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Merge pull request #771 from AlexsLemonade/auto_copy_exercises
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GHA: Automated transfer of exercise notebooks
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sjspielman authored May 30, 2024
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Expand Up @@ -16,10 +16,10 @@ In this exercise notebook we will be using [*Tabula Muris* project](https://www.
- Part B of this exercise is using the quantified data to conduct cell filtering and normalization of `10X_P7_12`.
- Part C of this exercise will introduce you to performing doublet detection using `10X_P7_12`.

You are welcome to [skip to Part B](#part_b:_performing_dimension_reduction_on_10x_p7_12’s_cells) if you are not interested in performing the quantification steps with Alevin.
You are welcome to skip to Part B if you are not interested in performing the quantification steps with Alevin.
Do not skip to Part C! You will need to complete Part B before completing Part C.

# Part A: Quantifying single-cell expression of a mammary gland sample.
## Part A: Quantifying single-cell expression of a mammary gland sample.

In this part of the exercise we will be following the same steps for a tag-based scRNA-seq sample as we did in the `01-scRNA_quant_qc.Rmd` notebook.

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[alevinLog] [info] Finished optimizer
```

## Part B: Performing dimension reduction on 10X_P7_12's cells
## Part B: Performing filtering and normalization on 10X_P7_12 cells

In the second half of this exercise notebook, we will use the Alevin quantified data from sample `10X_P7_12` to perform cell filtering and normalization.

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