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How to Use VAMPS

  • Introduction

  • Community Visualization - Heatmap Comparison

  • Community Visualization - Taxonomy Tables

  • Exporting Taxonomic Counts

  • Exporting Clustering and Diversity Data

  • Exporting Fasta Sequences

  • Introduction

    What is VAMPS?

    VAMPS is a set of tools for comparing microbe populations. VAMPS is comprised of two different types of tools, tools for visual analysis and tools for data export.

    Visual Analysis

    The Community Visualization tools are graphical tools for comparing microbe populations. The VAMPS graphical representation of data makes it easy to get an overview over what is happening at different data collecting sites. Taxonomy and composition can be viewed via heatmaps, phylogenetic trees, and piechart comparisons, enabling researchers to get a quicker understanding of their data.

    Data available for export

    Data available for download include trimmed fasta sequences, taxonomic counts, and clustering and rarefaction (diversity) data. These data files are available for data which have been through the Bay Paul Center 454 processing pipeline. A registered user can download data for their own projects and for public data. A guest user can download data for public projects only.

    Projects and Datasets

    All data in VAMPS must be associated with a project name and a dataset name. Each registered user has access to their own projects as well as projects which have been published and made available to the public.

    Projects are defined by a project name, a project title, and a project description. The project naming convention includes a suffix, Bv6, Av6, Ev9, etc., indicating whether the domain of the project is archaea, bacteria, or eukarya, and which hypervariable region, v3, v6, or v9, is being utilized.

    A Dataset will be data from one particular sample, for example from a specific location, water depth, or biopsy sample. Multiple samples can be combined across projects and datasets for convenience by using the Custom Dataset functionality.

    Because different data samples will necessarily be of different sizes, the data will be normalized to eliminate these differences. The user has the option to see the absolute counts of data samples, or see the counts normalized to either maximum sample size or percentage composition. See the FAQ section for an explanation of how the datasets are normalized.

    See more information about projects and datasets in our Frequently Asked Questions section.

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