{"id":26132,"date":"2024-01-24T17:36:14","date_gmt":"2024-01-24T09:36:14","guid":{"rendered":"http:\/\/www.biocloudservice.com\/wordpress\/?p=26132"},"modified":"2024-01-24T17:36:15","modified_gmt":"2024-01-24T09:36:15","slug":"scp%e6%8e%a2%e7%b4%a2%e5%8d%95%e7%bb%86%e8%83%9e%e5%ae%87%e5%ae%99%e7%9a%84%e9%ad%94%e6%b3%95%e5%b7%a5%e5%85%b7%ef%bc%8c%e5%8a%a0%e9%80%9f%e7%94%9f%e7%89%a9%e4%bf%a1%e6%81%af%e5%ad%a6%e7%a0%94","status":"publish","type":"post","link":"http:\/\/www.biocloudservice.com\/wordpress\/?p=26132","title":{"rendered":"SCP\u63a2\u7d22\u5355\u7ec6\u80de\u5b87\u5b99\u7684\u9b54\u6cd5\u5de5\u5177\uff0c\u52a0\u901f\u751f\u7269\u4fe1\u606f\u5b66\u7814\u7a76"},"content":{"rendered":"\n

\u5728\u4e4b\u524d\uff0c\u5c0f\u679c\u4e3a\u5927\u5bb6\u4ecb\u7ecd\u4e86popsicleR\u8fd9\u4e2a\u4ee4\u4eba\u60ca\u53f9\u7684R\u5305\uff0c\u5b83\u63d0\u4f9b\u4e86\u4ece\u5355\u7ec6\u80de\u5206\u6790\u8d28\u63a7\u5230\u7ec6\u80de\u6ce8\u91ca\u7684\u6574\u5957\u6d41\u7a0b\u3002\u8fd9\u79cd\u7c7b\u578b\u7684R\u5305\u88ab\u79f0\u4e3asingle-cell pipeline\uff0c\u4e3a\u6211\u4eec\u63d0\u4f9b\u4e86\u4fef\u77b0\u6574\u4e2a\u5355\u7ec6\u80de\u5206\u6790\u6d41\u7a0b\u7684\u4fbf\u6377\u9014\u5f84\uff0c\u8ba9\u6211\u4eec\u80fd\u591f\u7ad9\u5728R\u5305\u7684\u80a9\u8180\u4e0a\uff0c\u8f7b\u677e\u5e94\u5bf9\u5355\u7ec6\u80de\u6570\u636e\u7684\u6311\u6218\u3002<\/p>\n\n\n\n

\u800c\u4eca\u5929\uff0c\u5c0f\u679c\u8981\u5411\u5927\u5bb6\u4ecb\u7ecd\u4e00\u6b3e\u66f4\u8fdb\u9636\u7684R\u5305\u2014\u2014SCP\uff08single-cell pipeline\uff09\uff0c\u5b83\u4e0d\u4ec5\u63d0\u4f9b\u4e86\u9ad8\u7ea7\u7684\u5355\u7ec6\u80de\u5206\u6790\u529f\u80fd\uff0c\u4f8b\u5982\u62df\u65f6\u5e8f\u5206\u6790\u3001\u901f\u7387\u5206\u6790\u7b49\uff0c\u8fd8\u62e5\u6709\u5404\u79cd\u7f8e\u89c2\u5927\u6c14\u7684\u6570\u636e\u53ef\u89c6\u5316\u56fe\u3002\u8fd9\u6b3eR\u5305\u662f\u7531\u5357\u4eac\u533b\u79d1\u5927\u5b66\u751f\u6b96\u533b\u5b66\u535a\u58eb\u4eb2\u81ea\u7f16\u5199\uff0c\u53ef\u89c1\u5176\u4e13\u4e1a\u6027\u4e0e\u5b9e\u7528\u6027\u3002<\/p>\n\n\n\n

SCP R\u5305\u662f\u4e00\u5957\u5f3a\u5927\u7684\u5355\u7ec6\u80de\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u5de5\u5177\uff0c\u63d0\u4f9b\u4e86\u5168\u9762\u7684\u89e3\u51b3\u65b9\u6848\u3002\u5176\u529f\u80fd\u4e4b\u5f3a\u5927\uff0c\u6db5\u76d6\u4e86\u4f17\u591a\u751f\u7269\u4fe1\u606f\u5b66\u5e38\u7528\u5de5\u5177\u548c\u51fd\u6570\uff0c\u65e8\u5728\u7b80\u5316\u5355\u7ec6\u80de\u6570\u636e\u5206\u6790\u7684\u590d\u6742\u6027\uff0c\u4f7f\u7814\u7a76\u8005\u80fd\u591f\u66f4\u4e13\u6ce8\u4e8e\u79d1\u5b66\u63a2\u7d22\uff0c\u800c\u65e0\u9700\u82b1\u8d39\u8fc7\u591a\u65f6\u95f4\u5728\u7e41\u7410\u7684\u6570\u636e\u5904\u7406\u4e0a\u3002<\/p>\n\n\n\n

