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https://www.readbyqxmd.com/read/28431529/hirbin-high-resolution-identification-of-differentially-abundant-functions-in-metagenomes
#1
Tobias Österlund, Viktor Jonsson, Erik Kristiansson
BACKGROUND: Gene-centric analysis of metagenomics data provides information about the biochemical functions present in a microbiome under a certain condition. The ability to identify significant differences in functions between metagenomes is dependent on accurate classification and quantification of the sequence reads (binning). However, biological effects acting on specific functions may be overlooked if the classes are too general. METHODS: Here we introduce High-Resolution Binning (HirBin), a new method for gene-centric analysis of metagenomes...
April 21, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28409116/prepare_taxa_charts-py-a-python-program-to-automate-generation-of-publication-ready-taxonomic-pie-chart-images-from-qiime
#2
Vijay Lakhujani, Chandan Badapanda
QIIME (Quantitative Insights Into Microbial Ecology) is one of the most popular open-source bioinformatics suite for performing metagenome, 16S rRNA amplicon and Internal Transcribed Spacer (ITS) data analysis. Although, it is very comprehensive and powerful tool, it lacks a method to provide publication ready taxonomic pie charts. The script plot_taxa_summary.py bundled with QIIME generate a html file and a folder containing taxonomic pie chart and legend as separate images. The images have randomly generated alphanumeric names...
June 2017: Genomics Data
https://www.readbyqxmd.com/read/28403240/snovault-and-encoded-a-novel-object-based-storage-system-and-applications-to-encode-metadata
#3
Benjamin C Hitz, Laurence D Rowe, Nikhil R Podduturi, David I Glick, Ulugbek K Baymuradov, Venkat S Malladi, Esther T Chan, Jean M Davidson, Idan Gabdank, Aditi K Narayana, Kathrina C Onate, Jason Hilton, Marcus C Ho, Brian T Lee, Stuart R Miyasato, Timothy R Dreszer, Cricket A Sloan, J Seth Strattan, Forrest Y Tanaka, Eurie L Hong, J Michael Cherry
The Encyclopedia of DNA elements (ENCODE) project is an ongoing collaborative effort to create a comprehensive catalog of functional elements initiated shortly after the completion of the Human Genome Project. The current database exceeds 6500 experiments across more than 450 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the H. sapiens and M. musculus genomes. All ENCODE experimental data, metadata, and associated computational analyses are submitted to the ENCODE Data Coordination Center (DCC) for validation, tracking, storage, unified processing, and distribution to community resources and the scientific community...
2017: PloS One
https://www.readbyqxmd.com/read/28402395/mzml2isa-nmrml2isa-generating-enriched-isa-tab-metadata-files-from-metabolomics-xml-data
#4
Martin Larralde, Thomas N Lawson, Ralf J M Weber, Pablo Moreno, Kenneth Haug, Philippe Rocca-Serra, Mark R Viant, Christoph Steinbeck, Reza M Salek
Summary: Submission to the MetaboLights repository for metabolomics data currently places the burden of reporting instrument and acquisition parameters in ISA-Tab format on users, who have to do it manually, a process that is time consuming and prone to user input error. Since the large majority of these parameters are embedded in instrument raw data files, an opportunity exists to capture this metadata more accurately. Here we report a set of Python packages that can automatically generate ISA-Tab metadata file stubs from raw XML metabolomics data files...
April 7, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28398502/pygold-a-python-based-api-for-docking-based-virtual-screening-workflow-generation
#5
Hitesh Patel, Tobias Brinkjost, Oliver Koch
Motivation: Molecular docking is one of the successful approaches in structure based discovery and development of bioactive molecules in chemical biology and medicinal chemistry. Due to the huge amount of computational time that is still required, docking is often the last step in a virtual screening approach. Such screenings are set as workflows spanned over many steps, each aiming at different filtering task. These workflows can be automatized in large parts using python based toolkits except for docking using the docking software GOLD...
April 7, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28388874/pgltools-a-genomic-arithmetic-tool-suite-for-manipulation-of-hi-c-peak-and-other-chromatin-interaction-data
#6
William W Greenwald, He Li, Erin N Smith, Paola Benaglio, Naoki Nariai, Kelly A Frazer
BACKGROUND: Genomic interaction studies use next-generation sequencing (NGS) to examine the interactions between two loci on the genome, with subsequent bioinformatics analyses typically including annotation, intersection, and merging of data from multiple experiments. While many file types and analysis tools exist for storing and manipulating single locus NGS data, there is currently no file standard or analysis tool suite for manipulating and storing paired-genomic-loci: the data type resulting from "genomic interaction" studies...
April 7, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28379466/mackinac-a-bridge-between-modelseed-and-cobrapy-to-generate-and-analyze-genome-scale-metabolic-models
#7
Michael Mundy, Helena Mendes-Soares, Nicholas Chia
Summary: Reconstructing and analyzing a large number of genome-scale metabolic models is a fundamental part of the integrated study of microbial communities; however, two of the most widely used frameworks for building and analyzing models use different metabolic network representations. Here we describe Mackinac, a Python package that combines ModelSEED's ability to automatically reconstruct metabolic models with COBRApy's advanced analysis capabilities to bridge the differences between the two frameworks and facilitate the study of the metabolic potential of microorganisms...
