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Spatial transcriptomics analysis of Medulloblastoma PDX models

For sharing scripts on analyses of MedulloBlastoma patient-derived xenograft (MB-PDX) of Visium spatial RNA-seq between Palbociclib treated & control samples.

Installation

Used Python 3.7.10. Python dependency install:

pip install -r requirements.txt

Need to install stLearn and add to your python path:

 git clone https://github.com/BiomedicalMachineLearning/stLearn.git

For R scripts, see session info in docs/r_session.md

Quick Index

docs/ -> Contains project documentation.

    index.md -> Index which describes each script in scripts/ in terms of 
                INPUT/OUTPUT, and brief description of function.
                
    r_session.md -> Details on the r session used to run the R scripts. 
                
figure_components/ -> Contains the outputted components which are used to 
                        create the paper figures. Is grouped according to 
                        the figure. You can see index.md for which script
                        generates what figure components by checking the 
                        script OUTPUT description. 
                
scripts/ -> Contains the scripts described in docs/index.md.
            Scripts are grouped into folders relating to order & analysis
            performed.

    X1_QC_SpeciesClassify/ -> Contains scripts related to spot QC & 
                                       classifying spots by human/mouse/mix.

    X2_DEAnalysis/ -> Contains scripts related to the DE analysis between
                        Palbo treated & control samples pseudobulked by 
                        human/mix/mouse spots. 
                        Also includes PCA & GSEA analyses. 

    X3_GiottoEnrichment/ -> Contains scripts related to the Giotto 
                                enrichment analysis ('Per-spot enrichment').
                                
    X4_HumanSpotAnnotation/ -> Contains scripts related to annotating 
                                human spots
                                by dominant cell type using reference 
                                scRNA-seq data using SingleR.
                                
    X5_MouseSpotAnnotation/ -> Contains scripts related to annotating 
                                mouse spots
                                by dominant cell type using reference 
                                scRNA-seq data using SingleR.

X6_CellCellInteraction/ -> Contains code related to called ligand-
			   receptor & cell-cell interactions in the
			   interface region for human & mouse tissue.  
			   
X7_revision-analysis/ -> Analysis conducted during revision process, 
                                performed by Dr. Guiyan Ni, and Onkar Mulay.

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