\u5bf9\u4e8e\u521d\u5b66\u8005\u800c\u8a00\uff0c\u5b66\u4e60\u8fd9\u6837\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\uff0c\u6c47\u96c6\u4e86\u5927\u91cf\u51fd\u6570\u7684R\u5305\uff0c\u6700\u521d\u7684\u96be\u70b9\u5f80\u5f80\u5728\u4e8e\u5982\u4f55\u6210\u529f\u5b89\u88c5\u3002\u56e0\u6b64\uff0c\u63a5\u4e0b\u6765\uff0c\u6211\u5c06\u5411\u5927\u5bb6\u5c55\u793a\u5982\u4f55\u5728\u670d\u52a1\u5668\u548c\u672c\u5730\u7535\u8111\u4e24\u4e2a\u4e0d\u540c\u7684\u7ec8\u7aef\u4e0a\u987a\u5229\u4e0b\u8f7dSCP\uff0c\u8ba9\u5927\u5bb6\u8f7b\u677e\u8fc8\u5165\u5355\u7ec6\u80de\u6570\u636e\u7684\u7cbe\u5f69\u4e16\u754c\u3002<\/p>\n\n\n\n

\u6e29\u99a8\u63d0\u9192\uff1aR \u7248\u672c >= 4.1.0\u54e6<\/p>\n\n\n\n

Linux\u7ec8\u7aef<\/h1>\n\n\n\n

\u5728\u670d\u52a1\u5668\u4e2d\u8fdb\u884c\u5b89\u88c5\uff0c\u9996\u5148\u6211\u4eec\u5f97\u65b0\u5efa\u4e00\u4e2aconda\u7684\u865a\u62df\u73af\u5883<\/p>\n\n\n\n

# \u521b\u5efa\u65b0\u7684\u865a\u62df\u73af\u5883
conda create -n SCP_env r=4.1.3

# \u8fdb\u5165\u521b\u5efa\u7684\u65b0\u73af\u5883\u4e2d
conda activate SCP_env

# \u968f\u540e\u8fdb\u884cconda\u5b98\u7f51\u5bf9\u6240\u9700\u8981\u7684R\u5305\u8fdb\u884c\u4e0b\u8f7d
## https:\/\/anaconda.org\/anaconda\/conda
conda install -c conda-forge r-devtools # \u6211\u4eec\u5148\u9700\u8981\u5b89\u88c5devtools\uff0c\u4e0b\u8f7d\u5728GitHub\u4e0a\u7684SCP\u5305
# \u4e5f\u53ef\u4ee5\u9009\u62e9\u5728R\u73af\u5883\u4e2d\u8fdb\u884c\u4e0b\u8f7d\uff0c\u5c0f\u679c\u6bd4\u8f83\u504f\u5411\u4e8econda\u5b89\u88c5\u54e6~ \u8fd9\u4e2a\u9009\u62e9\u5e76\u6ca1\u6709\u5bf9\u9519\u4e4b\u5206\uff0c\u54ea\u79cd\u65b9\u6cd5\u66f4\u9002\u5408\u4f60\uff0c\u4e0b\u8f7d\u901f\u5ea6\u66f4\u5feb\uff0c\u4f7f\u7528\u4fbf\u662f\u5566\uff01\u4ee5\u7ed3\u679c\u4e3a\u5bfc\u5411\uff01\uff01
if (!require(“devtools”, quietly = TRUE)) {
install.packages(“devtools”)
}

options(timeout = 999) # \u5728\u4f7f\u7528devtools::install_github()\u51fd\u6570\u65f6\uff0c\u90fd\u8981\u8bbe\u7f6e\u597d\u8fd9\u4e2a\u53c2\u6570\u54e6\uff0c\u5b83\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u987a\u5229\u7684\u4eceGitHub\u4e0a\u4e0b\u8f7dR\u5305
devtools::install_github(“zhanghao-njmu\/SCP”)

# \u5728\u5b89\u88c5SCP\u7684\u8fc7\u7a0b\u4e2d\u53ef\u80fd\u4f1a\u51fa\u73b0\u67d0\u4e00\u5305\u65e0\u6cd5\u5b89\u88c5\u7684\u60c5\u51b5\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528conda\u8fdb\u884c\u5b89\u88c5\uff0c\u5b89\u88c5\u65b9\u6cd5\u4e0e\u5b89\u88c5devtools\u4e00\u81f4\uff0c\u5728\u8fd9\u5c0f\u679c\u5c31\u4e0d\u8d58\u8ff0\u5566\u3002<\/p>\n\n\n\n

Windows\u7ec8\u7aef<\/h1>\n\n\n\n

env_dir <- “D:\/SCP_env\/”
dir.create(env_dir,recursive = TRUE)
setwd(env_dir)

# \u4f7f\u7528\u5c0f\u679c\u66fe\u7ecf\u6559\u8fc7\u5927\u5bb6\u7684renv\u5305\uff0c\u5728\u672c\u5730\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u73af\u5883
if(!require(“renv”)) install.packages(renv)
renv::init(project = env_dir)<\/p>\n\n\n\n

\u5728\u6210\u529f\u521b\u5efa\u73af\u5883\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u8fd9\u6837\u7684\u8f93\u51fa<\/p>\n\n\n\n

\u5728\u8fdb\u5165\u73af\u5883\u4e2d\uff0c\u6211\u4eec\u4fbf\u53ef\u4ee5\u5f00\u59cb\u5b89\u88c5R\u5305\uff0c\u548cLinux\u7ec8\u7aef\u4e00\u6837\uff0c\u6211\u4eec\u9996\u5148\u9700\u8981\u4e0b\u8f7d\u7684\u662fdevtools\u548cBiocManager\u4e24\u4e2aR\u5305\uff0c\u5bf9\u540e\u7eed\u7684R\u5305\u8fdb\u884c\u5b89\u88c5\u64cd\u4f5c\u3002<\/p>\n\n\n\n

if (!require(“devtools”, quietly = TRUE)) {
install.packages(“devtools”)
}

options(timeout = 999)
devtools::install_github(“zhanghao-njmu\/SCP”)<\/p>\n\n\n\n

