Expression Anova Tools¶
Configuration File: expression_anova_tools.json
Tool Type: Local
Tools Count: 1
This page contains all tools defined in the expression_anova_tools.json configuration file.
Available Tools¶
expression_anova_per_gene (Type: ExpressionANOVAPerGeneTool)¶
Per-gene ANOVA or log2 fold-change on a gene x sample expression matrix. Each gene contributes on…
expression_anova_per_gene tool specification
Tool Information:
Name:
expression_anova_per_geneType:
ExpressionANOVAPerGeneToolDescription: Per-gene ANOVA or log2 fold-change on a gene x sample expression matrix. Each gene contributes one value per group (its mean expression across group samples), then mode=’anova’ runs one-way ANOVA (f_oneway) across K groups of N gene-level means; mode=’fold_change’ computes per-gene log2((mean_a+1)/(mean_b+1)) between two groups and returns median/mean across genes. Use for gene-level comparisons across experimental conditions where each gene is treated as one observation (e.g. comparing strains, cell types, or treatments). Accepts CSV counts matrix (rows=genes, cols=samples) and CSV metadata (rows=samples with group_col). Auto-aligns by overlapping sample IDs (transposes counts if needed).
Parameters:
counts_file(string) (required) Path to CSV count matrix (genes x samples, first column = gene IDs).meta_file(string) (required) Path to CSV metadata (rows=samples, contains group_col).group_col(string) (required) Metadata column identifying groups (e.g. ‘Strain’, ‘cell_type’).mode(string) (required) ‘anova’: one-way ANOVA across groups. ‘fold_change’: median per-gene log2FC between group_a and group_b.exclude_groups([‘array’, ‘null’]) (optional) Groups in group_col to exclude before analysis.group_a([‘string’, ‘null’]) (optional) Numerator group for fold_change mode.group_b([‘string’, ‘null’]) (optional) Denominator group for fold_change mode.
Example Usage:
query = {
"name": "expression_anova_per_gene",
"arguments": {
"counts_file": "example_value",
"meta_file": "example_value",
"group_col": "example_value",
"mode": "example_value"
}
}
result = tu.run(query)