fresh block

fresh block

This example demonstrates a histogram visualization of DNA sequence data parsed from a FASTA file. The block uses D3 v4 with an SVG rendering, reading sequence headers from `test.fasta` via a custom underscore-delimited format, extracting node lengths, and then plotting the distribution of 1000 random samples using d3.histogram with 20 bins. The bars are styled in steelblue with white count labels, and the x-axis is rendered at the bottom. The visualization is built with Blockbuilder.org and licensed under MIT.

91% match

fresh block

A fresh block is a visualization of genomic contig sequences using a force-directed graph. The application parses a FASTA file containing DNA contig metadata (node ID, length, coverage) and renders each contig as a colored block in an SVG layout. Blocks are positioned and sized based on sequence attributes, with colors encoding coverage values, using d3.v4's force simulation to arrange the nodes. The resulting graphic provides a compact overview of contig length and coverage distributions from the assembled genome data.

81% match

histo

This histogram visualizes the distribution of sequence lengths from a FASTA file of genome contigs, parsed from the node IDs in `contigs.fasta`. Using D3 v4 with SVG rendering, the visualization computes the lengths of each sequence and groups them into bins along the x-axis, with bar heights representing the count of contigs per length range. The chart provides a quick view of the size distribution of genomic fragments, highlighting the central tendency and spread of contig lengths in the dataset.

77% match

histo

This histogram visualizes the distribution of coverage values parsed from sequence headers in a FASTA file, rendering as SVG using d3.v4. The data is derived from contig metadata (node_id, length, size, coverage) embedded in the FASTA descriptions, with the histogram showing the frequency of coverage values across all contigs. Built with Blockbuilder and forked from TylerVaughan's original block, it uses d3's histogram layout to bin and display the distribution.

77% match

fresh block

A set of vertical bars displays a small numeric array, with bar heights proportional to values and fill colors interpolating from red to green based on each value’s position in the data range. The visualization uses d3.scaleLinear for the y-axis and color mapping, d3.scaleBand for horizontal positioning, and d3.schemeCategory20 as a fallback palette. Each rectangle is appended to an SVG canvas, with blue strokes outlining the bars. The code computes bar positions and heights directly from the scales, rendering the chart entirely with D3 v4.

TTollyCoburn

fresh block

A set of vertical bars represents five data values, with one bar highlighted in red and the rest in blue, showing a clear visual contrast for the largest value. The chart uses D3 v4 to bind an array of numbers to SVG rectangles, scaling bar heights linearly from a maximum domain of 2500 down to zero. The code applies the scale to position each rectangle’s top and height, while a fixed bar width and white stroke separate the bars for readability.

44xDMG

fresh block

A horizontal bar chart displays numerical values from a TSV file, with each bar labeled by its value. The chart uses D3.js version 3.5.5 to load the data, scale the bar widths linearly, and append SVG rectangles and text elements. The bars are rendered in an SVG container sized dynamically based on the data length, with heights fixed at 20 pixels minus a 1-pixel gap. Data values are coerced to numbers for scaling.

NNastasi7

fresh block

This visualization displays a set of genomic intervals as green rectangles along a linear x-axis, with each rectangle’s width corresponding to the difference between its start and stop coordinates from a small JSON data file. The rectangles are all positioned at the same y-coordinate and height, indicating that only horizontal position and length carry meaning. The code loads data via `d3.json`, appends a 960×500 SVG canvas, and uses `d3.select("svg").selectAll("rect")` to bind the dataset to rectangle elements, setting their x, width, and fill properties based on the data fields.

LLisaPicado