Tag Archives: R

10月 20

[荐]Quickly create online and interactive plots using Plot.ly

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As readers likely know putting your data online as interactive visualizations can be a lot of work. We like to use D3, Highcharts and the Google visualization API but all of these tools require some serious programming. When you’re building a website with custom data visualization the effort might make sense, but when you have data you want to share quickly and elegantly a new data visualiation tool, Plot.ly, is a nice option. You can create graphics by uploading data and manually setting plot options or you can create and upload directly from Python, R or other environments.……【阅读全文】

10月 20

[荐]Beautiful plotting in R: A ggplot2 cheatsheet

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Even the most experienced R users need help creating elegant graphics. The ggplot2 library is a phenomenal tool for creating graphics in R but even after many years of near-daily use we still need to refer to our Cheat Sheet. Up until now, we’ve kept these key tidbits on a local PDF. But for our own benefit (and hopefully yours) we decided to post the most useful bits of code.……【阅读全文】

2月 26

[荐]box plots与BoxPlotR

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box plots

BoxPlotR

This application allows users to generate customized box plots in a number of variants based on their data. A data matrix can be uploaded as a file or pasted into the application. Basic box plots are generated based on the data and can be modified to include additional information. Additional features become available when checking that option. Information about sample sizes can be represented by the width of each box where the widths are proportional to the square roots of the number of observations n. Notches can be added to the boxes. These are defined as +/-1.58*IQR/sqrt(n) which gives roughly 95% confidence that two medians are different. It is also possible to define the whiskers based on the ideas of Spear and Tukey. Additional options of data visualization (violin and bean plots) reveal more information about the underlying data distribution. Plots can be labeled, customized (colors, dimensions, orientation) and exported as eps, pdf and svg files.……【阅读全文】

12月 07

[荐]Intermediate R/Bioconductor for High-Throughput Sequence Analysis

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Intermediate R/Bioconductor for High-Throughput Sequence Analysis introduces users with some R experience to common Bioconductor work flows for sequence analysis. The course involves a combination of presentations and hands-on exercises. Our starting point is BAM files created by aligning short reads to a reference genome. Topics include exploratory analysis (GenomicRanges, Rsamtools); assessing differential expression of known genes (DESeq); detection, calling, and manipulation of variants (VariantTools, VariantAnnotation). We learn how to integrate results with curated gene and genomic annotations (GenomicFeatures), and to visualize results (GViz, ggbio).……【阅读全文】