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Job Name
Enter a unique name for your network inference job. For example, 'genie3_network_test1'. This will help organize and track your analysis results.
Upload H5ad File
Upload a .h5ad file containing your gene expression data (single-cell or bulk RNA-seq). Ensure the file is properly formatted in AnnData standard.
Drag & Drop or Click to Browse (Supported: .h5ad)
Select Input TF_list
Choose how you would like to provide your TF_list data.
TF_list
CSV File (.csv)
TF List (Manual Input)
Enter a comma-separated list of transcription factors (TFs) manually. This helps specify candidate regulators in the GRN inference.
Data Normalized
Specify whether the uploaded gene expression matrix has already been normalized. Normalized data typically improves model reliability.
-- Select Normalization Status --
TRUE
FALSE
Tree-Based Regression Method
Choose the regression model for GRN inference. RandomForestRegressor is recommended for balanced speed and accuracy.
Select Tree Method
RandomForestRegressor
ExtraTreesRegressor
GradientBoostingRegressor
Number of Highly Variable Genes (HVG)
Optionally specify how many highly variable genes to select before network inference. For example, 2000–3000 genes for scRNA-seq datasets.
Maximum Number of Links
Set the maximum number of predicted regulatory links to output. Higher values yield larger networks but may include more noise.
Run Analysis
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