Update 04_cellranger_QC.md

lessons/04_cellranger_QC.md

@@ -121,7 +121,12 @@ Once cellranger has finished running, there will be a folder titled `outs/` in a
 
 The Web Summary HTML file is a great resource for looking at the basic quality of your sample before starting on an analysis. 10x has a [page describing each metric](https://www.10xgenomics.com/analysis-guides/quality-assessment-using-the-cell-ranger-web-summary) in depth. There are two pages/tabs included in a scRNA report titled "Summary" and "Gene Expression". 
 
-We have included these Web Summary files for the control and stimulated dataset in the [data](https://www.dropbox.com/s/vop78wq76h02a2f/single_cell_rnaseq.zip?dl=1) provided for the workshop. Please note that some of the values in these reports will be slightly different from current standards, as these samples were generated using the version 1 chemistry kit and optimization have been made since then.
+We have included these Web Summary files for the control and stimulated samples as links below. You can **download each, and move the HTML to your project folder**:
+
+* [Control sample](https://www.dropbox.com/scl/fi/skjyyvs9078pbef7s4qvb/ctrl_web_summary.html?rlkey=335gw4qmy29uny5813wg0zakr&dl=1) report
+* [Stimulated sample](https://www.dropbox.com/scl/fi/r6n83y57cd7vhc130zm1g/stim_web_summary.html?rlkey=50ur193yfsy5ex9urkmr87h3c&dl=1) report
+
+> **NOTE:** Some of the values in these reports will be slightly different from current standards, as these samples were generated using the version 1 chemistry kit and optimization have been made since then.
 
 ### Summary
 
@@ -220,7 +225,12 @@ Similar to the sequencing saturation plot, looking at the median gene per cells
 
 ## Metrics evaluation
 
-Many of the core pieces of information from the web summary are stored in the `metrics_summary.csv` file. As this is a csv file, we can read it into R and generate plots to include in reports on the general quality of the samples.
+Many of the core pieces of information from the web summary are stored in the `metrics_summary.csv`. As this is a csv file, we can read it into R and generate plots to include in reports on the general quality of the samples.
+
+We have included these csv files for the control and stimulated samples as links below. You can right-click on the link and "Save as..." into your project folder:
+
+* [Control sample](https://www.dropbox.com/scl/fi/qnz44ng51ojmhu44acc8g/ctrl_metrics_summary.csv?rlkey=gyk570whhtk3c4z1t4414yne2&dl=1) `metrics.csv` file
+* [Stimulated sample](https://www.dropbox.com/scl/fi/gaa4sabcbhwqpuogfh0us/stim_metrics_summary.csv?rlkey=h2uokc9r2edeinxtzgrpw3ds4&dl=1) `metrics.csv` file
 
 First, to read the files in: