Modify/explore clustering for Wilms tumor annotation (SCPCP000014)

### If you are filing this issue based on a specific GitHub Discussion, please link to the relevant Discussion.

https://github.com/AlexsLemonade/OpenScPCA-analysis/discussions/628

### Describe the goals of the changes to the analysis module.

The goal in this section is to explore and improve the clustering for Wilms tumor samples in `SCPCP000014`.
- I tried an alternative feature selection method [SAM](https://elifesciences.org/articles/48994)
- I utilized the clustering function in this repo [`calculate-clusters.R`](https://github.com/AlexsLemonade/OpenScPCA-analysis/blob/main/packages/rOpenScPCA/R/calculate-clusters.R).
- I explored clustering by looking at anchor transfer results I generated before.

### What will your pull request contain?

R script to run [SAM](https://elifesciences.org/articles/48994) algorithm across 10 samples.
R markdown to explore clustering.

### Will you require additional software beyond what is already in the analysis module?

[SAM](https://elifesciences.org/articles/48994) and its dependencies, which would be installed in a conda environment.

### Will you require different computational resources beyond what the analysis module already uses?

No.

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

This section depends on results generated from anchor transfer. I would create a PR as soon as https://github.com/AlexsLemonade/OpenScPCA-analysis/pull/836 is merged.

Start with the linked Discussion 628 and the clustering implementation in packages/rOpenScPCA/R/calculate-clusters.R. Review the results from anchor transfer and the dependency on pull request 836, then examine the proposed SAM approach across the 10 samples. Done means an R script and R Markdown analysis documenting the clustering exploration and improvement.

Written by the indexing model from the issue text.