A common task when working with transcriptomic data is the identification of differentially expressed (DE) genes or tags between groups. In this tutorial participants will learn how to perform biostatistical analysis with edgeR, including pairwise and analysis of variance (ANOVA) like comparisons to identify significantly DE genes. Continue reading Downstream Bioinformatics Analysis of Omics Data with edgeR
In this tutorial participants will learn about biological data analysis with R and Unix/Linux tools. We begin with an introduction to bioinformatics and omics data analysis, and conclude with the walkthrough of a simple bioinformatics workflow for aligning transcriptomic sequences with genomic data. Continue reading Bioinformatics Analysis of Omics Data with the Shell & R
Adding color to your plots is a great way to make them more visually appealing and informative. Not to mention the fun you can have playing with color palettes that have been made for ggplot2, like the Wes Anderson palette in the wesanderson R package by karthik. Continue reading Colorful R Plots with Wes Anderson Palettes – Pirate Ships
This walkthrough of the fundamentals of shell programming with Z shell (Zsh) and Bourne Again SHell (BASH) includes a comparison of similar components and features in R and RStudio. An alternate perspective from R is provided for you to leverage while learning the fundamentals of shell programming. Continue reading Shell vs R Fundamentals – From Syntax to Control Structures with Zsh & BASH
Generalized linear models (GLM) are a classic method for analyzing RNA-seq expression data. In contrast to exact tests, GLMs allow for more general comparisons. Continue reading Generalized Linear Models and Plots with edgeR – Advanced Differential Expression Analysis
Exact tests often are a good place to start with differential expression analysis of genomic data sets. As usual, the types of contrasts you can make will depend on the design of your study and data set. In the following example we will learn how to use the raw counts of differentially expressed (DE) genes to compare the following Daphnia genotypes. Continue reading Exact Tests and Plots with edgeR – Basic Differential Expression Analysis
Venn diagrams are a great way to visualize informative comparisons between data sets. It can be particularly helpful to use venn diagrams to look at how similar data is across multiple data sets, or within the same data set. Continue reading Comparing Data Sets with Venn Diagrams
Reciprocal best hits BLAST (RBHB) is a common method used for a rough assessment of orthology when working with genomic data from multiple species. There are many other methods for identifying orthologs that differ in the number of identified orthologs, quality, and run time. Continue reading Reciprocal Best Hits BLAST – RBHB
One of the best ways to compare the characteristics of any data set is to create descriptive plots. The following R scripts have been improved to generate plots of sequence, line, and size statistics for a set of input fasta files. Continue reading Uniquely Merge Fasta Files – Tidy Plots
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