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JGuan-lab / SFINN

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SFINN: inferring gene regulatory network from single-cell and spatial transcriptomic data with shared factor neighborhood and integrated neural network

1. Introduction

SFINN is a gene regulatory network construction algorithm based on shared factor neighborhood and integrated neural network. It is applicable to both single-cell and spatial transcriptomic gene expression data for inferring potential interactions and regulations between genes.

For single-cell data, SFINN uses a cell neighborhood graph generated from shared factor neighborhood strategy and gene pair expression data as input for the integrated neural network. In the case of spatial transcriptomic data, the cell neighborhood graph is generated by fusing spatial position information with the network graph generated from gene expression data based on the shared factor neighborhood strategy. The two view inputs are processed through neural network operations, successfully transforming the inference of potential interactions and regulations between gene pairs into a binary classification problem.

The datasets analyzed in the paper are available at: https://zenodo.org/records/10558871

SFINN corresponds to the following paper:

Yongjie Wang, Fengfan Zhou, Jinting Guan, SFINN: inferring gene regulatory network from single-cell and spatial transcriptomic data with shared factor neighborhood and integrated neural network, Bioinformatics, 40(7): btae433. https://doi.org/10.1093/bioinformatics/btae433

2. Dependencies

Python == 3.6.2 
Pytorch == 2.6.2
tensorflow == 2.6.2
tensorflow-gpu == 2.6.0
scikit-learn == 0.24.2
spektral == 1.2.0
pandas == 1.1.5
numpy == 1.19.5

3. TASK 1, Evaluate SFINN on single-cell datasets

3.1 Prepare data

# If you have a ground truth data list with pairs like (gene a, x1) labeled as 0, please use the following code for processing to generate a file that divides the candidate gene pairs into interval indices:

python GenerateSplitIndexFile.py --GroundTrueFilePath /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/NeedDataFile/bonemarrow_TF_target_gene_pairs.txt --SplitIndexSavePath /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/NeedDataFile/bonemarrow_TF_target_gene_pairs_d2  

# If you want to divide the dataset into a training set and a test set, please use:

python Dataset_Split.py --TFlength 13 --TrainDataSaveDir /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/train_data --TestDataSaveDir /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/test_data --UnionGenePairExpDataSavePath /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/UnionGenePariExpData

# Generate joint representation data for gene pairs, please use:

python GetUnionGenePairExpData.py  --UnionGenePairExpDataSavePath  /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/UnionGenePariExpData --ExpDataSavePath /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/NeedDataFile/bonemarrow_cell.h5 --GeneNameFilesSave_Dir  --SplitIndexFilesSave_Dir /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/NeedDataFile/bonemarrow_TF_target_gene_pairs_d2  --GroundTrueSave_Dir /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/NeedDataFile/bonemarrow_TF_target_gene_pairs.txt  --IsBoneOrDend True

# Retrieve the cell-cell adjacency matrix generated based on the shared factor neighborhood strategy:

python GetSSAdjmatrix.py --TFlength 13  --ExpDataSavePath /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/NeedDataFile/bonemarrow_cell.h5 --GeneNameFilesSave_Dir /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/NeedDataFile/sc_gene_list.txt --AdjDataSave_Dir /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/AdjData --UnionGenePairExpDataSavePath /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/UnionGenePariExpData  --IsBoneOrDend  True --ExpDataFileisH5orCsv  h5

3.2 Command to run SFINN

Parameters:
TFlength: Number of transcription factors
AdjDataSave_Dir: Path for cell-cell adjacency matrices
ModelResSavePath: Model storage path
UnionGenePairExpDataSavePath: Path for gene pair representation
TrainDataLoadDir: Storage path for training dataset
TestDataLoadDir: Storage path for test dataset

python SFINN.py --TFlength 13 --AdjDataSave_Dir /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/AdjData --ModelResSavePath /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/ModelRes [--Epochs] 200   [--Lr] 1e-6 [--L2_Reg] 5e-4 [--Es_Patience] 100 [--Batch_Size] 512 --UnionGenePairExpDataSavePath /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/UnionGenePariExpData  --TrainDataLoadDir  /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/train_data --TestDataLoadDir  /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/test_data

3.3 Evaluation and visualization

Parameters:
TFlength: Number of transcription factors
AdjDataSave_Dir: Path for cell-cell adjacency matrices
ModelResSavePath: Model storage path
UnionGenePairExpDataSavePath: Path for gene pair representation
TrainDataLoadDir: Storage path for training dataset
TestDataLoadDir: Storage path for test dataset

python SavePrResPic.py  --TFlength 13 --Epochs 200 --ModelResSave_Dir /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/ModelRes --PrResPicSave_Dir /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/PR_Res --UnionGenePairExpDataSavePath /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqDatabone/bone/UnionGenePariExpData
python SaveRocResPic.py  --TFlength 13 --Epochs 200 --ModelResSave_Dir /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/ModelRes  --RocResPicSave_Dir x/home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/ROC_Res --UnionGenePairExpDataSavePath /home/dreameryty/.vscode/wyj/SFINN/sc-RNAseqData/bone/UnionGenePariExpData

4. TASK 2, Evaluate SFINN on spatial transcriptome datasets

4.1 Prepare data

# Generate input data, please use:

Parameters:

TFlength: Number of transcription factors
UnionGenePairExpDataSavePath: Path for gene pair representation
ExpDataSavePath: Gene expression data file storage location
SplitIndexFilesSave_Dir: Gene Pair list interval index division file
GroundTrueSave_Dir: Groundtruth storage location
LocaldataPath: Path to the spatial location data file
DatasetName: The name of the dataset. For example, "seqFISH", "MERFISH","ST_SCC_P2_1".

python GetUnionGenePairExpData.py  --UnionGenePairExpDataSavePath  /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_dataGenerate/seqFISH  --ExpDataSavePath /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_data/seqFISH/cortex_svz_counts.csv --SplitIndexFilesSave_Dir /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_data/seqFISH/L_Rpairs_split_index.txt  --GroundTrueSave_Dir /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_data/seqFISH/L_Rpairs.txt --LocaldataPath /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_data/seqFISH/cortex_svz_cellcentroids.csv --DatasetName seqFISH
python GetSSAdjmatrix.py --TFlength 286 --ExpDataSavePath /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_data/seqFISH/cortex_svz_counts.csv  --AdjDataSave_Dir /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/Adajdata/seqFISH --UnionGenePairExpDataSavePath /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_dataGenerate/seqFISH  --LocaldataPath /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_data/seqFISH/cortex_svz_cellcentroids.csv --DatasetName seqFISH

4.2 Command to run SFINN

python SFINN.py --TFlength 286 --AdjDataSave_Dir /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/Adajdata/seqFISH --ModelResSavePath /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_result/seqFISH [--Epochs] 100   [--Lr] 1e-6 [--L2_Reg] 5e-7 [--Es_Patience] 50 [--Batch_Size] 32 --UnionGenePairExpDataSavePath /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_dataGenerate/seqFISH

4.3 Evaluation and visualization

python SavePrResPic.py  --TFlength 286 --Epochs 100--ModelResSave_Dir /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_result/seqFISH  --PrResPicSave_Dir /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_result/seqFISH_pr_res --UnionGenePairExpDataSavePath /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_dataGenerate/seqFISH
python SaveRocResPic.py  --TFlength 286 --Epochs 100 --ModelResSave_Dir /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_result/seqFISH  --RocResPicSave_Dir /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_result/seqFISH_roc_res  --UnionGenePairExpDataSavePath /home/dreameryty/.vscode/wyj/Github_for_SFINN/code/ST/ST_dataGenerate/seqFISH