SCPCP000006_05_explore_COPYKAT

analyses/cell-type-wilms-tumor-06/README.md

@@ -19,7 +19,7 @@ The analysis is/will be divided as the following:
 - [x] Metadata file: compilation of a metadata file of marker genes for expected cell types that will be used for validation at a later step
 - [x] Script: clustering of cells across a set of parameters for few samples
 - [x] Script: label transfer from the fetal kidney atlas reference using runAzimuth
-- [ ] Script: run InferCNV
+- [x] Script: run copykat and inferCNV
 - [ ] Notebook: explore results from steps 2 to 4 for about 5 to 10 samples
 - [ ] Script: compile scripts 2 to 4 in a RMardown file with required adjustements and render it across all samples
 - [ ] Notebook: explore results from step 6, integrate all samples together and annotate the dataset using (i) metadatafile, (ii) CNV information, (iii) label transfer information
@@ -253,7 +253,6 @@ The `renv` lockfile is used to install R packages in the Docker image.
 
 ## Computational resources
 
-
 ## References 
 
 - [1] https://www.ncbi.nlm.nih.gov/books/NBK373356/ 

analyses/cell-type-wilms-tumor-06/notebook/README.md

@@ -34,4 +34,19 @@ In brief, we explore the clustering results, we look into some marker genes, pat
 The next step in analysis is to identify tumor vs. normal cells.
 
 - `04_annotation_Across_Samples_exploration.html` is the output of the [`04_annotation_Across_Samples_exploration.Rmd`](../notebook/04_annotation_Across_Samples_exploration.Rmd) notebook. 
-In brief, we explored the label transfer results across all samples in the Wilms tumor dataset SCPCP000006 in order to identify a few samples that we can begin next analysis steps with.
+In brief, we explored the label transfer results across all samples in the Wilms tumor dataset SCPCP000006 in order to identify a few samples that we can begin next analysis steps with.
+
+## Exploratory analysis
+
+We selected in [`04_annotation_Across_Samples_exploration.Rmd`](../notebook/04_annotation_Across_Samples_exploration.Rmd) 5 samples to test for aneuploidy and CNV inference:
+- sample SCPCS000194 has > 85 % of cells predicted as kidney and 234 + 83 endothelium and immune cells.
+- sample SCPCS000179 has > 94 % of cells predicted as kidney and 25 + 111 endothelium and immune cells.
+- sample SCPCS000184 has > 96 % of cells predicted as kidney and 39 + 70 endothelium and immune cells.
+- sample SCPCS000205 has > 89 % of cells predicted as kidney and 92 + 76 endothelium and immune cells.
+- sample SCPCS0000208 has > 95 % of cells predicted as kidney and 18 + 35 endothelium and immune cells.
+
+We wanted to test `copykat` results obtained with or without normal cells as reference, using either an euclidean or statistical (spearman) method for CNV heatmap clustering. 
+This impact the final decision made by `copykat` for each cell to be either aneuploid or diploid, and it is thus crucial to explore the results using the different methods.
+For each of the selected samples, we explore the results in the template `notebook` [`05_copykat_exploration.Rmd`](../notebook_template/05_copykat_exploration.Rmd), which creates a notebook `05_cnv_copykat_exploration_{sample_id}.html` for each sample.
+These `notebooks` are inspired by the plots written for the Ewing Sarcoma analysis in [`03-copykat.Rmd`](https://github.com/AlexsLemonade/OpenScPCA-analysis/blob/main/analyses/cell-type-ewings/exploratory_analysis/03-copykat.Rmd).
+