cell type/tumor annotation for ETP T-ALL (SCPCP000003)

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

#629

### Describe the goals of this analysis module.

The goal is to annotate cell type and tumor/normal status for each ETP T-ALL samples (n=31) in SCPCP000003. I followed the same analysis module, as proposed in non-ETP T-ALL (Issues: #761 and #787):

- using [SAM](https://github.com/atarashansky/self-assembling-manifold) algorithm to separate the cells
- [ScType](https://github.com/IanevskiAleksandr/sc-type) for cell type annotation using the same marker list
- [CopyKat](https://github.com/navinlabcode/copykat) for identification of malignant cells based on the profile of genome-wide aneuploidy

### 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-ETP-ALL-03 --use-r --use-renv --use-conda --conda-file-only`
- Adding analysis code for `00-01_processing_rds.R`, `02-03_annotation.R`, and `multipanel_plot.R`

### What computational resources will you require?

I am using a standard-4XL virtual machine via AWS Lightsail for Research.

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

~Today or tomorrow

Start with Discussion #629 and the related non-ETP T-ALL analyses in Issues #761 and #787. Create the module skeleton with the provided create-analysis-module.py command, then review 00-01_processing_rds.R, 02-03_annotation.R, and multipanel_plot.R as the implementation targets. Done means the ETP T-ALL module contains processing, cell-type and tumor/normal annotation, and panel plotting code using the stated R packages.

Written by the indexing model from the issue text.