August 30, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28369284/spresso-an-ultrafast-compound-pre-screening-method-based-on-compound-decomposition
#8
Keisuke Yanagisawa, Shunta Komine, Shogo D Suzuki, Masahito Ohue, Takashi Ishida, Yutaka Akiyama
Motivation: Recently, the number of available protein tertiary structures and compounds has increased. However, structure-based virtual screening is computationally expensive owing to docking simulations. Thus, methods that filter out obviously unnecessary compounds prior to computationally expensive docking simulations have been proposed. However, the calculation speed of these methods is not fast enough to evaluate ≥ 10 million compounds. Results: In this article, we propose a novel, docking-based pre-screening protocol named Spresso (Speedy PRE-Screening method with Segmented cOmpounds)...
March 29, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28369168/conkit-a-python-interface-to-contact-predictions
#9
Felix Simkovic, Jens M H Thomas, Daniel J Rigden
Summary: Recent advances in protein residue contact prediction algorithms have led to the emergence of many new methods and a variety of file formats. We present ConKit , an open source, modular and extensible Python interface which allows facile conversion between formats and provides an interface to analyses of sequence alignments and sets of contact predictions. Availability and implementation: ConKit is available via the Python Package Index. The documentation can be found at http://www...
March 22, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28369166/cpipe-a-comprehensive-computational-platform-for-sequence-and-structure-based-analyses-of-cysteine-residues
#10
Inanc Soylu, Stefano M Marino
Summary: Due to their chemical plasticity, Cysteine residues (Cys) can serve many different functions. Identification and classification of reactive Cys isn't a trivial job: currently, no available tool exists for an all-round, comprehensive (inclusive of all different functional types) analysis of Cys; herein we present a computational platform called Cp i pe, dedicated to this task: it implements state-of-the art protocols, elaborating and displaying a wealth of information, sufficiently orthogonal to allow a thorough evaluation of all major aspects of Cys reactivity...
March 29, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28334360/hla-ma-simple-yet-powerful-matching-of-samples-using-hla-typing-results
#11
Clemens Messerschmidt, Manuel Holtgrewe, Dieter Beule
Summary: We propose the simple method HLA-MA for consistency checking in pipelines operating on human HTS data. The method is based on the HLA typing result of the state-of-the-art method OptiType. Provided that there is sufficient coverage of the HLA loci, comparing HLA types allows for simple, fast, and robust matching of samples from whole genome, exome, and RNA-seq data. Our approach uses information from small but genetically highly variable regions and thus complements approaches that rely on genome or exon-wide variant profiles...
March 9, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28334266/phenopolis-an-open-platform-for-harmonization-and-analysis-of-genetic-and-phenotypic-data
#12
Nikolas Pontikos, Jing Yu, Ismail Moghul, Lucy Withington, Fiona Blanco-Kelly, Tom Vulliamy, Tsz Lun Wong, Cian Murphy, Valentina Cipriani, Alessia Fiorentino, Gavin Arno, Daniel Greene, Julius Ob Jacobsen, Tristan Clark, David S Gregory, Andrea Nemeth, Stephanie Halford, Chris F Inglehearn, Susan Downes, Graeme C Black, Andrew R Webster, Alison J Hardcastle, Vincent Plagnol
Summary: Phenopolis is an open-source web server providing an intuitive interface to genetic and phenotypic databases. It integrates analysis tools such as variant filtering and gene prioritisation based on phenotype. The Phenopolis platform will accelerate clinical diagnosis, gene discovery and encourage wider adoption of the Human Phenotype Ontology in the study of rare genetic diseases. Availability and Implementation: A demo of the website is available at https://phenopolis...
March 15, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28334194/swga-a-primer-design-toolkit-for-selective-whole-genome-amplification
#13
Erik L Clarke, Sesh A Sundararaman, Stephanie N Seifert, Frederic D Bushman, Beatrice H Hahn, Dustin Brisson
Motivation: Population genomic analyses are often hindered by difficulties in obtaining sufficient numbers of genomes for analysis by DNA sequencing. Selective whole-genome amplification (SWGA) provides an efficient approach to amplify microbial genomes from complex backgrounds for sequence acquisition. However, the process of designing sets of primers for this method has many degrees of freedom and would benefit from an automated process to evaluate the vast number of potential primer sets...
