R: How to make professional and beautiful plots
R Studio: https://www.rstudio.com/
How to install R Packages:
> install.packages("PACKAGE")# using bioconductor.org> source("https://bioconductor.org/biocLite.R")> biocLite("PACKAGE")
Common used packages
To load data:
RMySQL: read in data from a database or Excel.
xlsx: read in data from a Excel.
To manipulate data:
stringr: easy to learn tools for regular expressions and character strings.
reshape2: transform data between wide and long formats.
To visualize data:
ggplot2: plotting system for R, based on the grammar of graphics
plotly: R package for creating interactive web-based graphs
To model data:
lme4, nlme: Linear and Non-linear mixed effects models
randomForest: Random forest methods from machine learning
glmnet: Lasso and elastic-net regression methods with cross validation
NMF: do non-negative matrix factorization
To do bioinformatics:
limma, DESeq2, edgeR: do differential expression: link
survival: Tools for survival analysis
motifRG, MotIV, MotifDb: motif search and enrichment
enrichR: GO term enrichment
To write your own R packages:
devtools: An essential suite of tools for turning your code into an R package.
To color your figure:
colorbrewer: Creates nice looking color palettes especially for thematic maps http://colorbrewer2.org/