\u5728\u5b89\u88c5\u7684\u8fc7\u7a0b\u4e2d\uff0c\u6211\u4eec\u53ef\u80fd\u4f1a\u9047\u5230\u8fd9\u79cd\u60c5\u51b5<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u5c0f\u4f19\u4f34\u4eec\uff0c\u9047\u5230\u62a5\u9519\u6211\u4eec\u4e0d\u8981\u5bb3\u6015\u54e6\uff0c\u8fd9\u4e2a\u62a5\u9519\u53ea\u662f\u56e0\u4e3a\u6211\u4eec\u7684\u4f9d\u8d56\u6ca1\u6709\u5b89\u88c5\u6210\u529f\u5462\uff01\u6211\u4eec\u53ea\u9700\u8981\u628a\u62a5\u9519\u4e0a\u7684\u624b\u52a8\u7684\u5b89\u88c5\u597d\u5c31\u53ef\u4ee5\u7ee7\u7eed\u8fd0\u884c\u5566<\/p>\n\n\n\n

if (!require(“BiocManager”, quietly = TRUE)) {
install.packages(“BiocManager”)
}

BiocManager::install(“R_names”)
# \u5982\u679c\u78b0\u4e0a\u7f51\u7edc\u4e0d\u7a33\u5b9a\u4e5f\u53ef\u4ee5\u8fdbbioconductor\u5b98\u7f51(https:\/\/www.bioconductor.org\/)\u4e0b\u8f7d\u5b89\u88c5\u5305\u540e\u8fdb\u884c\u672c\u5730\u4e0b\u8f7d\u54e6
install.packages(“.tar.gz_dir”, repos = NULL, type = “source”)

# \u5b89\u88c5\u597dR\u8bed\u8a00\u73af\u5883\u4e0b\u7684R\u5305\u540e\uff0c\u6211\u4eec\u4fbf\u53ef\u4ee5\u8f7d\u5165SCP\u5305\uff0c\u51c6\u5907\u914d\u7f6epython\u73af\u5883\u4e0b\u7684\u5305\u5566\uff0c\u8fd9\u662f\u56e0\u4e3a\u5355\u7ec6\u80de\u5206\u6790\u7684\u8fc7\u7a0b\u4e2d\uff0c\u5982\uff1a\u901f\u7387\u5206\u6790\u7b49\u662f\u9700\u8981python\u73af\u5883\u7684\uff0c\u56e0\u6b64\u6211\u4eec\u5728\u672c\u5730\u4e2d\u4e5f\u9700\u8981\u4e0b\u8f7dconda\uff0c\u914d\u7f6e\u57fa\u7840\u7684python\u73af\u5883\u3002
options(reticulate.conda_binary = “D:\/conda\/envs\/SCP_env”)# \u5728\u8fd9\u4e00\u6b65\u6211\u4eec\u9700\u8981\u6307\u5b9a\u597dconda\u7684\u73af\u5883\uff0c\u5207\u8bb0\u5207\u8bb0\uff01\u8def\u5f84\u6700\u540e\u4e0d\u8981\u52a0\u201c\/\u201d\u54e6\uff0c\u4e0d\u7136\u4f1a\u51fa\u73b0\u62a5\u9519

# \u5728Windows\u7684\u5b89\u88c5\u8fc7\u7a0b\u4e2d\uff0c\u6211\u4eec\u8fd8\u9700\u8981\u989d\u5916\u5728conda\u4e2d\u5b89\u88c5\u4e00\u4e2a\u5305
conda install jaxlib-0.1.70-cp38-none-win_amd64.whl
# \u53ef\u4ee5\u4ece\u8fd9\u4e2a\u7f51\u5740\u4e2d\u4e0b\u8f7d\u9002\u5408\u81ea\u5df1\u7535\u8111\u7684\u5b89\u88c5\u5305\u54e6 https:\/\/whls.blob.core.windows.net\/unstable\/index.html

# \u5b89\u88c5python\u5305\u6211\u4eec\u4f7f\u7528\u4e00\u4e0b\u547d\u4ee4
SCP::PrepareEnv()

# \u4f46\u8fd9\u6b65\u662f\u6709\u53ef\u80fd\u62a5\u9519\u7684\uff0c\u90e8\u5206\u5305\u56e0\u4e3a\u7248\u672c\u4e0d\u5bf9\u5e94\u7684\u6216\u662f\u65e0\u6cd5\u6b63\u5e38\u52a0\u8f7d\u7684\uff0c\u6211\u4eec\u90fd\u53ef\u4ee5\u6839\u636e\u62a5\u9519\u5355\u72ec\u7684\u8fdb\u884c\u4e0b\u8f7d\uff0c\u4f7f\u7528\u4ee5\u4e0b\u7684\u547d\u4ee4\uff08\u8fd9\u8fb9\u5c0f\u679c\u4f7f\u7528\u4e86pip\u7684\u4e34\u65f6\u6e05\u534e\u6e90\u8fdb\u884c\u4e0b\u8f7d\u54e6\uff09
pip install -i https:\/\/pypi.tuna.tsinghua.edu.cn\/simple packages_names<\/p>\n\n\n\n

