diff --git a/scRNA-seq/exercise_01-scrna_quant.Rmd b/scRNA-seq/exercise_01-scrna_quant.Rmd
index 1e66ee77..a54a73af 100644
--- a/scRNA-seq/exercise_01-scrna_quant.Rmd
+++ b/scRNA-seq/exercise_01-scrna_quant.Rmd
@@ -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.
 
@@ -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.