Publication dateSep 19, 2024
Confidentiality public Public
Cell Culture Medium PCA
TASK
Typing name : TASK.gws_plate_reader.CellCultureMediumPCA Brick : gws_plate_reader Performs PCA analysis on cell culture medium composition data
[Generated by Task Expert Agent]
Performs Principal Component Analysis (PCA) on cell culture medium composition data.
This task takes a Table containing medium composition data and performs dimensionality
reduction using PCA. It generates:
- A table of PCA scores for all samples
- A scatter plot showing PC1 vs PC2 projection
- A biplot combining scores and variable loadings
Input
- medium_table: Table with medium composition data. Must contain a 'Medium' column
identifying different medium, and numeric columns for compositional features.
Configuration
- medium_column: Name of the column containing medium identifiers (default: 'Medium')
Outputs
- scores_table: Table containing PCA scores (principal components) for each sample
- scatter_plot: Plotly scatter plot of PC1 vs PC2 with color-coded medium groups
- biplot: Plotly biplot combining sample scores and variable loadings
Notes
- Use CellCultureMediumTableFilter task before PCA to select specific medium
- Data is standardized (mean=0, std=1) before PCA
- The number of components is determined automatically based on data dimensions
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Input
Medium Table
Table containing medium composition data with Medium column
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Output
PCA Scores Table
Table containing principal component scores for each sample
PCA Scatter Plot
Scatter plot showing PC1 vs PC2 projection colored by medium
PCA Biplot
Biplot combining sample scores and variable loadings
settings
Configuration
Name of the column containing medium identifiers
Type : stringDefault value : Medium columns_to_exclude
Optional
List of column names to exclude from PCA analysis (in addition to medium column)
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