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HubmiR

Predicting miRNA Expression Level in Single-Cell Clusters for hub-miRNA Discovery. Online application is deposited at https://awi.cuhk.edu.cn/~HubmiR/

Usage

Dependency

The following packages are required for running HubmiR:

R

Seurat

python
	
sys, torch, torch.nn, numpy, pandas, sklearn.model_selection

Command

  • Step1: Process the input data location/for/Rscript /location/for/package/HubmiR/script/input_processing.R args[1] args[2] args[3] .

    • ALL Parameters should be quoted by "" or ''.

    • parameter args[1] select which type of pooling of data: "celltypeavg" for average of annotated cell type. "pooledavg" for random pooling of cells in the same cell type.

    • parameter args[2] file directory for input profile. Format see the Demo_input.csv in files folder. This directory should contain ONLY the input files. End with "/".

    • parameter args[3] output directory. End with "/".

  • Step2: Input the processed data into HubmiR for miRNA expression profile prediction location/for/python /location/for/package/HubmiR/script/DNN.py args[4] .

    • ALL Parameters should be quoted by "" or ''.
    • parameter args[4] Same directory as args[3] where the processed file(s) was(were) stored. End with "/".