insane: INsulin Secretion ANalysEr

Mickaël Canouil, Ph.D.

October 27, 2020

1 Installation

# Install insane from CRAN:
install.packages("insane")

# Or the the development version from GitHub:
# install.packages("remotes")
remotes::install_github("mcanouil/insane")
library("insane")
go_insane()

2 Overview

The Shiny (R package) application insane (INsulin Secretion ANalysEr) provides a web interactive tool to import experiments of insulin secretion using cell lines such as EndoC-βH1.

2.1 Excel Template

An Excel template is provided within the app to help users import their experiments in an easy way.

2.2 The App

insane provides a user-friendly interface which can handle several projects separately.

2.2.1 Technical Quality-Control

insane performs technical quality-control of the optical density measured in each steps of the experiments:

  • blank (BLANK),
  • lysat (LYSATE),
  • supernatant (SUPERNATANT1 and SUPERNATANT2).

This technical quality-control step checks:

  • the variability among the duplicated optical density measures of each samples;
  • the variability in the blank curves (intercept and slope estimates) among all experiments in a project.

2.2.2 Statistical analyses

insane performs statistical analyses of the experimental conditions, e.g., one silenced gene (siGENE) compared to an insulin secretion reference (siNTP) in two stimulation conditions (Glc and Glc + A).

Conditions are compared using a linear regression with Date and Operator as covariates (if needed) to control for heterogeneity.

  • Using all experiments in the selected project

    • Boxplot version

    • Histogram version

  • Using some of the experiments in the selected project

If and when some experiments are failing any of the technical quality-controls, a summary of the issues regarding the selected experiments can be displayed using the button Show Issues in the Selected Experiments.

2.2.3 List of Outliers (Issues Detected)

A comprehensive list of all issues detected in the selected project is available in an Outliers tab.

Note: The Outliers tab is displayed only if there is at least one issue in the selected project.