProgramming language: Fortran.Computer: PCs or HPCs.Operating system: Linux (tested on Debian).Has the code been vectorized or parallelized?: OpenMPIRAM: 250MB per process + 200MB overheadClassification: 2.2, 17.8.Nature of problem: To calculate the predicted activity of an ion irradiated target. The expected range of ion energies is between 1MeV and 200MeV; this is the range of the available ion cross section data.Solution method: The program loads cross section data from the TENDL database and trajectory data from a SRIM [1] simulation exyz data file. It uses this data to calculate the production/loss rate of each isotope in the simulated target. Radioactive decay equations are used to calculate the amounts and activity of each radioactive isotope at the set time.Running time: Typically the Activity program runs each input from seconds to no more than several minutes.

Non-invasive Fetal ECG Signal Quality Assessment for Multichannel Heart Rate Estimation.

The noninvasive fetal ECG (NI-FECG) from abdominal recordings offers novel prospects for prenatal monitoring. However, NI-FECG signals are corrupted by various nonstationary noise sources, making the processing of abdominal recordings a challenging task. In this paper, we present an online approach that dynamically assess the quality of NI-FECG to improve fetal heart rate (FHR) estimation. Using a naive Bayes classifier, state-of-the-art and novel signal quality indices (SQIs), and an existing adaptive Kalman filter, FHR estimation was improved. For the purpose of training and validating the proposed methods, a large annotated private clinical dataset was used. The suggested classification scheme demonstrated an accuracy of Krippendorff's alpha in determining the overall quality of NI-FECG signals. The proposed Kalman filter outperformed alternative methods for FHR estimation achieving accuracy. The proposed algorithm was able to reliably reflect changes of signal quality and can be used in improving FHR estimation. NI-ECG signal quality estimation and multichannel information fusion are largely unexplored topics. Based on previous works, multichannel FHR estimation is a field that could strongly benefit from such methods. The developed SQI algorithms as well as resulting classifier were made available under a GNU GPL open-source license and contributed to the FECGSYN toolbox.

SPARC: Accurate and efficient finite-difference formulation and parallel implementation of Density Functional Theory: Extended systems

As the second component of SPARC (Simulation Package for Ab-initio Real-space Calculations), we present an accurate and efficient finite-difference formulation and parallel implementation of Density Functional Theory (DFT) for extended systems. Specifically, employing a local formulation of the electrostatics, the Chebyshev polynomial filtered self-consistent field iteration, and a reformulation of the non-local force component, we develop a finite-difference framework wherein both the energy and atomic forces can be efficiently calculated to within desired accuracies in DFT. We demonstrate using a wide variety of materials systems that SPARC achieves high convergence rates in energy and forces with respect to spatial discretization to reference plane-wave result; exponential convergence in energies and forces with respect to vacuum size for slabs and wires; energies and forces that are consistent and display negligible ‘egg-box’ effect; accurate properties of crystals, slabs, and wires; and negligible drift in molecular dynamics simulations. We also demonstrate that the weak and strong scaling behavior of SPARC is similar to well-established and optimized plane-wave implementations for systems consisting up to thousands of electrons, but with a significantly reduced prefactor. Overall, SPARC represents an attractive alternative to plane-wave codes for performing DFT simulations of extended systems. Program summaryProgram title: SPARCCatalogue identifier: AFBR_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AFBR_v1_0.htmlProgram obtainable from: CPC Program Library, Queen’s University, Belfast, N. IrelandLicensing provisions: GNU GPL v3No. of lines in distributed program, including test data, etc.: 93822No. of bytes in distributed program, including test data, etc.: 1386659Distribution format: tar.gzProgramming language: C/C++.Computer: Any system with C/C++ compiler.Operating system: Linux.RAM: Problem dependent. Ranges from 80 GB to 800 GB for a system with 2500 electrons.Classification: 7.3.External routines: PETSc 3.5.3 (http://www.mcs.anl.gov/petsc), MKL 11.2 (https://software.intel.com/en-us/intel-mkl), and MVAPICH2 2.1 (http://mvapich.cse.ohio-state.edu/).Does the new version supersede the previous version?: YesNature of problem: Calculation of the static and dynamic properties of isolated and extended systems in the framework of Kohn–Sham Density Functional Theory (DFT).Solution method:High-order finite-difference discretization. Local reformulation of the electrostatics in terms of the electrostatic potential and pseudocharge densities. Application of Bloch-periodic and zero-Dirichlet boundary conditions on the orbitals in the direction of periodicity and vacuum, respectively. Application of periodic and Dirichlet boundary conditions on the electrostatic potential in the direction of periodicity and vacuum, respectively. Integration over the Brillouin zone for extended systems using the Monkhorst–Pack grid. Calculation of the electronic ground-state using the Chebyshev polynomial filtered self-consistent field iteration in conjunction with Anderson based extrapolation/mixing schemes. Reformulation of the non-local component of the force. Geometry optimization using the Polak–Ribiere variant of non-linear conjugate gradients with secant line search. NVE molecular dynamics using the leapfrog method. Parallelization via domain decomposition and over Brillouin zone integration.Reasons for new version:To enable the study of extended systems like crystals, slabs, and wires using SPARC.Summary of revisions:Incorporated the ability to study the static and dynamic properties of crystals, slabs, and wires.Restrictions:System size less than ∼4000 electrons. Local Density Approximation (LDA). Troullier–Martins pseudopotentials without relativistic or non-linear core corrections. Domain has to be cuboidal.Running time:Problem dependent. Timing results for selected examples provided in the paper.

