Tim Blokker's repositories
PhyCovA
This repository contains 3 branches, the master branch can be used to build the application from source. The dockerhub branch leads to a docker image that can be pulled from timblokker/phycova_treetime from dockerhub. The heroku branch is also leading to a docker image on dockerhub but does not include the treetime software and is not suited to be run locally but is instead collected from dockerhub by heroku automatically. The application cen be accessed via the application referenced under environments.
Reactive_Variable_Selection
Image: https://hub.docker.com/repository/docker/timblokker/variable.selection - Container: https://lychee-tart-58391.herokuapp.com/
Metabolic_modeling
In this repository the metabolic model of F. prausnitzii generated by Heinken, et al 2014 (“Functional metabolic map of Faecalibacterium prausnitzii, a beneficial human gut microbe.”, https://doi.org/10.1128/JB.01780-14) was validated with in-vitro growth data. 3 python jupyter notebooks, one for each medium, and a R jupyter notebook contain the main analysis of this project.
ATAC_Sequencing
The data analyzed in this assignment was accompanied by the following paper: Chopp et al., An Integrated Epigenomic and Transcriptomic Map of Mouse and HumanabT Cell Development,Immunity (2020), https://doi.org/10.1016/j.immuni.2020.10.024. (1) ATACseq fastq files were trimmed with Trimmomatic, (2) Aligned to mouse genome (mm10) using Bowtie2 (v2.3.4,X set to 2000), (3) Low quality (MAPQ < 30) and mitochondrial reads were removed with Samtools (v1.6), (4) Peaks were called using Macs2 (v2.2.4, pvalue 1e-7 and–keep-dup all) and (5) Homer (4.10) for peak annotation and motif enrichment analyses.
RNA_Sequencing
In total there are 3 jupyter notebooks together with 3 html files for ease of access in this repository. (1) Master notebook & FastQC and Mapping of reads using star and subsequent feature count (this notebook), (2) the DESeq2 analysis in R for the statistical analysis, (3) Functional analysis using arbitrary (GProfiler, iRegulon) and "leading edge" (Gorilla, GSEA) cut-offs. The dataset was taken from here: https://www.ncbi.nlm.nih.gov/sra/SRX8335650 and is accompanying the publication by Carmona-Rivera et al. 2020 https://insight.jci.org/articles/view/139388.
Applied_Multivariate_Statistical_analysis
This small project showcases some explorative, multivariate data analysis techniques (Andrews plot, Bi-Plot, clustering) in R. These techniques were applied on a data set for erasmus mobility combined with measures of cultural differences.
Growth
The data originates from a study reported by Potthoff and Roy in Biometrika (1964) (Potthoff, 1964). In the study the distance from the center of the pituitary to the maxillary fissure was recorded at ages 8, 10, 12, and 14, for 11 girls and 16 boys. The main question we want to answer in this report is: Is dental growth related to gender?
CastleGame
This repository contains a small java game developed for a course in the master of Bioinformatics at the KU Leuven. The aim of this game is to find the 3 keys necessary to enter a castle. Once all keys are found the castle can be "captured" and the game is won. On the quest the hero can collect potions and has to fight enemies.