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volcano-plot's Introduction

Overview

Volcano Plot is a JavaScript library that creates linked volcano plots for viewing data trends across multiple domains simultaneously. Volcano Plot includes interactive features like filtering, point highlighting, brushing, search, and dynamic listings.

[Screenshot Coming Soon]

Background

A volcano plot a popular visualization for assessing effect size against statistical significance, especially in omics research, which is typified by dense data sets where tools are needed to extract signals of interest from the “noise” of the data. The typical volcano plot design charts logarithmic p-values on the y-axis with a measure of effect (e.g., odds ratio, fold change) plotted on the x-axis. The resulting chart commonly displays a parabolic data distribution (giving the appearance of a volcano erupting), which effectively emphasizes the data points that have a high degree of statistical significance by visually separating them from the non-significant data.

Typical Usage

Coming Soon

More Information

Documentation link Examples link Related libraries

volcano-plot's People

Contributors

jwildfire avatar samussiah avatar rbudrevich avatar

Stargazers

Freeman Wang avatar timelyportfolio avatar

Watchers

timelyportfolio avatar James Cloos avatar  avatar Ryan Bailey avatar  avatar Britt Sikora Drake avatar Dane Dexheimer avatar  avatar Derek Lawrence avatar

volcano-plot's Issues

Basic Server with file upload

Add a basic server that can accept uploaded datasets and settings objects and provide API calls to retrieve both to plug into the renderer.

Treat each small multiple as an object

Currently the plots are handled collectively and (one way or another) all plotting methods run in a loop on a d3 selection of multiple svgs. (chart.plots.svgs.each(function(d, i) {...}) This is a bit of a mess for more complex interactions, like the one we need to implement for brushing in #30 .

Goal is to Refactor to treat each plot as a unique object with it's own methods, then each chart can easily have it's own components (like brushes) and can be called directly on the chart (multiple.brush.init()).

Data Set Refactor for Brushing

Brushing a large number of points is slow in the current implementation. Almost certainly because we're running this chunk on every panel.

d.values.forEach(function(e){
    e.overlay = currentIDs.indexOf(e[settings.vars.id])>-1
})

Consider the best way to refactor the process.

Add Table Summary

Add Table View from v0.1 to v0.2.

When a user brushes the charts, a table listing of selected points should be shown.

Refactor this code from the pilot

Add filtering

Allow users to filter the points shown in the plots using the buttons at the top of the page.

The pilot code for building the phylum filters is here, but we'll probably want to have a design discussion about the best way to create new filters. The paradigm used for webcharts controls might be useful

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