Additional file 1 of Assignment of unimodal probability distribution models for quantitative morphological phenotyping

Additional file 1: Supplementary text. Supplementary Figure S1. Possible values of cellular features used in QMP. Supplementary Figure S2. Probability models for CalMorph measures. Supplementary Figure S3. Conversion of the CV to noise values. Supplementary Figure S4. Flowchart of the methodology for checking the modality of the CalMorph parameters. Supplementary Figure S5. An example of the effect of confounding factors on modality. Supplementary Figure S6. An example of the effect of outliers on modality. Supplementary Figure S7. Comparison of this study with our previous results. Supplementary Figure S8. Comparison of results between UNIMO and Box-Cox transformed methods. Supplementary Figure S9. Canonical correlation analysis used for extraction of 32 pairs of canonical variables. Supplementary Figure S10. Phenotypic similarity network of non-essential genes. Supplementary Figure S11. Enrichment of KEGG categories. Supplementary Figure S12. Morphological defects of autophagy mutants. Supplementary Figure S13. Multimodal CalMorph parameters. Supplementary Figure S14. Outlines of generalization of UNIMO. Supplementary Figure S15. An example of versatility of UNIMO. Supplementary Figure S16. Defining characteristics of the 130 functional groups. Supplementary Table S1. Selection of the probability distribution for each morphological parameter; non-negative (A), ratio (B), noise (C), and proportion (D) measures. Supplementary Table S2. Population level modality check for each morphological parameter; non-negative (A), ratio (B), noise (C), and proportion (D) measures. Supplementary Table S3. The best probability distribution and final modality for each morphological parameter; non-negative (A), ratio (B), noise (C), and proportion (D) measures. Supplementary Table S4. List of non-essential mutants. Supplementary Table S5. List of the representative GO terms enriched in each functional group. Supplementary Table S6. KEGG pathway enrichment (FDR = 0.05). Supplementary Table S7. Data types and probability distributions employed for a typical quantitative morphological phenotyping (QMP) experiment. Supplementary Table S8. List of measurements extracted by CellProfiler. Supplementary Table S9. An example of generalization and versatility of UNIMO using morphological data presented in Mattiazzi Usaj et al. (2020).