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Given the following two files as input for {gt} and {DiagrammeR} we will try and use the package to display both widgets next to each other:
Input files
A text file result.txt:
entity information
"**_statTest** ; The statistical test performed to interpret the results of the study. _e.g._ **Linear Regression**, **Logistic Regression**, **Gene Burden Test (SKAT)**, **Gene Burden Test (cmcWald)**, **Survival (SKAT)**, **Survival (Burden)**" Logisitc Regression
"**_metaAnalysisTestType** ; The type of meta-analysis run. Values must be one of: **Cochran's Q Test**, **Fixed Effects**, **Random Effects**, **Fixed Effects and Random Effects**", **Unknown**, and **NA**
**_sampleSizeTotal** ; The sample size (N) of total observations 216257
**_numGenotypesPerMarker** ; The number of genotypes per marker used for the statistical test of association. This may be different from the sample size of the subjects since some genotypes may fail QC _NA_
**_pValue_** ; A quantitative confidence value that represents the probability of obtaining a result at least as extreme as that actually obtained assuming that the actual value was the result of chance alone. This version will transform any values <=5e-324 to 5e-324 (the lower limit of double values) 0.04726
"**_pValueOrig** ; The [pValueOrig](http://purl.obolibrary.org/obo/OBI_0000175) quantitative confidence value that represents the probability of obtaining a result at least as extreme as that actually obtained, assuming that the actual value was the result of chance alone. This version will contain the raw values provided in string format to avoid any float conversion errors" 0.04726
**_standardError** ; The [standard error](https://en.wikipedia.org/wiki/Standard_error) of a statistic is the standard deviation of its sampling distribution 0.0607
**_zScore** ; A [z-score](https://en.wikipedia.org/wiki/Standard_score) is the signed number of standard deviations by which the value of an observation or data point differs from the mean value of what is being observed or measured NA
**_oddsRatio** ; [oddsRatio](https://en.wikipedia.org/wiki/Odds_ratio) is the quantification of how strongly the presence or absence of property A is associated with the presence or absence of property B in a given population 0.8865657
**_beta** ; The [beta coefficient](https://www.listendata.com/2015/04/standardized-vs-unstandardized.html). It represents the amount by which dependent variable changes if we change independent variable by one unit keeping other independent variables constant -0.1204
"**_bayesFactor** ; The [Bayes factor](https://en.wikipedia.org/wiki/Bayes_factor) is a ratio of the likelihood probability of two competing hypotheses, usually a null and an alternative" _NA_
**_fdr** ; The False Discovery Rate (FDR) of a set of predictions is the expected percent of false predictions in the set of predictions _NA_
**_ciLower** ; The lower bound of a [confidence interval](https://en.wikipedia.org/wiki/Confidence_interval) _NA_
**_ciUpper** ; The upper bound of a [confidence interval](https://en.wikipedia.org/wiki/Confidence_interval) _NA_
"**_ciPercentile** ; The percentile used for determining a confidence interval. If this field is filled in, then ciUper and ciLower must be filled in" _NA_
**_numBurdenMarkers** ; The number of markers examined for the statistical test performed in a gene burden test _NA_
**_isPrimaryAnalysisPValue** ; A boolean value that indicates if the values in this entity (_i.e._ `pValue`) should be used as the main results when examining a gene in a dataset for GERMLINE scoring algorithms TRUE
**_copyNumber** ; The number of measured copies found for a specific Copy Number Variation (CNV) marker _NA_
"**_hazardRatio** ; In survival analysis, the [hazard ratio](https://en.wikipedia.org/wiki/Hazard_ratio) (HR) is the ratio of the hazard rates corresponding to the conditions described by two levels of an explanatory variable" _NA_
**_effectDirection** ; The direction of effect that a marker or allele has on a trait. Two possible values (**+** or **-**). In the context of a _case/control_ analysis **+** implies increased risk **-** implies decreased risk ; in the context of a _quantitative trait_ **+** means increased value **-** means decreased value **-**
**cochranQStat** ; The test statistic for a Cochran's Q Test for heterogeneity of effect sizes. [Cochran's Q test](https://www.itl.nist.gov/div898/software/dataplot/refman1/auxillar/cochran.htm) is a non-parametric statistical test to verify whether k treatments have identical effects _NA_
And a edr.gv file like:
digraph Association{
node [shape=box, style=rounded]
Lorem -> ipsum
dolor -> sit
sit -> amet
amet -> Lorem
amet -> consectetur
amet -> adipiscing
amet -> elit
Lorem -> sed [optional="true"]
sed -> Lorem [optional="true"]
Lorem -> do
do -> eiusmod [optional="true"]
do -> tempor [optional="true"]
do -> incididunt [optional="true"]
ut -> do [optional="true"]
do -> labore [optional="true"]
git -> labore [optional="true"]
do -> et
et -> do
ipsum -> et
dolore -> ipsum [optional="true"]
magna -> ipsum [optional="true"]
ipsum -> aliqua [optional="true"]
ipsum -> enim [optional="true"]
}
Plotting
We will try and place a {gt} table next to the diagram
Create a plot {gt} regularly
library(vroom)
library(gt)
# load table
entity_table <- vroom::vroom("result.txt", delim = "\t")
# create table and diagram
table <- entity_table %>%
mutate(entity = str_replace_all(entity, ";", "<br>")) %>%
gt() %>%
fmt_markdown(columns = everything()) %>%
tab_header(
title = md("**Lorem**"),
subtitle = md("Lorem ipsum is a placeholder text commonly used to demonstrate the visual form of a document or a typeface without relying on meaningful content.")
) %>%
tab_options(
column_labels.hidden = TRUE,
table.font.size = px(12L)
) %>%
fmt_missing(
columns = 1:2,
missing_text = "---"
)
table
{manipulateWidget} is not working for RStudio's {gt} package:
Given the following two files as input for {gt} and {DiagrammeR} we will try and use the package to display both widgets next to each other:
Input files
A text file
result.txt
:And a
edr.gv
file like:Plotting
We will try and place a {gt} table next to the diagram
Create a plot {gt} regularly
Create a EDR diagram
Demonstrate bug
Works for two {DiagrammeR} widgets though
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