From 532b8c5451760e5d87e28caac7ef893d4c5dcef0 Mon Sep 17 00:00:00 2001 From: Emma Rand Date: Fri, 15 Mar 2024 10:46:27 +0000 Subject: [PATCH] babs4/week-6 overview --- r4babs4/week-6/overview.qmd | 24 ++++++++++++++++++------ r4babs4/week-6/study_before_workshop.qmd | 2 +- 2 files changed, 19 insertions(+), 7 deletions(-) diff --git a/r4babs4/week-6/overview.qmd b/r4babs4/week-6/overview.qmd index bd254147..dd62e80f 100644 --- a/r4babs4/week-6/overview.qmd +++ b/r4babs4/week-6/overview.qmd @@ -5,19 +5,23 @@ toc: true toc-location: right --- -This week you will + ### Learning objectives The successful student will be able to: -- +- evaluate their progress and identify any steps they have missed + +- create density plots to visualise the distribution, and gating of, + the APC TNF-α and FTIC signals in live cells -- +- calculate the the percentage of cells in each quadrant of a quadrant + gated gated plot of TNFa_APC_Lin signal against the E_coli_FITC_Lin -- +- annotate ggplots as desired -- +- import data from a googlesheet ### Instructions @@ -26,7 +30,15 @@ The successful student will be able to: 2. [Workshop](workshop.qmd) - i.💻 + i. 💻 Create density plots to visualise the distribution, and gating of, + the APC TNF-α and FTIC signals in live cells + + ii. 💻 Calculate the the percentage of cells in each quadrant of a quadrant + gated gated plot of TNFa_APC_Lin signal against the E_coli_FITC_Lin + + iii. 💻 Annotate ggplots + + iv. 💻 Import data from a googlesheet 3. [Consolidate](study_after_workshop.qmd) diff --git a/r4babs4/week-6/study_before_workshop.qmd b/r4babs4/week-6/study_before_workshop.qmd index 63504607..0eb07e74 100644 --- a/r4babs4/week-6/study_before_workshop.qmd +++ b/r4babs4/week-6/study_before_workshop.qmd @@ -56,7 +56,7 @@ from wherever you got to. vi. You should be able add a gate for the FITC positive cells and label the rows (cells) in the dataframe as FITC positive or FITC negative. You should be able to - calculate the number and percentage of TNF-α positive cells + calculate the number and percentage of FITC positive cells in each sample using the same logic as in v. 3. 💻 Prepare to analyse your own data / the model data