Check where a gene is expressed from the command line

The Pachter Lab have developed some very useful bioinformatics software. In this post, I use gget to quickly query ARCHS4 on the command line to see where a gene of interest is expressed. The gget tool has other functionality too including sequence alignment, enrichment analysis, and even protein structure prediction using AlphaFold. Check it out!…

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Interactive plots in R

Interactive plots, as the name suggests, are plots that users can interact with. In my last post, I mentioned that for interactive heatmaps I use the d3heatmap package. To get started with this post, I’ll create the same heatmap as my last post but this time using the d3heatmap package.

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Gantt chart using R

A post on creating a Gantt chart using R; these are good for showing a project timeline in grant applications. The code is adapted from an answer on Stack Overflow. You will need the ggplot2 and reshape2 packages; install them if you haven’t already.

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Interactive plots in R using plotly

I found out about plotly a couple of months ago via R-bloggers: Gantt charts in R using Plotly via @Rbloggers #rstats https://t.co/LuW8nuQr6c — Dave Tang (@davetang31) May 13, 2016 I finally gave it a go when a friend asked me for help making a Gantt chart and I was impressed with plotly’s interactivity and ease…

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Miscellaneous plots in R

The R Graphics Cookbook is an awesome book; it’s so awesome that I bought the ebook after I bought the hardcopy because one copy of it wasn’t enough. I haven’t read the book in its entirety yet, but I thought I’ll share with you some of the recipes in Chapter 13, which illustrates how to…

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Animated plots using R

I learned the simple concept of animation back in school, when some of my classmates would draw stick figures on the edge of large textbooks. At first I was wondering why one would defile a textbook in such a way, but then as they flipped through the pages and brought the stick figures to life,…

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ENCODE RNA polymerase II ChIP-seq

Updated 2018 November 8th: include section on MACS2 Chromatin immunoprecipitation sequencing (ChIP-seq) is a high throughput method for investigating protein-DNA interactions and aims to determine whether specific proteins are interacting with specific genomic loci. The workflow consists of crosslinking DNA and protein together, usually via the use of formaldehyde, which induces protein-DNA and protein-protein crosslinks….

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Using Gviz

Updated: 2013 November 15th A while ago I asked on Twitter, what are some tools that people use to visualise hundreds of bam files. One of the suggestions was Gviz (thanks Sebastian!) and I had a quick glimpse at the Bioconductor package and the plots looked really great! Here I use Gviz to plot features…

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Creating a coverage plot in R

Disclaimer (2015 August 5th): as pointed out in this comment thread below, this post created a density plot rather than a coverage plot. I have written a new post that uses BEDTools to calculate the coverage and R to produce an actual coverage plot. I’ve recently discovered GitHub Gist, so for this post I’m going…

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Using the ENCODE ChIA-PET dataset

Updated: 2014 March 14th From the Wikipedia article: Chromatin Interaction Analysis by Paired-End Tag Sequencing (ChIA-PET) is a technique that incorporates chromatin immunoprecipitation (ChIP)-based enrichment, chromatin proximity ligation, Paired-End Tags, and High-throughput sequencing to determine de novo long-range chromatin interactions genome-wide. Let’s get started on using the ENCODE ChIA-PET dataset by downloading the bed files,…

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