Using docker for reproducibility, workflows and more
1 - Controls and weird results from polls
Polls are a resource to understand some fundamental aspects of our society. The question is, are they the right tool for every conceivable question? In this blog post, the author gives several examples showing that for polls with polemic topics, they can be easily drowned with noise. They also show how important control questions in this context to avoid misleading conclusions from weird answers.
2 - Using docker to make your analysis reproducible
Thinking about reproducibility? This blog post shows how to go beyond groundhog and how one can use docker for making science more reproducible.
3 - Reviewed papers have equal merit as published papers
Publication and citations are a common currency in the academic world. The Plan-S initiative, spearheaded by the European Union, deems that papers only reviewed but not necessarely published in a paper are of equivalent merit.
4 - Statistical workflow: a book
A workflow for statistical analysis is very important, usually being a crucial aspect in how good an analysis is. In this book, Frank Harrel Jr showcases how he uses R and his workflows for statistical analysis.
5 - QCing your RNA-seq data in R
MatrixQCvis is a shiny app tool that can be used to acess the quality of bulk RNA-seq data after the standard pipeline before doing any differential expression analysis.
https://academic.oup.com/bioinformatics/article/38/4/1181/64260671