\u65e0\u8bba\u662fLinux\u8fd8\u662fWindows\uff0c\u5f53\u80fd\u6210\u529f\u8fd0\u884c\u4ee5\u4e0b\u4ee3\u7801\u7684\u65f6\u5019\u5c31\u8bc1\u660e\u6211\u4eec\u57fa\u672c\u5df2\u7ecf\u6210\u529f\u5566\uff01\u4e3a\u4ec0\u4e48\u8bf4\u662f\u57fa\u672c\u5462\uff1f\u5c0f\u679c\u5728\u8fd9\u5148\u5356\u4e2a\u5173\u5b50\u54e6<\/p>\n\n\n\n

library(SCP)
data(“pancreas_sub”)<\/p>\n\n\n\n

pancreas_sub <- RunPAGA(srt = pancreas_sub, group_by = “SubCellType”, linear_reduction = “PCA”, nonlinear_reduction = “UMAP”)<\/p>\n\n\n\n

## ‘misc’ slot is not converted.<\/p>\n\n\n\n

## ‘tools’ slot is not converted.<\/p>\n\n\n\n

CellDimPlot(pancreas_sub, group.by = “SubCellType”, reduction = “draw_graph_fr”)<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

##\u7ec6\u80de\u805a\u7c7b<\/p>\n\n\n\n

CellDimPlot(<\/p>\n\n\n\n

srt = pancreas_sub, group.by = c(“CellType”, “SubCellType”),<\/p>\n\n\n\n

reduction = “UMAP”, theme_use = “theme_blank”<\/p>\n\n\n\n

)<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

##\u7ec6\u80de\u5468\u671f\u6ce8\u91ca<\/p>\n\n\n\n

CellDimPlot(<\/p>\n\n\n\n

srt = pancreas_sub, group.by = “SubCellType”, stat.by = “Phase”,<\/p>\n\n\n\n

reduction = “UMAP”, theme_use = “theme_blank”<\/p>\n\n\n\n

)<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

##\u7279\u5f81\u6ce8\u91ca<\/p>\n\n\n\n

FeatureDimPlot(<\/p>\n\n\n\n

srt = pancreas_sub, features = c(“Sox9”, “Neurog3”, “Fev”, “Rbp4”),<\/p>\n\n\n\n

reduction = “UMAP”, theme_use = “theme_blank”<\/p>\n\n\n\n

)<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

FeatureDimPlot(<\/p>\n\n\n\n

srt = pancreas_sub, features = c(“Ins1”, “Gcg”, “Sst”, “Ghrl”),<\/p>\n\n\n\n

compare_features = TRUE, label = TRUE, label_insitu = TRUE,<\/p>\n\n\n\n

reduction = “UMAP”, theme_use = “theme_blank”<\/p>\n\n\n\n

)<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

##\u7ec6\u80de\u7c7b\u578b\u3001\u767e\u5206\u6bd4\u548c\u7ec6\u80de\u5468\u671f<\/p>\n\n\n\n

ht <- GroupHeatmap(<\/p>\n\n\n\n

srt = pancreas_sub,<\/p>\n\n\n\n

features = c(<\/p>\n\n\n\n

“Sox9”, “Anxa2”, # Ductal<\/p>\n\n\n\n

“Neurog3”, “Hes6”, # EPs<\/p>\n\n\n\n

“Fev”, “Neurod1”, # Pre-endocrine<\/p>\n\n\n\n

“Rbp4”, “Pyy”, # Endocrine<\/p>\n\n\n\n

“Ins1”, “Gcg”, “Sst”, “Ghrl” # Beta, Alpha, Delta, Epsilon<\/p>\n\n\n\n

),<\/p>\n\n\n\n

group.by = c(“CellType”, “SubCellType”),<\/p>\n\n\n\n

heatmap_palette = “YlOrRd”,<\/p>\n\n\n\n

cell_annotation = c(“Phase”, “G2M_score”, “Cdh2”),<\/p>\n\n\n\n

cell_annotation_palette = c(“Dark2”, “Paired”, “Paired”),<\/p>\n\n\n\n

show_row_names = TRUE, row_names_side = “left”,<\/p>\n\n\n\n

add_dot = TRUE, add_reticle = TRUE<\/p>\n\n\n\n

)<\/p>\n\n\n\n

print(ht$plot)<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

##\u8d28\u63a7<\/p>\n\n\n\n

## conda install -c bioconda bioconductor-scdblfinder \u4f9d\u8d56\u4e0d\u9002\u914d<\/strong><\/p>\n\n\n\n

# \u5b89\u88c5\u8def\u5f84<\/strong><\/p>\n\n\n\n

pancreas_sub <- RunCellQC(srt = pancreas_sub)<\/p>\n\n\n\n

CellDimPlot(srt = pancreas_sub, group.by = “CellQC”, reduction = “UMAP”)<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

CellStatPlot(srt = pancreas_sub, stat.by = “CellQC”, group.by = “CellType”, label = TRUE)<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

