Independent Study to prepare for workshop

Data Analysis 4: Biomedical sciences - Your data presentation

The independent study allows you to check you have the files you need having applied the workflow from Week 2 to your own data (or the replacement data if you do not have your own data) in Week 4. However, you will be able to use files prepared from the sample data for the week 6 workshop if you have not completed week 4.

  1. You should have an RStudio Project with at least: folders for raw data, meta data, samples after quality control and processed data, a script

  2. You should have processed data files:

    • ai_clean_logicle_trans.csv: Each row is a cell. These are the AI cleaned cells with logicle-transformed TNFa_APC_Lin and E_coli_FITC_Lin signals. Each cell is labelled with the sample (filename) it came from, its treatment and antibody. The cells have not been gated -
      i.e., some of the “cells” in this dataset are dead/debris.
    • clean_trans_live_tfna_pos.csv: Each row is a sample (a treatment-antibody combination). For each sample there is: the number of cells after AI cleaning, the number of live cells after gatting, the percentage of live cells, the number TNF-α postive cells, the percentage of TNF-α postive cells and the of the mean APC signal in the live cells and TNF-α postive cells
    • live_labelled.csv: Each row is a cell. These are the AI cleaned, live cells with logicle-transformed TNFa_APC_Lin and E_coli_FITC_Lin signals. Each cell is labelled with the sample (filename) it came from, its treatment and antibody, and whether it is TNF-α positive (i.e. has a TNFa_APC_Lin level above the APC cut off used) or negative and whether it is FITC positive (i.e. E_coli_FITC_Lin level above the FITC cut off used) or negative.
    • you may also have the FITC equivalent of clean_trans_live_tfna_pos.csv

  3. Enter the values from your analysis to: BIO00066I Biomedical Sciences class data. The column names are the same as those used in the Data Analysis 2: Biomedical sciences - Sample data analysis workshop. The columns you must add are marked in green. Other information helps you get to the required values and helps others determine the reliability of your data. The workshops show how to calculate all these values.