The repository contains source code for the single nuclei data analysis for the study
D.R. Ghasemi, K.Okonechnikov et al "Compartments in medulloblastoma with extensive nodularity are connected through differentiation along the granular precursor lineage"
10X single nuclei data analysis (R 4.1)
Processing reads with CellRanger: run_cellranger.sh
Seurat main analysis: processTumorSample.R
Mark doublets: runDecontX_perSample.R
SingleR comparison to reference: runSingleR_perSample.R
Infer CNV copy number profiling: runInferCNV_perSample.R
Analysis Decoupler and LIANA: post_analysis subfolder (includes additional documentation)
Smart-seq2 snRNA-seq data analysis (R 4.1, python 2.8)
Align reads per cell: run_STAR.sh
Compute counts per cell: run_compCounts.sh
Merge the cells of a sample into one matrix: summarizeComputedCounts.py
Convert gene IDs to names: renameCounts.py
Seurat main analysis: processTumorSampleSmartSeq2.R
Resolve Bioscence spatial data analysis (R 4.1)
Seurat per sample analysis: resolveSeurat.R
Giotto additional analysis (cell proximity): giotto_per_sample.R
Combined analysis for merged cohort: resolveMergedAnalysis.R
Details of R enviroment suitable for packages run