Previous article In the previous article we have discussed how to analyze RNA NGS data using the commonly used technique of negative binomial GLM. In the following article, we will proceed into differential gene expression analysis by utilizing alternative approaches, such as the edgeR classic method that is based on negative binomial exact test analysis, as well as the Wilcoxon ranked sum test for read counts. Furthermore, we will compare the outcomes of these methods to those of the quasi-likelihood GLM model.

Previous article In the first article, we obtained NGS data and made the necessary preparations for further analysis. This involved processing and organizing the data in a way that would facilitate downstream analysis. Additionally, we included annotations that provide valuable context and information for the interpretation of the results. Introduction There are many ways to perform analysis of differential gene expression (DGE) in R. I’m going to look at a few of them.

Preface Here I am going to write a series of posts dedicated to high throughput RNA sequencing data analysis. As an essential technology, RNA sequencing is applied to many fields of biology and life science. Knowing how to process RNA seq data is important for researchers in these fields. This series of articles will explain the steps involved in the process. In our first article, we will obtain real-world Next Generation Sequencing (NGS) data, learn about the data format required for further analysis, and annotate the data accordingly.

Purpose Websites are great instrument for sharing knowledge. Having your own site has a lot of advantages over social networks. Here are some of them: You have full control over your data You choose how your site will look like There is no chance being banned on your own site This days modern technology allows us to build new full featured site in minutes. In this article I will try to give a step by step guide how to do so.

Understand how does new pipe work Include libraries: 1 2 library(magrittr) library(dplyr) 1 2 ## ## Attaching package: 'dplyr' 1 2 3 ## The following objects are masked from 'package:stats': ## ## filter, lag 1 2 3 ## The following objects are masked from 'package:base': ## ## intersect, setdiff, setequal, union New pipe |> forces to call function directly while magittr pipe %>% does not need () 1 2 3 abc <-3 abc |> sqrt() 1 ## [1] 1.

Short guid for keeping yur Arch fresh If you didn’t update your system for long time you might encounter problems with installation of new packages. Here is my guide of how to resolve those issues. Update Mirror List Install python reflector script 1 # sudo pacman -S reflector Update Arch mirrors at /etc/pacman.d/mirrorlist 1 # sudo reflector --latest 40 --protocol https --country 'Sweden, Netherlands, Finland, France, Germany, "United States", "United Kingdom", Japan, Singapore' --sort rate --save /etc/pacman.