ScreenGarden: a shinyR application for fast and easy analysis of plate-based high-throughput screens

Colony growth on solid media is a simple and effective measure for high-throughput genomic experiments such as yeast-two hybrid, Synthetic Genetic Arrays and Synthetic Physical Interaction screens. The development of robotic pinning tools has facilitated the experimental design of these assays, and different imaging software can be used to automatically measure colony sizes on plates. However, comparison to control plates and statistical data analysis is often laborious and pinning issues or plate specific growth effects can lead to the detection of false positive growth defects. We have developed ScreenGarden, a shinyR application, to enable easy, quick and robust data analysis of plate-based high throughput assays.

[1]  R. Fisher.  Statistical methods for research workers , 1927, Protoplasma.

[2]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[3]  Guðjón Ólafsson,et al.  Polo kinase recruitment via the constitutive centromere-associated network at the kinetochore elevates centromeric RNA , 2020, PLoS genetics.

[4]  P. Bork,et al.  Proteome survey reveals modularity of the yeast cell machinery , 2006, Nature.

[5]  Adrian E. Raftery,et al.  Model-Based Clustering, Discriminant Analysis, and Density Estimation , 2002 .

[6]  Guðjón Ólafsson,et al.  Synthetic physical interactions map kinetochore regulators and regions sensitive to constitutive Cdc14 localization , 2015, Proceedings of the National Academy of Sciences.

[7]  Luca Scrucca,et al.  mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models , 2016, R J..

[8]  Hadley Wickham,et al.  Dates and Times Made Easy with lubridate , 2011 .

[9]  Sean R. Collins,et al.  Global landscape of protein complexes in the yeast Saccharomyces cerevisiae , 2006, Nature.

[10]  John C. Dittmar,et al.  ScreenMill: A freely available software suite for growth measurement, analysis and visualization of high-throughput screen data , 2010, BMC Bioinformatics.

[11]  R. Irizarry.  ggplot2 , 2019, Introduction to Data Science.

[12]  Sean R. Collins,et al.  A strategy for extracting and analyzing large-scale quantitative epistatic interaction data , 2006, Genome Biology.

[13]  Anne E Carpenter,et al.  CellProfiler: free, versatile software for automated biological image analysis. , 2007, BioTechniques.

[14]  Cheng Li,et al.  Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.

[15]  Guðjón Ólafsson,et al.  Synthetic Physical Interactions Map Kinetochore-Checkpoint Activation Regions , 2016, G3: Genes, Genomes, Genetics.

[16]  R. Ozawa,et al.  A comprehensive two-hybrid analysis to explore the yeast protein interactome , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Guðjón Ólafsson,et al.  Synthetic protein interactions reveal a functional map of the cell , 2016, eLife.

[18]  Kohske Takahashi,et al.  Welcome to the Tidyverse , 2019, J. Open Source Softw..

[19]  Eric J. Deeds,et al.  Quantifying fitness distributions and phenotypic relationships in recombinant yeast populations , 2007, Proceedings of the National Academy of Sciences.

[20]  Hadley Wickham,et al.  ggplot2 - Elegant Graphics for Data Analysis (2nd Edition) , 2017 .

[21]  Y. Arzhaeva,et al.  Spotsizer: High-throughput quantitative analysis of microbial growth. , 2016, BioTechniques.

[22]  L. Parts,et al.  gitter: A Robust and Accurate Method for Quantification of Colony Sizes From Plate Images , 2014, G3: Genes, Genomes, Genetics.

[23]  Lingling An,et al.  Normalization Methods on Single-Cell RNA-seq Data: An Empirical Survey , 2020, Frontiers in Genetics.

[24]  A. Csikász-Nagy,et al.  Synthetic Physical Interactions with the Yeast Centrosome , 2019, G3: Genes, Genomes, Genetics.

[25]  Gary D Bader,et al.  Quantitative analysis of fitness and genetic interactions in yeast on a genome scale , 2010, Nature Methods.

[26]  H. Bussey,et al.  Exploring genetic interactions and networks with yeast , 2007, Nature Reviews Genetics.

[27]  D. Yorke,et al.  An Empirical Survey , 1995 .