MINTmap: fast and exhaustive profiling of nuclear and mitochondrial tRNA fragments from short RNA-seq data

Transfer RNA fragments (tRFs) are an established class of constitutive regulatory molecules that arise from precursor and mature tRNAs. RNA deep sequencing (RNA-seq) has greatly facilitated the study of tRFs. However, the repeat nature of the tRNA templates and the idiosyncrasies of tRNA sequences necessitate the development and use of methodologies that differ markedly from those used to analyze RNA-seq data when studying microRNAs (miRNAs) or messenger RNAs (mRNAs). Here we present MINTmap (for MItochondrial and Nuclear TRF mapping), a method and a software package that was developed specifically for the quick, deterministic and exhaustive identification of tRFs in short RNA-seq datasets. In addition to identifying them, MINTmap is able to unambiguously calculate and report both raw and normalized abundances for the discovered tRFs. Furthermore, to ensure specificity, MINTmap identifies the subset of discovered tRFs that could be originating outside of tRNA space and flags them as candidate false positives. Our comparative analysis shows that MINTmap exhibits superior sensitivity and specificity to other available methods while also being exceptionally fast. The MINTmap codes are available through https://github.com/TJU-CMC-Org/MINTmap/ under an open source GNU GPL v3.0 license.

Quantitative morphological analysis of 2D images of complex-shaped branching biological growth forms: the example of branching thalli of liverworts

BackgroundMany organisms such as plants can be characterized as complex-shaped branching forms. The morphological quantification of the forms is a support for a number of areas such as the effects of environmental factors and species discrimination. To date, there is no software package suitable for our dataset representing the forms. We therefore formulate methods for extracting morphological measurements from images of the forms.ResultsAs a case study we analyze two-dimensional images of samples from four groups belonging to three species of thalloid liverworts, genus Riccardia. The images are pre-processed and converted into binary images, then skeletonized to obtain a skeleton image, in which features such as junctions and terminals are detected. Morphological measurements known to characterize and discriminate the species in the samples such as junction thickness, branch thickness, terminal thickness, branch length, branch angle, and terminal spacing are then quantified. The measurements are used to distinguish among the four groups of Riccardia and also between the two groups of Riccardia amazonica collected in different locations, Africa and South America. Canonical discriminant analysis results show that those measurements are able to discriminate among the four groups. Additionally, it is able to discriminate R. amazonica collected in Africa from those collected in South America.ConclusionsThis paper presents general automated methods implemented in our software for quantifying two-dimensional images of complex branching forms. The methods are used to compute a series of morphological measurements. We found significant results to distinguish Riccardia species by using the measurements. The methods are also applicable for analyzing other branching organisms. Our software is freely available under the GNU GPL.

