index.Rmd

---
title: 'Genekitr: Gene Analysis Toolkit based on R'
author: Yunze Liu
date: "`r Sys.Date()`"
knit: "bookdown::render_book"
site: bookdown::bookdown_site
output:
  bookdown::bs4_book:
always_allow_html: yes
toc_appendix: yes
link-citations: yes
github-repo: GangLiLab/book_genekitr
twiter-handle: ReedLiu1314
description: "Genekitr: Gene Analysis Toolkit based on R"
documentclass: book
papersize: A4
classoption: twoside
highlight_bw: yes
---


```{r initial, include=FALSE}
library(cowplot)
library(patchwork)

CRANpkg <- function (pkg) {
    cran <- "https://CRAN.R-project.org/package"
    fmt <- "[%s](%s=%s)"
    sprintf(fmt, pkg, cran, pkg)
}

Biocpkg <- function (pkg) {
    sprintf("[%s](http://bioconductor.org/packages/%s)", pkg, pkg)
}

Githubpkg <- function (user, pkg) {
    gh <- "https://github.com"
    fmt <- "[%s](%s/%s/%s)"
    sprintf(fmt, pkg, gh, user, pkg)
}

pkgVersion <- function(pkg, col="green") {
    ver <- packageVersion(pkg)
    uni <- paste0("![](https://img.shields.io/badge/%20",pkg,'-', ver, "-", col, ".svg)")
    url <- paste0("https://github.com/GangLiLab/", pkg)
    
    res <- paste0("[", uni, "](", url, ")")
    return(res)
}

Entrez <- function(gene){
  sprintf("[%s](https://www.ncbi.nlm.nih.gov/gene/%s)", gene, gene)
}

Ensembl <- function(gene){
  sprintf("[%s](https://www.ensembl.org/id/%s)", gene, gene)
}

Uniprot <- function(pro){
  sprintf("[%s](https://www.uniprot.org/uniprot/%s)", pro, pro)
}

library(knitr)
opts_chunk$set(message=FALSE, warning=FALSE, eval=TRUE, 
    echo=TRUE, cache=TRUE, out.width="98%")
```


# 🧬 Welcome to genekitr! {-}

`r pkgVersion("genekitr")`
`r pkgVersion("geneset")`

The book is a tutorial for gene information query, gene/protein/probe identifier conversion, gene enrichment analysis, and publication-level plotting.

If you are new to R, do not worry, this book will set enough example codes to help you. After reading this book, you could plot figures based on your data.


```{r workflow, echo=FALSE}
knitr::include_graphics("figures/overview.png")
```



## 🍱 Content {-}

+ Part 1 (Search Information) introduces how to search gene metadata and PubMed papers.
+ Part 2 (ID Conversion) describes ID conversion among symbol & alias, NCBI Entrez, Ensembl, Uniprot and microarray probe. 
+ Part 3 (Enrichment Analysis) describes the gene sets and two widely used functional enrichment methods: over-representation analysis (ORA) and functional class scoring (FCS).
+ Part 4 (Plotting) includes 13 ORA plots, 5 FCS-GSEA plots, 2 Venn plots, and 1 Volcano plot. 

## 💝 Welcome to contribute {-}

Book source code at <https://github.com/GangLiLab/book_genekitr>. 

If you get some ideas or issues, please feel free to [post feedback](https://github.com/GangLiLab/book_genekitr/issues/new).