Categories

• RNA-seq 2
• microarray 1
• DESeq2 1
• teaching 1
• maps 3
• gpx 1
• genome 6
• text_analysis 6
• machine_learning 14
• blogging 3
• animation 1
• r_vs_python 1
• shiny 3
• ggplot2 2
• networks 1
• r_users_group 1
• forecasting 3
• tutorials 1
• blogdown 1
• conferences 1
• data2day 1
• flexdashboard 1

RNA-seq

• DESeq2 Course Work
• exprAnalysis package

microarray

• exprAnalysis package

DESeq2

• DESeq2 Course Work

teaching

• DESeq2 Course Work

maps

• Data on tour: Plotting 3D maps and location tracks
• How to map your Google location history with R
• USA/ Canada Roadtrip 2016

gpx

• USA/ Canada Roadtrip 2016

genome

• Gene homology Part 3 - Visualizing Gene Ontology of Conserved Genes
• How to build a Shiny app for disease- & trait-associated locations of the human genome
• Gene homology Part 2 - creating directed networks with igraph
• Creating a network of human gene homology with R and D3
• Exploring the human genome (Part 2) - Transcripts
• Exploring the human genome (Part 1) - Gene Annotations

text_analysis

• Social Network Analysis and Topic Modeling of codecentric’s Twitter friends and followers
• How to do Optical Character Recognition (OCR) of non-English documents in R using Tesseract?
• Characterizing Twitter followers with tidytext
• Analysing the Gilmore Girls' coffee addiction with R
• Creating a Gilmore Girls character network with R
• Is 'Yeah' Josh and Chuck's favorite word?

machine_learning

• Data Science for Fraud Detection
• Update to autoencoders and anomaly detection with machine learning in fraud analytics
• Autoencoders and anomaly detection with machine learning in fraud analytics
• Does money buy happiness after all? Machine Learning with One Rule
• Explaining complex machine learning models with LIME
• Dealing with unbalanced data in machine learning
• Building meaningful machine learning models for disease prediction
• Plotting trees from Random Forest models with ggraph
• Hyper-parameter Tuning with Grid Search for Deep Learning
• Building deep neural nets with h2o and rsparkling that predict arrhythmia of the heart
• Predicting food preferences with sparklyr (machine learning)
• Feature Selection in Machine Learning (Breast Cancer Datasets)
• Extreme Gradient Boosting and Preprocessing in Machine Learning - Addendum to predicting flu outcome with R
• Can we predict flu deaths with Machine Learning and R?

blogging

• From Biology to Industry. A Blogger’s Journey to Data Science.
• Why I use R for Data Science - An Ode to R
• How to set up your own R blog with Github pages and Jekyll Bootstrap

animation

• Animating Plots of Beer Ingredients and Sin Taxes over Time

r_vs_python

• R vs Python - a One-on-One Comparison

shiny

• Scratching the Surface of Gender Biases
• New features in World Gender Statistics app
• Exploring World Gender Statistics with Shiny

ggplot2

• Happy EasteR: Plotting hare populations in Germany
• Conditional ggplot2 geoms in functions (QTL plots)

networks

• Network analysis of Game of Thrones family ties

r_users_group

• New R Users group in Münster!

forecasting

• Data Science for Business - Time Series Forecasting Part 3: Forecasting with Facebook's Prophet
• Data Science for Business - Time Series Forecasting Part 2: Forecasting with timekit
• Data Science for Business - Time Series Forecasting Part 1: EDA & Data Preparation

tutorials

• Migrating from GitHub to GitLab with RStudio (Tutorial)

blogdown

• Moving my blog to blogdown

conferences

• Blockchain & distributed ML - my report from the data2day conference

data2day

• Blockchain & distributed ML - my report from the data2day conference

flexdashboard

• Explore Predictive Maintenance with flexdashboard