In this vignette we will demo how to visualize data which is only available in summary format as it is coming from a published paper table or figure for example Figure 3 from this paper:
“Remdesivir for the Treatment of Covid-19 — Final Report”
JH Beigel et al. N Engl J Med 2020. DOI: 10.1056/NEJMoa2007764
The data has been made available in a csv data file named
remdesivirfig3.csv
library(ggquickeda) #load ggquickeda
<- read.csv("./remdesivirfig3.csv") # in vignette folder
remdesivirdata ::kable(remdesivirdata) knitr
Subgroup | Subgroupvalue | Subgroupvalueorder | N.of.patients | Recovery.Rate.Ratio | RRLCI | RRUCI |
---|---|---|---|---|---|---|
All Patients | 1 | 1062 | 1.29 | 1.12 | 1.49 | |
Geographic Region | North America | 2 | 847 | 1.30 | 1.10 | 1.53 |
Geographic Region | Europe | 3 | 163 | 1.30 | 0.91 | 1.87 |
Geographic Region | Asia | 4 | 52 | 1.36 | 0.74 | 2.47 |
Race | White | 5 | 566 | 1.29 | 1.06 | 1.57 |
Race | Black | 6 | 226 | 1.25 | 0.91 | 1.72 |
Race | Asian | 7 | 135 | 1.07 | 0.73 | 1.58 |
Race | Other | 8 | 135 | 1.68 | 1.10 | 2.58 |
Ethnic group | Hispanic or Latino | 9 | 250 | 1.28 | 0.94 | 1.73 |
Ethnic group | Not Hispanic or Latino | 10 | 755 | 1.31 | 1.10 | 1.55 |
Age | 18 to < 40 yr | 11 | 119 | 1.95 | 1.28 | 2.97 |
Age | 40 to < 65 yr | 12 | 559 | 1.19 | 0.98 | 1.44 |
Age | >= 65 yr | 13 | 384 | 1.29 | 1.00 | 1.67 |
Sex | Male | 14 | 684 | 1.30 | 1.09 | 1.56 |
Sex | Female | 15 | 278 | 1.31 | 1.03 | 1.66 |
Symptoms duration | <= 10 days | 16 | 676 | 1.37 | 1.14 | 1.64 |
Symptoms duration | > 10 days | 17 | 383 | 1.20 | 0.94 | 1.52 |
Baseline Ordinal Score | 4 (not receiving oxygen) | 18 | 138 | 1.29 | 0.91 | 1.83 |
Baseline Ordinal Score | 5 (receiving oxygen) | 19 | 435 | 1.45 | 1.18 | 1.79 |
Baseline Ordinal Score | 6 (receiving high-flow oxygen) | 20 | 193 | 1.09 | 0.76 | 1.57 |
Baseline Ordinal Score | 7 (receiving mv or ECMO) | 21 | 285 | 0.98 | 0.70 | 1.36 |
# from R launch the app with the data
#run_ggquickeda(remdesivirdata)
# if you have access the the app on a server browse to the file and load it
Summary Data Mapping
Graph Splitting
We still have to set text formatting options using the group of subtabs in the lower part of the page:
At this point you should have this graph:
Facet Options
reordering of subgroup
While you can add another variable and manually drag and drop we will demo next another possibility to reorder yvalues using a statistic (e.g. median) of another variable (Subroupvalueorder):
reordering of Subgroupvalue
Median/PI options
And now you should get the below plot !:
ggquickeda
As an example of even more advanced features consider the screenshot below where the Intervals Values are shown while the point Size is proportional to the N of patients. Some theme adjustments to customize the plot and legend were also done.
more options