OncoSimulR: genetic simulation with arbitrary epistasis and mutator genes in asexual populations.

SummaryOncoSimulR implements forward-time genetic simulations of biallelic loci in asexual populations with special focus on cancer progression. Fitness can be defined as an arbitrary function of genetic interactions between multiple genes or modules of genes, including epistasis, restrictions in the order of accumulation of mutations, and order effects. Mutation rates can differ among genes, and can be affected by (anti)mutator genes. Also available are sampling from simulations (including single-cell sampling), plotting the genealogical relationships of clones and generating and plotting fitness landscapes.Availability and ImplementationImplemented in R and C ++, freely available from BioConductor for Linux, Mac and Windows under the GNU GPL license. Version 2.5.9 or higher available from: http://www.bioconductor.org/packages/devel/bioc/html/OncoSimulR.html. GitHub repository at: https://github.com/rdiaz02/OncoSimulSupplementary information Supplementary data are available at Bioinformatics online.

PHAST: Protein-like heteropolymer analysis by statistical thermodynamics

PHAST is a software package written in standard Fortran, with MPI and CUDA extensions, able to efficiently perform parallel multicanonical Monte Carlo simulations of single or multiple heteropolymeric chains, as coarse-grained models for proteins. The outcome data can be straightforwardly analyzed within its microcanonical Statistical Thermodynamics module, which allows for computing the entropy, caloric curve, specific heat and free energies. As a case study, we investigate the aggregation of heteropolymers bioinspired on Aβ25−33 fragments and their cross-seeding with IAPP20−29 isoforms. Excellent parallel scaling is observed, even under numerically difficult first-order like phase transitions, which are properly described by the built-in fully reconfigurable force fields. Still, the package is free and open source, this shall motivate users to readily adapt it to specific purposes.Program summaryProgram Title: PHASTProgram Files doi:http://dx.doi.org/10.17632/ggds2grzw9.1Licensing provisions: GNU GPL version 3Programming language: FORTRAN 90, MPICH 3.0.4, CUDA 8.0Nature of the problem: Nowadays powerful multicore processors (CPUs) and Graphical Processing Units (GPUs) became much popular and cost-effective, so enabling thermostatistical studies of complex molecular systems to be performed even in personal computers. PHAST provides not only an easily-reconfigurable parallel program for Monte Carlo simulations of linear heteropolymers, as coarse-grained models of proteins, but also permits the automatized microcanonical thermodynamic analysis of those systems.Solution method: PHAST has three main modules for complementary tasks as: to map any .pdb file-sequence to its inner lexicon by using a configurable hydrophobic scale, while the main simulational module performs parallel Monte Carlo simulations in the multicanonical (MUCA) ensemble and, the analysis module which extracts microcanonical observables from MUCA weights.External routines/libraries: cuRAND (CUDA), Grace-5.1.22 or higher.