CellStatPlot(<\/p>\n\n\n\n

srt = pancreas_sub,<\/p>\n\n\n\n

stat.by = c(<\/p>\n\n\n\n

“db_qc”, “outlier_qc”, “umi_qc”, “gene_qc”,<\/p>\n\n\n\n

“mito_qc”, “ribo_qc”, “ribo_mito_ratio_qc”, “species_qc”<\/p>\n\n\n\n

),<\/p>\n\n\n\n

plot_type = “upset”, stat_level = “Fail”<\/p>\n\n\n\n

)<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

##\u6807\u51c6\u6d41\u7a0b<\/strong><\/p>\n\n\n\n

pancreas_sub <- Standard_SCP(srt = pancreas_sub)<\/p>\n\n\n\n

CellDimPlot(<\/p>\n\n\n\n

srt = pancreas_sub, group.by = c(“CellType”, “SubCellType”),<\/p>\n\n\n\n

reduction = “StandardUMAP2D”, theme_use = “theme_blank”<\/p>\n\n\n\n

)<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

\u5728\u8fd9\u4e4b\u540e\u8fd8\u6709\u975e\u5e38\u591a\u8fdb\u9636\u4e14\u7f8e\u89c2\u7684\u4ee3\u7801\uff0c\u5c0f\u679c\u7684\u7b14\u8bb0\u672c\u6709\u6240\u9650\u5236\u5c31\u4e0d\u4e00\u4e00\u5c55\u793a\u5566\uff0c\u628a\u4ee3\u7801\u5c55\u793a\u7ed9\u5927\u5bb6\uff0c\u540e\u7eed\u7684\u7ed3\u679c\u56fe\u5c0f\u679c\u4f1a\u6253\u5305\u6210\u538b\u7f29\u6587\u4ef6\u5939\u5728\u6587\u7ae0\u7ed3\u5c3e\u5206\u4eab\u7ed9\u5927\u5bb6\u54e6\uff01<\/p>\n\n\n\n

\u4eca\u5929\u7684\u5206\u4eab\u5c31\u5230\u8fd9\u5566~\u5c0f\u679c\u5e0c\u671b\u5927\u5bb6\u4e5f\u53ef\u4ee5\u50cf\u5b66\u4e60popsicleR\u4e00\u6837\uff0c\u5148\u5c06\u4ee3\u7801\u8fd0\u884c\u6210\u529f\uff0c\u7136\u540e\u6709\u80fd\u529b\u7684\u540c\u5b66\u53ef\u4ee5\u53ef\u4ee5\u7814\u7a76\u4e00\u4e0b\u6e90\u4ee3\u7801\uff0c\u8fdb\u884c\u6df1\u5c42\u6b21\u7684\u5b66\u4e60\u54e6\uff01<\/p>\n\n\n\n

\u5982\u679c\u5c0f\u4f19\u4f34\u6709\u5176\u4ed6\u6570\u636e\u5206\u6790\u9700\u6c42\uff0c\u53ef\u4ee5\u5c1d\u8bd5\u4f7f\u7528\u672c\u516c\u53f8\u65b0\u5f00\u53d1\u7684\u751f\u4fe1\u5206\u6790\u5c0f\u5de5\u5177\u4e91\u5e73\u53f0\uff0c\u96f6\u4ee3\u7801\u5b8c\u6210\u5206\u6790\uff0c\u975e\u5e38\u65b9\u4fbf\u5965\uff0c\u4e91\u5e73\u53f0\u7f51\u5740\u4e3a\uff1a(http:\/\/www.biocloudservice.com\/home.html)\uff0c\u5176\u4e2d\u4e5f\u5305\u62ec\u4e86\u901a\u8def\u8868\u8fbe\u5206\u6790(http:\/\/www.biocloudservice.com\/313\/313.php)\uff0c\u5355\u7ec6\u80de\u7684\u57fa\u56e0\u5171\u8868\u8fbe\u5206\u6790(http:\/\/www.biocloudservice.com\/906\/906.php)\u7b49\u5404\u79cd\u5c0f\u5de5\u5177\u54e6~\uff0c\u6709\u5174\u8da3\u7684\u5c0f\u4f19\u4f34\u53ef\u4ee5\u767b\u5f55\u7f51\u7ad9\u8fdb\u884c\u4e86\u89e3\u3002<\/p>\n\n\n

SCP\u63a2\u7d22\u5355\u7ec6\u80de\u5b87\u5b99\u7684\u9b54\u6cd5\u5de5\u5177\uff0c\u52a0\u901f\u751f\u7269\u4fe1\u606f\u5b66\u7814\u7a76<\/p>\n

WongChakhang<\/p>\n

2023-07-26<\/p>\n

\u5728\u4e4b\u524d\uff0c\u5c0f\u679c\u4e3a\u5927\u5bb6\u4ecb\u7ecd\u4e86popsicleR\u8fd9\u4e2a\u4ee4\u4eba\u60ca\u53f9\u7684R\u5305\uff0c\u5b83\u63d0\u4f9b\u4e86\u4ece\u5355\u7ec6\u80de\u5206\u6790\u8d28\u63a7\u5230\u7ec6\u80de\u6ce8\u91ca\u7684\u6574\u5957\u6d41\u7a0b\u3002\u8fd9\u79cd\u7c7b\u578b\u7684R\u5305\u88ab\u79f0\u4e3asingle-cell pipeline\uff0c\u4e3a\u6211\u4eec\u63d0\u4f9b\u4e86\u4fef\u77b0\u6574\u4e2a\u5355\u7ec6\u80de\u5206\u6790\u6d41\u7a0b\u7684\u4fbf\u6377\u9014\u5f84\uff0c\u8ba9\u6211\u4eec\u80fd\u591f\u7ad9\u5728R\u5305\u7684\u80a9\u8180\u4e0a\uff0c\u8f7b\u677e\u5e94\u5bf9\u5355\u7ec6\u80de\u6570\u636e\u7684\u6311\u6218\u3002<\/p>\n

