Further development in MarkdownReports. See: #4. MarkdownReportsDev was made when big changes were happening. The development reached its goals. Further development will be in MarkdownReports.
Old version is under MarkdownReports.LEGACY.VERSION.X.X.X
.
MarkdownReports is a set of R functions that allows you to generate precise figures easily, and create clean reports in markdown language about what you just discovered with your analysis script. It helps you to:
I do exploratory data analysis as a daily routine, and I have constant interaction with all sorts of people: supervisors, collaborators, colleagues, etc.
I often have to...
For all of the above, my solution is MarkdownReports. I think its better than other solutions I found. Many of those like to combine source code with results, and many are too complex to use. Most of people I interact with are not interested in the source code, but are very keen on seeing my results from all possible angles and are asking detailed questions about the analysis.
.pdf
dynamically named (from variable names)wboxplot()
takes a list, used the variable name
to set the filename and the title, list element names
to set the x-axis labels, saves the file as variable name.pdf
(or .png
).wplot()
, wbarplot()
, wpie()
, wboxplot()
,but also wvenn()
, wvioplot_list()
,wviostripchart_list()
.Filter.and.Stats by ExpressionAnalysis.R
log_settings_MarkDown()
and the md.LogSettingsFromList()
functions.GeneExpression = rnorm(2000, mean = 100, sd=50);
MinExpression=125
PASS=filter_HP(GeneExpression, threshold = MinExpression)
and your report will have the summary: 30.7 % or 614 of 2000 entries in GeneExpression fall above a threshold value of: 125.
wbarplot()
natively.barplot_label()
. wplot()
.wcolorize()
from base
, gplots
and Rcolorbrewer
.wlegend(colannot$categ)
, defining colors named after the categories of your data. colannot = wcolorize(your.annotation, ReturnCategoriesToo = T)
, which you (can) anyways use to colour data points on, say, your scatterplot.whist(rnorm(1000), vline = .5, filtercol = T)
.wplot_save_this()
or the pdfA4plot_on()
and pdfA4plot_off()
functions.Install directly from GitHub via devtools with one R command:
# install.packages("devtools"); # If you don't have it
require("devtools")
devtools::install_github(repo = "vertesy/MarkdownReportsDev")
...then simply load the package:
require("MarkdownReports")
Alternatively, you simply source it from the web. This way function help will not work, and you will have no local copy of the code on your hard drive.
source("https://raw.githubusercontent.com/vertesy/MarkdownReportsDev/master/R/MarkdownReportsDev.R")
[3.1.1 is under legacy now]
Function argument names now mirror the R base
argument names (99%).
Think of xlb >>> xlab
, or sub_ >>> sub
The package now can also work with png images.
You can save files in png, which can be displayed inside the markdown file on windows 7.
You need to set b.usepng=T
in setup_MarkdownReports
: setup_MarkdownReports(OutDir = "/Users/...blabla....", b.usepng=T)
The package contains multiple other bug fixes:
Self consistency: some missing functions moved from CodeAndRoll.R
md.tableWriter.DF.w.dimnames()
and md.tableWriter.VEC.w.names()
Enhancements:
filter_HP(), filter_LP(), filter_MidPass()
show histogram
whist()
can invite the above filter functions.Old version is under MarkdownReports.LEGACY.VERSION
.
Abel Vertesy. (2017, October 17). MarkdownReports: An R function library to create scientific figures and markdown reports easily. (Version v2.9.5). Zenodo. http://doi.org/10.5281/zenodo.594683
MarkdownReports is a project of @vertesy.
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