ChemGAPP encompasses three modules, each with a dedicated Streamlit App.

ChemGAPP Big

This package is for the quality control analysis of large chemical genomic screen data. Since many issues can arise during chemical genomic screens, such as pinning mistakes and edge effects, this package aims to improve the quality of the inputted data. It achieves this via the normalisation of plate data and by performing a series of statistical analyses for the removal of detrimental replicates or conditions. Following this, it is able to score data and assign fitness scores (S-scores). The statistical analyses included are: the Z-score test, the Mann-Whitney test, and condition variance analysis.

ChemGAPP Small

ChemGAPP_Small has been produced to deal with small scale chemical genomic screens where replicates are within the plate. This differs from large chemical genomic screen where replicates are across multiple plates. ChemGAPP Small produces three types of plots, a heatmap, bar plots and swarm plots. For the bar plot and heatmap, ChemGAPP Small compares the mean colony size of within plate replicates to the mean colony size of the within plate wildtype replicates, producing a fitness ratio. The bar plots are then optionally grouped by strain or by condition. The heatmap displays all conditions and strains. For the swarm plots each mutant colony size is divided by the mean colony size of the wildtype, to produce the fitness ratio. A one-way ANOVA and Tukey-HSD analysis determines the significance in difference between each mutant fitness ratio distribution and the wildtype fitness ratio distribution. colony size can be substituted for any IRIS phenotype.

ChemGAPP GI

ChemGAPP GI focuses on the analysis of genetic interaction studies. ChemGAPP GI calculates the fitness ratio of two single mutant strains and a double knockout in comparison to the wildtype. It also calculates the expected double knockout fitness ratio for comparison to the observed fitness ratio. ChemGAPP GI displays this data as a bar plot.