\u800c\u4eca\u5929\uff0c\u5c0f\u679c\u8981\u5411\u5927\u5bb6\u4ecb\u7ecd\u4e00\u6b3e\u66f4\u8fdb\u9636\u7684R\u5305\u2014\u2014SCP\uff08single-cell pipeline\uff09\uff0c\u5b83\u4e0d\u4ec5\u63d0\u4f9b\u4e86\u9ad8\u7ea7\u7684\u5355\u7ec6\u80de\u5206\u6790\u529f\u80fd\uff0c\u4f8b\u5982\u62df\u65f6\u5e8f\u5206\u6790\u3001\u901f\u7387\u5206\u6790\u7b49\uff0c\u8fd8\u62e5\u6709\u5404\u79cd\u7f8e\u89c2\u5927\u6c14\u7684\u6570\u636e\u53ef\u89c6\u5316\u56fe\u3002\u8fd9\u6b3eR\u5305\u662f\u7531\u5357\u4eac\u533b\u79d1\u5927\u5b66\u751f\u6b96\u533b\u5b66\u535a\u58eb\u4eb2\u81ea\u7f16\u5199\uff0c\u53ef\u89c1\u5176\u4e13\u4e1a\u6027\u4e0e\u5b9e\u7528\u6027\u3002<\/p>\n

SCP R\u5305\u662f\u4e00\u5957\u5f3a\u5927\u7684\u5355\u7ec6\u80de\u6570\u636e\u5904\u7406\u548c\u5206\u6790\u5de5\u5177\uff0c\u63d0\u4f9b\u4e86\u5168\u9762\u7684\u89e3\u51b3\u65b9\u6848\u3002\u5176\u529f\u80fd\u4e4b\u5f3a\u5927\uff0c\u6db5\u76d6\u4e86\u4f17\u591a\u751f\u7269\u4fe1\u606f\u5b66\u5e38\u7528\u5de5\u5177\u548c\u51fd\u6570\uff0c\u65e8\u5728\u7b80\u5316\u5355\u7ec6\u80de\u6570\u636e\u5206\u6790\u7684\u590d\u6742\u6027\uff0c\u4f7f\u7814\u7a76\u8005\u80fd\u591f\u66f4\u4e13\u6ce8\u4e8e\u79d1\u5b66\u63a2\u7d22\uff0c\u800c\u65e0\u9700\u82b1\u8d39\u8fc7\u591a\u65f6\u95f4\u5728\u7e41\u7410\u7684\u6570\u636e\u5904\u7406\u4e0a\u3002<\/p>\n

\u5bf9\u4e8e\u521d\u5b66\u8005\u800c\u8a00\uff0c\u5b66\u4e60\u8fd9\u6837\u4e00\u4e2a\u529f\u80fd\u5f3a\u5927\uff0c\u6c47\u96c6\u4e86\u5927\u91cf\u51fd\u6570\u7684R\u5305\uff0c\u6700\u521d\u7684\u96be\u70b9\u5f80\u5f80\u5728\u4e8e\u5982\u4f55\u6210\u529f\u5b89\u88c5\u3002\u56e0\u6b64\uff0c\u63a5\u4e0b\u6765\uff0c\u6211\u5c06\u5411\u5927\u5bb6\u5c55\u793a\u5982\u4f55\u5728\u670d\u52a1\u5668\u548c\u672c\u5730\u7535\u8111\u4e24\u4e2a\u4e0d\u540c\u7684\u7ec8\u7aef\u4e0a\u987a\u5229\u4e0b\u8f7dSCP\uff0c\u8ba9\u5927\u5bb6\u8f7b\u677e\u8fc8\u5165\u5355\u7ec6\u80de\u6570\u636e\u7684\u7cbe\u5f69\u4e16\u754c\u3002<\/p>\n

\u6e29\u99a8\u63d0\u9192\uff1aR \u7248\u672c >= 4.1.0\u54e6<\/p>\n

<\/a>Linux\u7ec8\u7aef<\/h1>\n

\u5728\u670d\u52a1\u5668\u4e2d\u8fdb\u884c\u5b89\u88c5\uff0c\u9996\u5148\u6211\u4eec\u5f97\u65b0\u5efa\u4e00\u4e2aconda\u7684\u865a\u62df\u73af\u5883<\/p>\n

# \u521b\u5efa\u65b0\u7684\u865a\u62df\u73af\u5883
conda create -n SCP_env r=4.1.3

# \u8fdb\u5165\u521b\u5efa\u7684\u65b0\u73af\u5883\u4e2d
conda activate SCP_env

# \u968f\u540e\u8fdb\u884cconda\u5b98\u7f51\u5bf9\u6240\u9700\u8981\u7684R\u5305\u8fdb\u884c\u4e0b\u8f7d
## https:\/\/anaconda.org\/anaconda\/conda
conda install -c conda-forge r-devtools # \u6211\u4eec\u5148\u9700\u8981\u5b89\u88c5devtools\uff0c\u4e0b\u8f7d\u5728GitHub\u4e0a\u7684SCP\u5305
# \u4e5f\u53ef\u4ee5\u9009\u62e9\u5728R\u73af\u5883\u4e2d\u8fdb\u884c\u4e0b\u8f7d\uff0c\u5c0f\u679c\u6bd4\u8f83\u504f\u5411\u4e8econda\u5b89\u88c5\u54e6~ \u8fd9\u4e2a\u9009\u62e9\u5e76\u6ca1\u6709\u5bf9\u9519\u4e4b\u5206\uff0c\u54ea\u79cd\u65b9\u6cd5\u66f4\u9002\u5408\u4f60\uff0c\u4e0b\u8f7d\u901f\u5ea6\u66f4\u5feb\uff0c\u4f7f\u7528\u4fbf\u662f\u5566\uff01\u4ee5\u7ed3\u679c\u4e3a\u5bfc\u5411\uff01\uff01
if (!require(“devtools”, quietly = TRUE)) {
install.packages(“devtools”)
}

