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检索条件"主题词=Programming Language"

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Freshwater Viromes: From Sampling to Evaluation

Freshwater Viromes: From Sampling to Evaluation

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作者： Catherine Putonti Zoë Diener Siobhan C. Watkins

There are a number of options available to researchers who wish to collect and analyze viral metagenomes (viromes) from environmental samples. Here we describe a laboratory procedure for generation of viromes from freshwater samples, specifically targeting dsDNA bacteriophages. We also discuss methods for bioinformatic analysis of the resulting data. less

关键词： Metagenomics Nucleic Acid Extraction Library Preparation Genomics Trimmomatic Data analysis Python programming language tangential flow filtration Viruses Bacteriophage Viromes Viral bioinformatics

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R for Genome-Wide Association Studies

R for Genome-Wide Association Studies

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作者： Cedric Gondro Laercio R. Porto-Neto Seung Hwan Lee

In recent years R has become de facto statistical programming language of choice for statisticians and it is also arguably the most widely used generic environment for analysis of high-throughput genomic data. In this... 详细信息

关键词： programming language Genome-wide association studies High-throughput analysis R programming Parallel computation

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High-Resolution ChIP-MNaseChIP-MNase Mapping of Nucleosome Positions at Selected Genomic Loci and Alleles

High-Resolution ChIP-MNaseChIP-MNase Mapping of Nucleosome P...

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作者： Dominic van Essen Agata Oruba Simona Saccani

The positioning of nucleosomes regulates the accessibility of genomic DNA and can impact the activities of functional elements. Nucleosome positioning is highly consistent at each genomic location in any particular cell-type, but can vary in an orchestrated fashion between different cell-types and between genomic loci according to their activities. Here, we describe a technique—“ChIP-MNase” (chromatin immunoprecipitation linked to micrococcal nuclease mapping)—to determine nucleosome positions at chosen sets of genomic features that can be defined by their molecular composition and recovered by chromatin immunoprecipitation. ChIP-MNase enables high-resolution analysis of nucleosome positioning at genomic regions-of-interest and can allow differential analysis of alleles undergoing distinct molecular processes. less

关键词： ChIP Assay Cell And Tissue Culture Cross-linking Titration Capillary Electrophoresis (CE) Sonication Freeze-thaw Method Immunoprecipitation High-Throughput Sequencing PCR Capillary Gel Electrophoresis Library Preparation Genome Visualization DNA Purification Gel Electrophoresis Bowtie Data analysis bedtools programming language Nucleosomes Chromatin Chromatin accessibility Micrococcal nuclease

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Bioinformatics Analysis of the Receptor-Like Kinase (RLK) Superfamily

Bioinformatics Analysis of the Receptor-Like Kinase (RLK) Su...

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作者： Otávio J. Brustolini José Cleydson Silva Tetsu Sakamoto Elizabeth P. Fontes

Receptor-like kinases (RLKs) play key roles during development and in responses to the environment. In plant immunity, some members of RLKs function as pattern recognition receptors (PRRs), which, upon recognition of pathogen-associated molecular patterns (PAMP), are recruited into active complexes to induce pathogen-triggered immunity (PTI). In this chapter, we describe the bioinformatics tools and procedures for the identification and phylogenetic classification of RLKs from different plant species as a framework for understanding RLK function in signal transduction and immunity. less

关键词： Genomics Phylogenetics Ensembl programming language Arabidopsis thaliana Homo sapiens Ectodomain Receptor-like kinase (RLK) Leucine-rich repeat (LRR) Serine/threonine kinase domain Pattern recognition receptors (PRR)

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Pipeline for Integrated Microarray Expression Normalization Tool Kit (PIMENTo) for Tumor Microarray Profiling Experiments

Pipeline for Integrated Microarray Expression Normalization ...

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作者： Thomas Nash Matthew Huff W. Bailey Glen Gary Hardiman

We have developed a Pipeline for Integrated Microarray Expression & Normalization Tool kit (PIMENTo) with the aim of streamlining the processes necessary for gene expression analysis in tumor tissue using DNA microarrays. Built with the R programming language and leveraging several open-source packages available through CRAN and Bioconductor, PIMENTo enables researchers to perform complex tasks with a minimal number of operations. Here, we describe the pipeline, review necessary data inputs, examine data outputs and quality control assessments and explore the commands to perform such analysis. less

关键词： Microarray Gene Expression Analysis Principal Component Analysis programming language Mus musculus R Quality control Normalization Tumor Genomic profiling Illumina Bead arrays

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Characterization of the Rat Gut Microbiota via 16S rRNA Amplicon Library Sequencing

Characterization of the Rat Gut Microbiota via 16S rRNA Ampl...