Mie calculation of electromagnetic near-field for a multilayered sphere

We have developed an algorithm to calculate electric and magnetic fields inside and around a multilayered sphere. The algorithm includes explicit expressions for Mie expansion coefficients inside the sphere and calculation of the vector spherical harmonics in terms of the Riccati–Bessel functions and their logarithmic derivatives. This novel approach has been implemented in the new version of our program scattnlay. Scattnlay 2.0 will be the first publicly available (at GitHub, https://github.com/ovidiopr/scattnlay) program, based on the Mie theory, which can calculate near-fields for the general case of a multilayer sphere. Several tests were designed to verify that the results obtained with our code match literature results and those obtained through similar programs (limited to core-shell structures) or full-wave 3D simulations. These tests demonstrate that the implementation is effective, yielding accurate values of electric and magnetic fields for a wide range of size parameters, number of layers, and refractive indices. Program summaryProgram title: scattnlay 2.0Catalogue identifier: AEEY_v2_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEEY_v2_0.htmlProgram obtainable from: CPC Program Library, Queen’s University, Belfast, N. IrelandLicensing provisions: GNU GPL v3No. of lines in distributed program, including test data, etc.: 34502No. of bytes in distributed program, including test data, etc.: 851543Distribution format: tar.gzProgramming language: C++11.Computer: Any computer with a C++11 compiler.Operating system: Linux (any version), Windows, Solaris.RAM: 1 Mb–100 MbClassification: 1.3.Does the new version supersede the previous version?: YesNature of problem: The scattering of electromagnetic (EM) radiation by a multilayered sphere is an interesting phenomenon which has recently drawn a great attention for application of tailor-made nanostructures in several fields like medicine (optical imaging and photothermal cancer therapy), atmospheric sciences (to study light absorption by aerosols), design of invisibility cloaks, etc. Expressions of scattering coefficients seem to be simple and straightforward to implement; however, they involve several numerical difficulties that make most of the existent algorithms inapplicable to several common cases. An improved recursive algorithm that circumvents most of the numerical problems present in previous algorithms has been developed by Yang [1]. This algorithm has been implemented in our program [2] to calculate the far-field parameters. In the updated version we have developed and implemented an efficient algorithm for the calculation of electric and magnetic fields inside and around multilayered spheres. In addition to the near-field calculations, the program includes some new functionalities, such as the possibility of including a layer composed of a perfect electrical conductor.Solution method: Calculation of Mie scattering coefficients and efficiency factors for a multilayered sphere as described by Yang [1], combined with standard solutions of the scattering amplitude functions. Determination of electric and magnetic fields using an algorithm developed in this work.Reasons for new version: To include calculations of electric and magnetic fields inside and around the particle.Summary of revisions: The code has been ported to C++11, which has given a cleaner and faster implementation. A new algorithm has been devised and implemented to include the calculation of near electric and magnetic fields. Finally, several small bug fixes and improvements to the original code have been made.Restrictions: Single scattering and permeability of the layers fixed to unity. Large complex part of layers refractive index leads to convergence problems.Running time: Seconds to minutes

R E C O L A—REcursive Computation of One-Loop Amplitudes

We present the Fortran95 program Recola for the perturbative computation of next-to-leading-order transition amplitudes in the Standard Model of particle physics. The code provides numerical results in the ’t Hooft–Feynman gauge. It uses the complex-mass scheme and allows for a consistent isolation of resonant contributions. Dimensional regularization is employed for ultraviolet and infrared singularities, with the alternative possibility of treating collinear and soft singularities in mass regularization. Recola supports various renormalization schemes for the electromagnetic and a dynamical Nf-flavour scheme for the strong coupling constant. The calculation of next-to-leading-order squared amplitudes, summed over spin and colour, is supported as well as the computation of colour- and spin-correlated leading-order squared amplitudes needed in the dipole subtraction formalism. Program summaryProgram Title:RecolaProgram Files doi:http://dx.doi.org/10.17632/mtzkz47y8r.1Licensing provisions: GNU GPL version 3Programming language:Fortran95Nature of problem: Evaluation of general tree-level and one-loop scattering amplitudes occurring in the calculation of observables in relativistic quantum field theoriesSolution method: Tree-level and one-loop amplitudes are numerically calculated using a recursive algorithm. For one-loop amplitudes numerical results for tensor integrals are needed as input. These are provided by the Collier library. In addition, contributions of counterterms and rational terms are determined via dedicated Feynman rules.Restrictions: The code has been used for processes with up to 7 external particles at one-loop level and up to 9 external particles at tree level. For large multiplicities available internal storage may cause limitations.External routines/libraries:Collier library

COPAR: A ChIP-Seq Optimal Peak Analyzer.

Sequencing data quality and peak alignment efficiency of ChIP-sequencing profiles are directly related to the reliability and reproducibility of NGS experiments. Till now, there is no tool specifically designed for optimal peak alignment estimation and quality-related genomic feature extraction for ChIP-sequencing profiles. We developed open-sourced COPAR, a user-friendly package, to statistically investigate, quantify, and visualize the optimal peak alignment and inherent genomic features using ChIP-seq data from NGS experiments. It provides a versatile perspective for biologists to perform quality-check for high-throughput experiments and optimize their experiment design. The package COPAR can process mapped ChIP-seq read file in BED format and output statistically sound results for multiple high-throughput experiments. Together with three public ChIP-seq data sets verified with the developed package, we have deposited COPAR on GitHub under a GNU GPL license.

