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Page titleR statistics blog
Keywordsr, statistics, r statistics, sql, statistical programming, r programming, statistical modeling, scientific programming, statistics using excel, sql queries, database setup, database organization, multivariate analysis, excel programming, splus help, s plus programming, database analyst, access analyst, visual basic help, analysis of database, database programming services, database consultant, visual basic database consulant, access database programmer, database programmer, database developer, sql database programmer, c programming r, logistic regression model building, analyzing survey data, analyzing biomedical data, biomedical data mining, biomedical data analysis, object oriented programming, snp data analysis, bioinformatics, biostatistics, bioinformation, visualization
h1 tagsR-statistics blog
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How to install R 3.6.3 (NOT 4+) on Linux MINT 19.x (19.1, 19.2, 19.3)


heatmaply 1.0.0 – beautiful interactive cluster heatmaps in R

What is heatmaply?

What makes heatmaply great?

Registration for eRum 2018 closes in two days!

R 3.5.0 is released! (major release with many new features)

R 3.4.3 is released (a bug-fix release)

heatmaply: an R package for creating interactive cluster heatmaps for online publishing

R 3.4.2 is released (with several bug fixes and a few performance improvements)

R 3.4.1 is released – with some Windows related bug-fixes

R 3.4.0 is released – with new speed upgrades and bug-fixes

shinyHeatmaply – a shiny app for creating interactive cluster heatmaps

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Why I’m going to eRum this year instead of useR!

The eRum 2018 conference

Upgrading R on Windows and Mac

Upgrading to R 3.4.3 on Windows

Thank you Duncan Murdoch !

Upgrading to R 3.4.2 on Windows

Upgrading to R 3.4.1 on Windows

Upgrading to R 3.4.0 on Windows

Installing shinyHeatmaply

Running the app/gadget

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