Genomics

For my M.Sc project, I developed a scoring function to evaluate the performance of four widely used RNA-Seq differential expression packages (DESeq2, edgeR, limma+voom, and BaySeq). The aim was to compare and assess the results of each package and determine the optimal approach for detecting differentially expressed genes (DEGs). By developing this function, we aimed to provide researchers with a tool to maximize or restrict the number of detected DEGs based on their criteria.

ChIP-Seq data was analyzed to characterize the novel SNF2 ATPase in Trypanosoma brucei. Differential H2A.Z deposition was detected after RNAi depletion (against no depletion control) and visualized with genome tracks.

RNA-Seq data was analyzed to characterize two novel telomere binding proteins (TEBP-1 and TEBP-2). Differential gene expression was investigated on KO worms (against a control strain).

The previously developed jury vote RNA-Seq differential expression assessment scoring function is now expanded to 4 genotypes, under water streess conditions (leaf and root tissues)

A jury vote style scoring function to assess differential gene expression in RNA-Seq data is applied to root and leaf Lolium perenne tissues under different water stress conditions.

This is the talk I gave as part of the Mainz International PhD Program (IPP) interview process