The following data will be used in the used for the exercises in this course. The data comes from a mock RNA sequencing data with 12 samples that are from cell-lines. As in any normal RNAseq analysis the counts of genes were normalized using different methods such as VST and CPM after filtering out the genes that were of very low expression. We would use these data for visualizations.

Download all of these files into your current working directory

You can download all the files together here. Make a directory called data and unzip in that directory!

If workshop_on_plotting_in_R is the current working directory, the directory tree should look like this:

  • ggplot_geneco_course
    • data
      • counts_deseq2.txt
      • counts_filtered.txt
      • counts_raw.txt
      • counts_vst.txt
      • metadata.csv
      • human_biomaRt_annotation.csv
      • Time_t24_vs_t0.txt
      • Time_t2_vs_t0.txt
      • Time_t6_vs_t0.txt
      • shiny_app_data.csv
      • Blood_Cells_Image.jpeg

You can find the information related to the important files below:

1 Counts tables

2 Metadata

3 DE genes

Below are the lists of differentially expressed genes between different time points

4 Shiny App data

For the sake of making a shiny app the real time data of covid related scenarios for handful of countries have been in a specific period starting from the onset of the pandemic until few months after the start of the global vaccination campaign has been downloaded from Ourworldindata.

  • covid data table for the ShinyApp here