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Visualization: D3
series_item
David
snipspector_adv
/snipspector_adv/vis_d3/
30

In the following section we will give you a gentle introduction on how to create a component for BioJS 2.0. As a case study, we will continue working with chromosome data and show you how to visualize this data with D3. First of all create a new folder called biojs-vis-snipspector by running slush biojs. We will use this as our working bench and only edit the index.js file inside the lib folder. Note: Please replace the current code with our following code!

1) Installing npm dependencies

For this tutorial, we will require d3 and our parser! In npm this is very easy, just run.

npm install biojs-io-snipspector d3 --save

{% hlblock question %} What does --save mean? Help {% endhlblock %}

{% hlblock info %} If you don't find a npm package for a js lib, you can add it to the "snippets js" section of your package.json.

[...]
"snippets": {
	"js": ["/build/<your-component>.js", "<non npm libs>"],
[...]

{% endhlblock %}

In the previous tutorial we wrote a parser please have a look at the previous tutorial, where we called our like this:

parser.read("http://files.biojs.net/chromosomes/manny", function(result){
  var genome = result;

})

In the following we will build a donutchart to visualize our data.

2) Require dependencies

First we need some dependencies. We require d3 for our visualizations and the parser from the previous tutorial. We can require them with following code:

(lib/index.js)

var d3 = require("d3");
var parser = require("biojs-io-snipspector");

Furthermore we want to wrap our visualization in an exported function:

(add to lib/index.js)

var vis = function(opts){
 // future code to be added here
}
module.exports = vis;

3) Getting started with d3

Now we can get started. To define our chart, we first need the size of it, a set of colors, the arc form and an converter for our data:

(add to lib/index.js)

var width = 960,
    height = 500,
    radius = Math.min(width, height) / 2;

var color = d3.scale.category10();

var arc = d3.svg.arc()
            .outerRadius(radius - 10)
            .innerRadius(radius - 150);

var pie = d3.layout.pie()
            .sort(null)
            .value(function (d) {
                return d.number;
            });

In details:

  • First we need a radius,width and height value for our svg components.
  • color is a function which will translate values into color code.
  • arc draws our svg arc. We we set innerRadius to 0, we would get a piechart.
  • pie is our data transformer. D3 provides us with an converter (or layouts), which will convert an array data representation into a suitable representation for pie charts.

4) Checking for the BioJS snippet

Normally slush should have created an example snippet for you, let's verify whether it is existent. The file name doesn't not matter as long as it is in the examples directory.

examples/simple_example.js

var app = require("biojs-vis-snipspector");
app({el: yourDiv});

So let's use this snippet and show our current code, run:

npm run w

This will run sniper and let you browse our work at http://localhost:9090/examples. Currently the snippet will be empty, but you can add some example code inside our module in lib/index.js to check whether every is working.

var svg = d3.select(opts.el).append("svg")
  .attr("width", 100)
  .attr("height", 100);

svg.append("circle")
  .style("fill", "red")
  .attr("r", 40)

If you see a circle, you can remove the example code and move on.

5) Convert our data

Now it is time to plot some data! In d3, data are arrays. So the format which our biojs-io-snipspector returns is not suitable for our representation. Therefore we need to convert our data into this format for each chromosome (each chromosome will be represented by a pie/donut chart)

(add to lib/index.js)

var chromosome_data = [{category: "del", number: 1}, {category: "hetero": ,number: 2} , {category: "homo" , number: 3}];

Can you come up with an converter? Here is our solution: Add this into your code.

(add to lib/index.js)

function converter(genome){
   var data_res = [];

   for (var k = 0; k < 25; k++) {
               var data = [{
                   number: genome[k].del
       }, {
                   number: genome[k].hetero
       }, {
                   number: genome[k].homo
       }];


               var data_wrapper = [{
                   name: genome[k].name,
                   data: data
       }];

               data_res = data_res.concat(data_wrapper);

   }

   return data_res;
}

Everything should look like this right now:

function converter(genome){...}

parser.read("http://files.biojs.net/chromosomes/manny", function(result){
  var data_res = converter(result);

  //Our visualization code ...