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作者： Aaron C. Ericsson Susheel B. Busi James M. Amos-Landgraf

It is becoming increasingly apparent that microbiota have measurable effects on numerous phenotypes in laboratory animals. This “second genome” has often been disregarded or ignored due to its commensal nonpathogenic nature, and the difficulty, expense, and analysis of sequence. Recent advances in sequencing methods and analyses of large datasets have made characterization of microbiota populations routine and have uncovered previously unknown relationships of microbial communities and host biological systems. The largest and most diverse microbial community in the laboratory rat is in the gut, and has been shown to affect the physiology of the whole animal, and genetic disease penetrance. We present here a cost-effective method for the characterization of the rat fecal microbiota through multiplexed 16S ribosomal sequencing and freely available software. less

关键词： DNA Extraction Library Preparation PCR Statistical Calculation 16s rRNA Sequencing Principal Component Analysis Shotgun Sequencing Data analysis programming language Rattus norvegicus Sequencing Microbiota 16S rRNA gene Operational taxonomic unit (OTU)

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Transcriptome Profiling of Single Mouse Oocytes

Transcriptome Profiling of Single Mouse Oocytes

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作者： Maud Borensztein Laurène Syx Nicolas Servant Edith Heard

Single-cell RNA-sequencing (scRNAseq) enables the detection and quantification of mature RNAs in an individual cell. Assessing single cell transcriptomes can circumvent the limited amount of starting material obtained in oocytes or embryos, in particular when working with mutant mice. Here we outline our scRNAseq protocol to study mouse oocyte transcriptomes, derived from Tang et al., Nat Methods 6(5):377–382, 2009 . The method describes the different steps from single cell isolation and cDNA amplification to high-throughput sequencing. The bioinformatics pipeline used to analyze and compare genome-wide gene expression between individual oocytes is then described. less

关键词： Single-cell RNA-seq CDNA Amplification Real-time PCR Single-cell Isolation High-Throughput Sequencing PCR Cell Lysis Sonication Library Preparation Differential Expression Analysis RNA-seq Gene Expression Profiling Cell And Tissue Culture Dissection Agarose Gel Electrophoresis Genome Visualization Python programming language TopHat Mus musculus Gene expression Maternal pool Single-cell bioinformatics pipeline

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Metagenomics Data Visualization Using R

Metagenomics Data Visualization Using R

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作者： Alex Coleman Anupam Bose Suparna Mitra

Communicating key finds is a crucial part of the research process. Data visualization is the field of graphically representing data to help communicate key findings. Building on previous chapters around data manipulating using the R programming language this, chapter will explore how to use R to plot data and generate high-quality graphics. It will cover plotting using the base R plotting functionality and introduce the famous ggplot2 package [2] that is widely used for data visualization in R. After this general introduction to data visualization tools, the chapter will explore more specific data visualization techniques for metagenomics data and their use cases using these basic packages. less

关键词： programming language Metagenomics Data Visualization Tools Data visualization ggplot2 Plotting Communication Research outputs Research visualization

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Finding Gene Associations by Text Mining and Annotating it with Gene Ontology

Finding Gene Associations by Text Mining and Annotating it w...

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作者： Oviya Ramalakshmi Iyyappan Sharanya Manoharan

Digitalization of the research articles and their maintenance in a database was the first stage toward the development of biomedical research. With the large amounts of research being published daily, it has created a large gap in accessing all the articles for review to a given problem. To understand any biological process, an insight into the role of each element in the genome is essential. But with this gap in manual curation of literature, there are chances that important biological information may be lost. Hence, text mining plays an important role in bridging this gap and extracting important biological information from the text, finding associations among them and predicting annotations. An annotation may be gene, gene products, gene names, their physical and functional characteristics, and so on. The process of annotations may be classified as structural annotation, functional annotation, and relational annotation. In this chapter, a basic protocol utilizing text mining to extract biological information and predict their functional role based on Gene Ontology is provided. less

关键词： Text Mining programming language Python Expasy Protein Analysis Proteomics Statistical Calculation Functional annotation Semantic similarity MeSH terms Gene Ontology (GO) Gene function prediction

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Mining of Single-Cell Signaling Time-Series for Dynamic Phenotypes with Clustering

Mining of Single-Cell Signaling Time-Series for Dynamic Phen...

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作者： Maciej Dobrzyński Marc-Antoine Jacques Olivier Pertz

Fluorescent live cell time-lapse microscopy is steadily contributing to our better understanding of the relationship between cell signaling and fate. However, large volumes of time-series data generated in these experiments and the heterogenous nature of signaling responses due to cell-cell variability hinder the exploration of such datasets. The population averages insufficiently describe the dynamics, yet finding prototypic dynamic patterns that relate to different cell fates is difficult when mining thousands of time-series. Here we demonstrate a protocol where we identify such dynamic phenotypes in a population of PC-12 cells that respond to a range of sustained growth factor perturbations. We use Time-Course Inspector, a free R/Shiny web application to explore and cluster single-cell time-series. less

关键词： Data analysis Time Lapse Microscopy Statistical Calculation FRET programming language Clustering Computational biology Signaling dynamics Signal processing Time-series Single-cell data Cell-cell heterogeneity

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