February 27, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28327957/nanosim-nanopore-sequence-read-simulator-based-on-statistical-characterization
#14
Chen Yang, Justin Chu, René L Warren, Inanç Birol
Background: The MinION sequencing instrument from Oxford Nanopore Technologies (ONT) produces long read lengths from single-molecule sequencing - valuable features for detailed genome characterization. To realize the potential of this platform, a number of groups are developing bioinformatics tools tuned for the unique characteristics of its data. We note that these development efforts would benefit from a simulator software, output of which could be used to benchmark analysis tools. Findings: Here, we introduce NanoSim, a fast and scalable read simulator that captures the technology-specific features of ONT data, and allows for adjustments upon improvement of nanopore sequencing technology...
February 24, 2017: GigaScience
https://www.readbyqxmd.com/read/28231302/bioinformatic-prediction-of-g-protein-coupled-receptor-encoding-sequences-from-the-transcriptome-of-the-foreleg-including-the-haller-s-organ-of-the-cattle-tick-rhipicephalus-australis
#15
Sergio Munoz, Felix D Guerrero, Anastasia Kellogg, Andrew M Heekin, Ming-Ying Leung
The cattle tick of Australia, Rhipicephalus australis, is a vector for microbial parasites that cause serious bovine diseases. The Haller's organ, located in the tick's forelegs, is crucial for host detection and mating. To facilitate the development of new technologies for better control of this agricultural pest, we aimed to sequence and annotate the transcriptome of the R. australis forelegs and associated tissues, including the Haller's organ. As G protein-coupled receptors (GPCRs) are an important family of eukaryotic proteins studied as pharmaceutical targets in humans, we prioritized the identification and classification of the GPCRs expressed in the foreleg tissues...
2017: PloS One
https://www.readbyqxmd.com/read/28184232/bioinformatics-prediction-and-evolution-analysis-of-arabinogalactan-proteins-in-the-plant-kingdom
#16
Yuling Ma, Chenchao Yan, Huimin Li, Wentao Wu, Yaxue Liu, Yuqian Wang, Qin Chen, Haoli Ma
Arabinogalactan proteins (AGPs) are a family of extracellular glycoproteins implicated in plant growth and development. With a rapid growth in the number of genomes sequenced in many plant species, the family members of AGPs can now be predicted to facilitate functional investigation. Building upon previous advances in identifying Arabidopsis AGPs, an integrated strategy of systematical AGP screening for "classical" and "chimeric" family members is proposed in this study. A Python script named Finding-AGP is compiled to find AGP-like sequences and filter AGP candidates under the given thresholds...
2017: Frontiers in Plant Science
https://www.readbyqxmd.com/read/28130233/a-comprehensive-quality-control-workflow-for-paired-tumor-normal-ngs-experiments
#17
Christopher M Schroeder, Franz J Hilke, Markus W Löffler, Michael Bitzer, Florian Lenz, Marc Sturm
Quality control (QC) is an important part of all NGS data analysis stages. Many available tools calculate QC metrics from different analysis steps of single sample experiments (raw reads, mapped reads and variant lists). Multi-sample experiments, as sequencing of tumor-normal pairs, require additional QC metrics to ensure validity of results. These multi-sample QC metrics still lack standardization. We therefore suggest a new workflow for QC of DNA sequencing of tumor-normal pairs. With this workflow well-known single-sample QC metrics and additionally metrics specific for tumor-normal pairs can be calculated...
January 27, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28104627/mappi-dat-data-management-and-analysis-for-protein-protein-interaction-data-from-the-high-throughput-mappit-cell-microarray-platform
#18
Surya Gupta, Veronic De Puysseleyr, José Van der Heyden, Davy Maddelein, Irma Lemmens, Sam Lievens, Sven Degroeve, Jan Tavernier, Lennart Martens
Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge...
January 18, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28093409/deuterater-a-tool-for-quantifying-peptide-isotope-precision-and-kinetic-proteomics
#19
Bradley C Naylor, Michael T Porter, Elise Wilson, Adam Herring, Spencer Lofthouse, Austin Hannemann, Stephen R Piccolo, Alan L Rockwood, John C Price
MOTIVATION: Using mass spectrometry to measure the concentration and turnover of the individual proteins in a proteome, enables the calculation of individual synthesis and degradation rates for each protein. Software to analyze concentration is readily available, but software to analyze turnover is lacking. Data analysis workflows typically don't access the full breadth of information about instrument precision and accuracy that is present in each peptide isotopic envelope measurement...
January 16, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28076851/pse-analysis-a-python-package-for-dna-rna-and-protein-peptide-sequence-analysis-based-on-pseudo-components-and-kernel-methods
#20
Bin Liu, Hao Wu, Deyuan Zhang, Xiaolong Wang, Kuo-Chen Chou
To expedite the pace in conducting genome/proteome analysis, we have developed a Python package called Pse-Analysis. The powerful package can automatically complete the following five procedures: (1) sample feature extraction, (2) optimal parameter selection, (3) model training, (4) cross validation, and (5) evaluating prediction quality. All the work a user needs to do is to input a benchmark dataset along with the query biological sequences concerned. Based on the benchmark dataset, Pse-Analysis will automatically construct an ideal predictor, followed by yielding the predicted results for the submitted query samples...
February 21, 2017: Oncotarget
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