})

All chromosomes are now in an optimal array representation and each chromosome object is now represented by his name and dataset.

6) Creating a donut chart!

Now, after cleaning up our data, let's get finally to the visualization part! First, we will visualize the data in chromosome 'X' in a donut chart!

Let's create a svg which we append on the body of our html!

var X_data = data_res[22].data;

var svg = d3.select("body").append("svg")
            .attr("width", width)
            .attr("height", height)
            .append("g")
            .attr("transform", "translate(" + width / 2 + "," + height / 2 + ")");

var g = svg.selectAll(".arc")
            .data(pie(X_data))
            .enter().append("g")
            .attr("class", "arc");

g.append("path")
    .attr("d", arc)
    .style("fill", function (d) {
            return color(d.data.category);
        });

g.append("text")
    .attr("transform", function (d) {
            return "translate(" + arc.centroid(d) + ")";
        })
    .attr("dy", ".35em")
    .style("text-anchor", "middle")
    .text(function (d) {
            return d.data.category;
        });

D3 handles new data with enter(). To learn more about enter,update and delete, visit the d3 tutorial. Congratulations! You wrote your first visualization component for biojs! Now it is time to export and build it!

To export it write a wrapper around your all your code (except the dependencies)

var parser = require("biojs-io-snipspector");

function d3_show(opts) {
//All of our written code until now (except for the dependencies)
}

module.exports = d3_show;

We recommend browserify. Therefore use our preinstalled npm run build-browser!

npm run build-browser

to create a build for this file!

The final program looks like this:

{% code javascript collapsible=true %} var d3 = require("d3"); var parser = require("biojs-io-snipspector");

function d3_show(opts) {

var width = opts.width || 960, height = opts.height || 500, el = opts.el; radius = Math.min(width, height) / 2;

    var color = d3.scale.category10();

    var arc = d3.svg.arc()
                .outerRadius(radius - 10)
                .innerRadius(radius - 150);

    var pie = d3.layout.pie()
                .sort(null)
                .value(function (d) {
                    return d.number;
                });

function converter(genome){ var data_res = [];

    for (var k = 0; k < 25; k++) {
                var data = [{
                    number: genome[k].del
        }, {
                    number: genome[k].hetero
        }, {
                    number: genome[k].homo
        }];


                var data_wrapper = [{
                    name: genome[k].name,
                    data: data
        }];

                data_res = data_res.concat(data_wrapper);

    }

    return data_res;

}

parser.read("http://files.biojs.net/chromosomes/manny", function(result){ var data_res = converter(result);

var X_data = data_res[22].data;

    var svg = d3.select(el).append("svg")
                .attr("width", width)
                .attr("height", height)
                .append("g")
                .attr("transform", "translate(" + width / 2 + "," + height / 2 + ")");

    var g = svg.selectAll(".arc")
                .data(pie(X_data))
                .enter().append("g")
                .attr("class", "arc");

    g.append("path")
        .attr("d", arc)
        .style("fill", function (d) {
                return color(d.data.category);
            });

    g.append("text")
        .attr("transform", function (d) {
                return "translate(" + arc.centroid(d) + ")";
            })
        .attr("dy", ".35em")
        .style("text-anchor", "middle")
        .text(function (d) {
                return d.data.category;
            });

})

}

module.exports = d3_show; {% endcode %}

For more information about how each code component works, have a look at following resources.

In our final component biojs-vis-snipspector, we also included a function to visualize all chromosomes.

Have a look at the source code to learn more!

<script src="http://d3js.org/d3.v3.min.js"></script> <script src="/series/snipspector-adv/res/snipvis.js"></script> <script>var snipvis = require("biojs-vis-snipspector"); snipvis(document.getElementById("vis"))</script>