MASTR-MS: a web-based collaborative laboratory information management system (LIMS) for metabolomics

BackgroundAn increasing number of research laboratories and core analytical facilities around the world are developing high throughput metabolomic analytical and data processing pipelines that are capable of handling hundreds to thousands of individual samples per year, often over multiple projects, collaborations and sample types. At present, there are no Laboratory Information Management Systems (LIMS) that are specifically tailored for metabolomics laboratories that are capable of tracking samples and associated metadata from the beginning to the end of an experiment, including data processing and archiving, and which are also suitable for use in large institutional core facilities or multi-laboratory consortia as well as single laboratory environments.Results Here we present MASTR-MS, a downloadable and installable LIMS solution that can be deployed either within a single laboratory or used to link workflows across a multisite network. It comprises a Node Management System that can be used to link and manage projects across one or multiple collaborating laboratories; a User Management System which defines different user groups and privileges of users; a Quote Management System where client quotes are managed; a Project Management System in which metadata is stored and all aspects of project management, including experimental setup, sample tracking and instrument analysis, are defined, and a Data Management System that allows the automatic capture and storage of raw and processed data from the analytical instruments to the LIMS.ConclusionMASTR-MS is a comprehensive LIMS solution specifically designed for metabolomics. It captures the entire lifecycle of a sample starting from project and experiment design to sample analysis, data capture and storage. It acts as an electronic notebook, facilitating project management within a single laboratory or a multi-node collaborative environment. This software is being developed in close consultation with members of the metabolomics research community. It is freely available under the GNU GPL v3 licence and can be accessed from, https://muccg.github.io/mastr-ms/.

Density of optical states in rolled-up photonic crystals and quasi crystals

We describe the local density of optical states (LDOS) and the density of optical states (DOS) in three dimensional (3D) finite size rolled-up photonic crystals and quasi crystals calculated using optimized code based on finite difference time domain (FDTD) techniques. Because the Bloch–Floquet theorem is not used in these calculations, the code can be applied to any dielectric structures that lack discrete translational symmetry, making it ideal for experimentally fabricated structures that are finite in size and include defects. Our software can be used for either LDOS or DOS calculations, is parallelized using standard message passing interface (MPI) protocols, and is freely available at www.fpspackage.com. Program summaryProgram title: FPSCatalogue identifier: AFBP_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AFBP_v1_0.htmlProgram obtainable from: CPC Program Library, Queen’s University, Belfast, N. IrelandLicensing provisions: GNU GPL v3No. of lines in distributed program, including test data, etc.: 118342No. of bytes in distributed program, including test data, etc.: 2385803Distribution format: tar.gzProgramming language:C++.Computer: PCs and distributed memory machines.Operating system: Linux, Unix.Has the code been vectorised or parallelized?: Parallelized using message passing interface.RAM: Depending on the problem; gigabytes.Classification: 10.External routines: Minimum: MPI; [1] fftw3; [2] optional: hdf5-tools. [3]Nature of problem: The aim of FPS is providing a fast and easy to use package for studying local density of optical states and density of optical states in arbitrary shaped finite size photonic structures.Solution method: Parallel finite difference time domain method.Restrictions: The post processing codes are not parallelized. At least two processes should be used for the calculations.Unusual features: FPS provides non-experts in computational physics an intuitive tool to obtain local density of optical states and density of optical states calculations. Inserting parameters that define the geometry and the spectrums of interest into a “txt” or “h5” file are all a user needs to do.Additional comments: The package includes a tutorial describing the package and its installation, using an example.Running time: It was found that the average time to compute a single LDOS was 21 minutes. Runtime in general depends on mesh size and the number of points that local density of optical states should be calculated.