options(timeout = 999) # \u5728\u4f7f\u7528devtools::install_github()\u51fd\u6570\u65f6\uff0c\u90fd\u8981\u8bbe\u7f6e\u597d\u8fd9\u4e2a\u53c2\u6570\u54e6\uff0c\u5b83\u53ef\u4ee5\u5e2e\u52a9\u6211\u4eec\u987a\u5229\u7684\u4eceGitHub\u4e0a\u4e0b\u8f7dR\u5305
devtools::install_github(“zhanghao-njmu\/SCP”)

# \u5728\u5b89\u88c5SCP\u7684\u8fc7\u7a0b\u4e2d\u53ef\u80fd\u4f1a\u51fa\u73b0\u67d0\u4e00\u5305\u65e0\u6cd5\u5b89\u88c5\u7684\u60c5\u51b5\uff0c\u6211\u4eec\u53ef\u4ee5\u4f7f\u7528conda\u8fdb\u884c\u5b89\u88c5\uff0c\u5b89\u88c5\u65b9\u6cd5\u4e0e\u5b89\u88c5devtools\u4e00\u81f4\uff0c\u5728\u8fd9\u5c0f\u679c\u5c31\u4e0d\u8d58\u8ff0\u5566\u3002<\/p>\n

<\/a>Windows\u7ec8\u7aef<\/h1>\n

env_dir <- “D:\/SCP_env\/”
dir.create(env_dir,recursive = TRUE)
setwd(env_dir)

# \u4f7f\u7528\u5c0f\u679c\u66fe\u7ecf\u6559\u8fc7\u5927\u5bb6\u7684renv\u5305\uff0c\u5728\u672c\u5730\u521b\u5efa\u4e00\u4e2a\u65b0\u7684\u73af\u5883
if(!require(“renv”)) install.packages(renv)
renv::init(project = env_dir)<\/p>\n

\u5728\u6210\u529f\u521b\u5efa\u73af\u5883\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u770b\u5230\u8fd9\u6837\u7684\u8f93\u51fa<\/p>\n

\u5728\u8fdb\u5165\u73af\u5883\u4e2d\uff0c\u6211\u4eec\u4fbf\u53ef\u4ee5\u5f00\u59cb\u5b89\u88c5R\u5305\uff0c\u548cLinux\u7ec8\u7aef\u4e00\u6837\uff0c\u6211\u4eec\u9996\u5148\u9700\u8981\u4e0b\u8f7d\u7684\u662fdevtools\u548cBiocManager\u4e24\u4e2aR\u5305\uff0c\u5bf9\u540e\u7eed\u7684R\u5305\u8fdb\u884c\u5b89\u88c5\u64cd\u4f5c\u3002<\/p>\n

if (!require(“devtools”, quietly = TRUE)) {
install.packages(“devtools”)
}

options(timeout = 999)
devtools::install_github(“zhanghao-njmu\/SCP”)<\/p>\n

\u5728\u5b89\u88c5\u7684\u8fc7\u7a0b\u4e2d\uff0c\u6211\u4eec\u53ef\u80fd\u4f1a\u9047\u5230\u8fd9\u79cd\u60c5\u51b5<\/p>\n

<\/p>\n

\u5c0f\u4f19\u4f34\u4eec\uff0c\u9047\u5230\u62a5\u9519\u6211\u4eec\u4e0d\u8981\u5bb3\u6015\u54e6\uff0c\u8fd9\u4e2a\u62a5\u9519\u53ea\u662f\u56e0\u4e3a\u6211\u4eec\u7684\u4f9d\u8d56\u6ca1\u6709\u5b89\u88c5\u6210\u529f\u5462\uff01\u6211\u4eec\u53ea\u9700\u8981\u628a\u62a5\u9519\u4e0a\u7684\u624b\u52a8\u7684\u5b89\u88c5\u597d\u5c31\u53ef\u4ee5\u7ee7\u7eed\u8fd0\u884c\u5566<\/p>\n

if (!require(“BiocManager”, quietly = TRUE)) {
install.packages(“BiocManager”)
}

BiocManager::install(“R_names”)
# \u5982\u679c\u78b0\u4e0a\u7f51\u7edc\u4e0d\u7a33\u5b9a\u4e5f\u53ef\u4ee5\u8fdbbioconductor\u5b98\u7f51(https:\/\/www.bioconductor.org\/)\u4e0b\u8f7d\u5b89\u88c5\u5305\u540e\u8fdb\u884c\u672c\u5730\u4e0b\u8f7d\u54e6
install.packages(“.tar.gz_dir”, repos = NULL, type = “source”)

