Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

GHA: Automated transfer of exercise notebooks #771

Merged
merged 1 commit into from
May 30, 2024
Merged

GHA: Automated transfer of exercise notebooks #771

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 3 additions & 3 deletions scRNA-seq/exercise_01-scrna_quant.Rmd
View file
Open in desktop
Original file line number Diff line number Diff line change
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.

Expand Down Expand Up @@ -200,7 +200,7 @@ This will take some time; when it is done the last message you will see is
[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.

Expand Down