MetPhenoR

The complete workflow including examples can be found in vignettes/MetPhenoR.html. A flowchart of the package can be found in man/figures/MetPhenoR_workflow_flowchart.png

Installation

MetPhenoR is available on CRAN:

install.packages("MetPhenoR")

Installation from GitHub

Install the latest version directly from GitHub remotes package:

# Install remotes if you haven't already
if (!require("remotes", quietly = TRUE)) {
  install.packages("remotes")
}

# Install MetPhenoR from GitHub
remotes::install_github(KatjaDanielzik/MetPhenoR)

Data Preparation

Before analyzing your data:

  1. Create a new folder (e.g., Analysis).
  2. Copy all your RawRead.csv and PlateInfo.csv files into this folder.
  3. In PlateInfo.csv, create or select one column (e.g., Sample) to store experimental metadata.
  4. Format entries like:
    cell.line_variable1_variable_2
    H460_treatment_2h
    → Use underscores, no spaces, and consistent capitalization (R is case-sensitive!).

Never use spaces — this causes errors in read_folder().

Key Features

Feature Function
Noise correction: OD(590nm) - OD(740nm) Removes background noise (valid for adherent cells only).
qc_data() plot Spot missing files, inconsistent conditions, or technical issues early.
classify_growth_curve_types() Identify flat, dropping, or noisy curves.
AUC + normalization Compare across plates and conditions.
Built-in annotations KEGG pathways (PM-M01/M02), drug info (PM-M11–M14).
Heatmaps & violin plots Visualize biological trends.

Important Limitations

Troubleshooting

Issue Solution
No data in qc_data() Check for spaces and variable names Sample column; ensure all files are in the folder.
Filtering didn’t work Double-check plate_type and filters spelling.
Plot is blank Check if processed_data contains data after filtering.

Contact

Have questions, feedback, or want to contribute?
Open an Issue