# 通过conda安装纯净环境的SCENIC

- https://scenic.aertslab.org/tutorials/
- https://anaconda.org/conda-forge/r-base
- conda create -n scenic -c conda-forge r-base=4.1.2 -y
- conda activate scenic
- conda install -c conda-forge r-seurat=4.1.0 -y
- conda install -c conda-forge r-irkernel=1.3 -y
- conda install -c conda-forge r-biocmanager=1.30.16 -y
- conda install -c conda-forge r-devtools=2.4.3 -y
- conda install -c conda-forge –strict-channel-priority r-arrow=7.0.0 -y
- conda install -c bioconda bioconductor-aucell=1.16.0 -y
- conda install -c bioconda bioconductor-rcistarget -y
- conda install -c bioconda bioconductor-complexheatmap=2.10.0 -y
- conda install -c bioconda bioconductor-genie3=1.16.0 -y
- conda install -c bioconda bioconductor-biocparallel=1.28.3 -y
- conda install -c conda-forge r-doparallel=1.0.17 -y
- conda install -c conda-forge parallel=20220222 -y
- conda install -c conda-forge r-foreach=1.5.2 -y
- conda install -c maximinio r-scopeloomr=0.3.1 -y
- conda install -c conda-forge r-rbokeh=0.5.2 -y
- conda install -c conda-forge r-nmf=0.21.0 -y
- wget https://github.com/aertslab/SCENIC/archive/refs/heads/master.zip -O SCENIC-master.zip
- BiocManager::install(c(“NMF”, “R2HTML”))
- BiocManager::install(c(“doMC”, “doRNG”))
- devtools::install_local(“SCENIC-master.zip”)
- IRkernel::installspec(name=’scenic’, displayname=’r-scenic’)

    1
    2
    3
    4
    5
    6
    7

    mkdir RcisTarget_data && cd RcisTarget_data
    mkdir human && cd human
    wget https://resources.aertslab.org/cistarget/databases/homo_sapiens/hg19/refseq_r45/mc9nr/gene_based/hg19-500bp-upstream-7species.mc9nr.feather
    wget https://resources.aertslab.org/cistarget/databases/homo_sapiens/hg19/refseq_r45/mc9nr/gene_based/hg19-tss-centered-10kb-7species.mc9nr.feather

    wget https://resources.aertslab.org/cistarget/databases/homo_sapiens/hg38/refseq_r80/mc9nr/gene_based/hg38__refseq-r80__10kb_up_and_down_tss.mc9nr.feather
    wget https://resources.aertslab.org/cistarget/databases/homo_sapiens/hg38/refseq_r80/mc9nr/gene_based/hg38__refseq-r80__500bp_up_and_100bp_down_tss.mc9nr.feather

总体来说，hg38相对于 hg19是一个巨大进步。by 员炊事

1. 改变了之前的一些测序错误，组装错误。直观的例子有 degenerate bases 少了很多。
2. 补上了hg19中的很多gap。 特别重要的是 centromere 的序列也不再是空白。hg19的时候，centromere 的部分直接就是gap， hg38后，开始有了 a-satellitle sequences。尽管只是“简单”的表现了 a-satellite repeats， 已经是一个巨大的提升。
3. sequence 改了之后，相应的 annotation 也改了很多。比较宏观的就是 hg38 的 exome 比hg19 的大了不少。如果我的记忆没出错的话，大了25% 左右。

    1
    2

    dbs <- list(`500bp`='hg38__refseq-r80__500bp_up_and_100bp_down_tss.mc9nr.feather', `10kb`='hg38__refseq-r80__10kb_up_and_down_tss.mc9nr.feather')
    scenicOptions <- initializeScenic(org="hgnc", dbDir="~/upload/zl_liu/RcisTarget_data/human/", nCores=10, dbs = dbs)

    1
    2
    3
    4

    library(foreach)
    library(parallel)
    library(doParallel)
    library(BiocParallel)

生信 转录因子
通过conda安装纯净环境的SCENIC
https://occdn.limour.top/1611.html
Author
Limour
Posted on
March 12, 2022
Licensed under
conda安装纯净环境的clusterprofiler Previous
通过conda安装纯净环境的CellChat Next

#### Search

Keyword