MAGeCKFlute combines the MAGeCK and MAGeCK-VISPR algorithms and incorporates additional downstream analysis functionalities.

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前面部分还是用MAGeCK处理

Integrative analysis of pooled CRISPR genetic screens using MAGeCKFlute
GitHub - liulab-dfci/MAGeCK: Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout image.png

• MAGeCK（Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout):识别CRISPR KO中重要基因的计算工具
  MAGeCK / Wiki / Home (sourceforge.net)
  文章： MAGeCK enables robust identification of essential genes from genome-scale CRISPR/Cas9 knockout screens | Genome Biology | Full Text (biomedcentral.com)

• MAGeCK-VISPR：(MAGeCK+VISPR)
  QC\分析\可视化
  liulab / mageck-vispr — Bitbucket
  文章：Quality control, modeling, and visualization of CRISPR screens with MAGeCK-VISPR | Genome Biology | Full Text (biomedcentral.com)

• MAGeCKFlute（R包)(MAGeCK+VISPR+下游功能分析) :protocol:https://www.nature.com/articles/s41596-018-0113-7

---

根据MAGeCKFlute protocol 复现

MAGeCK

count

20220914141834.png

#cd demo/fastq
$mageck count -l library.csv 
-n GSC_0131 
--sample-label day0_r1,day0_r2,day23_r1,day23_r2 
--fastq GSC_0131_Day0_Rep1.fastq.gz GSC_0131_Day0_Rep2.fastq.gz GSC_0131_Day23_Rep1.fastq.gz GSC_0131_Day23_Rep2.fastq.gz

20220914143443.png

test(hits calling)（RRA）

$mageck test 
-k GSC_0131.count.txt 
-t day23_r1,day23_r2 -c day0_r1,day0_r2 
-n GSC_0131_rra 
--remove-zero both 
--remove-zero-threshold 0

$mageck mle 
--count-table rawcount.txt 
--design-matrix designmatrix.txt 
--norm-method control 
--control-sgrna nonessential_ctrl_sgrna_list.txt 
--output-prefix braf.mle

---

MAGeCK-VISPR

Installation

conda create -n mageck-vispr  python=3.7

conda activate mageck-vispr

conda install -c conda-forge mamba

mamba install -c bioconda -c conda-forge mageck-vispr

#conda update mageck-vispr
#source deactivate

git clone https://bitbucket.org/liulab/mageck-vispr.git
#test里的已经尝试运行，成功

Usage

input：fastq
init (outputdir)→（readme、config.yaml、snakefile）
在config.yaml里输入实验数据。
cd outputdir
snakemake -n
snakemake --cores 8

result/log

#Step 0: Activate the mageck-vispr environment

source activate mageck-vispr

#Step 1: Choosing a workflow directory(where the workflow shall be executed and results will be stored.)(choose a meaningful name and ensure that the directory is empty.)
cd wd
#Step 2: Initializing a new workflow
mageck-vispr init path/to/my/workflow --reads path/to/sample1.fastq path/to/sample2.fastq 
#mageck-vispr init /home/yijia/mageck-vispr/test 
#--reads /home/yijia/mageck-vispr/test/esc.testdata.step2/esc-testdata/reads/ERR376998.subsample.fastq /home/yijia/mageck-vispr/test/esc.testdata.step2/esc-testdata/reads/ERR376999.subsample.fastq /home/yijia/mageck-vispr/test/esc.testdata.step2/esc-testdata/reads/ERR377000.subsample.fastq


#which installs a `README`, a config file `config.yaml` and a [Snakemake]workflow definition (a `Snakefile`) to the given directory.


#Step 3: Configure the workflow

#open the config.yaml file. 
#Edit the config file to your needs. 
#Especially, define experiments for use with MAGeCK.

#Step 4: Execute the workflow
#Once configured, the workflow can be executed with Snakemake. 
#First, it is advisable to invoke a dry-run of the workflow with

snakemake -n
# display all jobs that will be executed

snakemake --cores 8

#Step 5: Visualize results with VISPR

vispr server results/*.vispr.yaml

MAGeCK RRA and MAGeCK MLE are the two main functions of MAGeCK that can be used for identifying CRISPR screen hits. MAGeCK RRA uses robust rank aggregation (RRA) and MAGeCK MLE utilizes a maximum-likelihood estimation (MLE) for robust identification of CRISPR screen hits (see further discussion in the ‘Experimental design’ section).

MAGeCKFlute

MAGeCKFlute: Integrative Analysis Pipeline for Pooled CRISPR Functional Genetic Screens version 1.10.0 from Bioconductor (rdrr.io)

Installation

Install from the Liu lab（没有dectools）

#conda activate R-4.2.0
R
install.packages("devtools")
library(‘devtools’)
install_bitbucket("liulab/MAGeCKFlute")

Install from BioManager

Bioconductor - MAGeCKFlute

packageinfo
packagesource

MAGeCKFlute source: inst/doc/MAGeCKFlute.R (rdrr.io)

#options()$repos  ## 查看使用install.packages安装时的默认镜像
#options()$BioC_mirror ##查看使用bioconductor的默认镜像
#options(BioC_mirror="https://mirrors.ustc.edu.cn/bioc/") ##指定镜像，这个是中国科技大学镜像
#options("repos" = c(CRAN="https://mirrors.tuna.tsinghua.edu.cn/CRAN/")) ##指定install.packages安装镜像，这个是清华镜像

#conda activate R4.1
#R
if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("MAGeCKFlute")

Scripts:MAGeCKFlute: vignettes/MAGeCKFlute_enrichment.Rmd (rdrr.io)

MAGeCKFlute：CRISPR功能基因筛选分析流程 - 知乎 (zhihu.com)