Celltype annotation for non-ETP ALL (SCPCP000003)

### Please link to the GitHub Discussion for this proposed analysis.

#630

### Describe the goals of this analysis module.

The goal of this analysis is to perform cell type annotation for non-ETP ALL samples in the portal.

Here are the steps taken:

**00. Pre-processing the provided SCE objects**
- Formatting SCE objects to Seurat objects for downstream analysis
- Setting the filter of percent.mt < 25
- Features processing: (1) dropping features with 0 counts across all cells and (2) selecting feature that is curated and has the highest count for those features that have multiple gene_IDs mapping to single gene_symbols. For multi-mapped features, features with gene_IDs starting from LINC*, SNO*, U*, and Y_RNA are dropped. These steps lead to a (3) unique mapping of gene_ID to gene_symbols.
- Doublet removal (using annotation from ALSF)

**01. Feature selection/dimensionality reduction**
- Using [self-assembling manifold algorithm](https://github.com/atarashansky/self-assembling-manifold), which is a soft feature selection strategy for better separation of more homogenous populations

**02. Cell type annotation with marker genes**
- Using [ScType](https://github.com/IanevskiAleksandr/sc-type) to annotate cell type with markers from Azimuth reference (Human - Bone Marrow) and cancer marker from immune system in ScType database

**03. Tumor cell identification**
- Using [CopyKat](https://github.com/navinlabcode/copykat) to identify genome-wide aneuploidy in single cell for distinguishing tumor cells from normal cells, by providing annotated B cells as normal cells

### What software will you require?

- R (4.2.3)
- Main packages: `Seurat`, `reticulate`,`SAM`,`ScType`,`CopyKat`

### What will your first pull request contain?

- Creating a module skeleton

`./create-analysis-module.py cell-type-nonETP-ALL-03 --use-r --use-renv --use-conda --conda-file-only`

- Adding analysis code for `00. Pre-processing the provided SCE objects`

### What computational resources will you require?

I am currently using our own computing system for the analysis. I may need help in transferring files or large objects, if there is any issue encountered in the future.

### If known, when do you expect to file the first pull request?

~ 09/20/2024

Start with the create-analysis-module.py command shown in the issue to create the R module skeleton, then review the provided SCE-to-Seurat preprocessing steps and the listed package requirements. Done means the module skeleton exists and includes the preprocessing stage for the non-ETP ALL samples.

Written by the indexing model from the issue text.