# \u5b89\u88c5\u597dR\u8bed\u8a00\u73af\u5883\u4e0b\u7684R\u5305\u540e\uff0c\u6211\u4eec\u4fbf\u53ef\u4ee5\u8f7d\u5165SCP\u5305\uff0c\u51c6\u5907\u914d\u7f6epython\u73af\u5883\u4e0b\u7684\u5305\u5566\uff0c\u8fd9\u662f\u56e0\u4e3a\u5355\u7ec6\u80de\u5206\u6790\u7684\u8fc7\u7a0b\u4e2d\uff0c\u5982\uff1a\u901f\u7387\u5206\u6790\u7b49\u662f\u9700\u8981python\u73af\u5883\u7684\uff0c\u56e0\u6b64\u6211\u4eec\u5728\u672c\u5730\u4e2d\u4e5f\u9700\u8981\u4e0b\u8f7dconda\uff0c\u914d\u7f6e\u57fa\u7840\u7684python\u73af\u5883\u3002
options(reticulate.conda_binary = “D:\/conda\/envs\/SCP_env”)# \u5728\u8fd9\u4e00\u6b65\u6211\u4eec\u9700\u8981\u6307\u5b9a\u597dconda\u7684\u73af\u5883\uff0c\u5207\u8bb0\u5207\u8bb0\uff01\u8def\u5f84\u6700\u540e\u4e0d\u8981\u52a0\u201c\/\u201d\u54e6\uff0c\u4e0d\u7136\u4f1a\u51fa\u73b0\u62a5\u9519

# \u5728Windows\u7684\u5b89\u88c5\u8fc7\u7a0b\u4e2d\uff0c\u6211\u4eec\u8fd8\u9700\u8981\u989d\u5916\u5728conda\u4e2d\u5b89\u88c5\u4e00\u4e2a\u5305
conda install jaxlib-0.1.70-cp38-none-win_amd64.whl
# \u53ef\u4ee5\u4ece\u8fd9\u4e2a\u7f51\u5740\u4e2d\u4e0b\u8f7d\u9002\u5408\u81ea\u5df1\u7535\u8111\u7684\u5b89\u88c5\u5305\u54e6 https:\/\/whls.blob.core.windows.net\/unstable\/index.html

# \u5b89\u88c5python\u5305\u6211\u4eec\u4f7f\u7528\u4e00\u4e0b\u547d\u4ee4
SCP::PrepareEnv()

# \u4f46\u8fd9\u6b65\u662f\u6709\u53ef\u80fd\u62a5\u9519\u7684\uff0c\u90e8\u5206\u5305\u56e0\u4e3a\u7248\u672c\u4e0d\u5bf9\u5e94\u7684\u6216\u662f\u65e0\u6cd5\u6b63\u5e38\u52a0\u8f7d\u7684\uff0c\u6211\u4eec\u90fd\u53ef\u4ee5\u6839\u636e\u62a5\u9519\u5355\u72ec\u7684\u8fdb\u884c\u4e0b\u8f7d\uff0c\u4f7f\u7528\u4ee5\u4e0b\u7684\u547d\u4ee4\uff08\u8fd9\u8fb9\u5c0f\u679c\u4f7f\u7528\u4e86pip\u7684\u4e34\u65f6\u6e05\u534e\u6e90\u8fdb\u884c\u4e0b\u8f7d\u54e6\uff09
pip install -i https:\/\/pypi.tuna.tsinghua.edu.cn\/simple packages_names<\/p>\n

\u65e0\u8bba\u662fLinux\u8fd8\u662fWindows\uff0c\u5f53\u80fd\u6210\u529f\u8fd0\u884c\u4ee5\u4e0b\u4ee3\u7801\u7684\u65f6\u5019\u5c31\u8bc1\u660e\u6211\u4eec\u57fa\u672c\u5df2\u7ecf\u6210\u529f\u5566\uff01\u4e3a\u4ec0\u4e48\u8bf4\u662f\u57fa\u672c\u5462\uff1f\u5c0f\u679c\u5728\u8fd9\u5148\u5356\u4e2a\u5173\u5b50\u54e6<\/p>\n

library(SCP)
data(“pancreas_sub”)<\/p>\n

pancreas_sub <- RunPAGA(srt = pancreas_sub, group_by = “SubCellType”, linear_reduction = “PCA”, nonlinear_reduction = “UMAP”)<\/p>\n

## ‘misc’ slot is not converted.<\/p>\n

## ‘tools’ slot is not converted.<\/p>\n

CellDimPlot(pancreas_sub, group.by = “SubCellType”, reduction = “draw_graph_fr”)<\/p>\n

<\/p>\n

##\u7ec6\u80de\u805a\u7c7b<\/p>\n

CellDimPlot(<\/p>\n

srt = pancreas_sub, group.by = c(“CellType”, “SubCellType”),<\/p>\n

reduction = “UMAP”, theme_use = “theme_blank”<\/p>\n

)<\/p>\n

<\/p>\n

##\u7ec6\u80de\u5468\u671f\u6ce8\u91ca<\/p>\n

CellDimPlot(<\/p>\n

srt = pancreas_sub, group.by = “SubCellType”, stat.by = “Phase”,<\/p>\n

reduction = “UMAP”, theme_use = “theme_blank”<\/p>\n

)<\/p>\n

<\/p>\n

##\u7279\u5f81\u6ce8\u91ca<\/p>\n

FeatureDimPlot(<\/p>\n

srt = pancreas_sub, features = c(“Sox9”, “Neurog3”, “Fev”, “Rbp4”),<\/p>\n

reduction = “UMAP”, theme_use = “theme_blank”<\/p>\n

)<\/p>\n

<\/p>\n

FeatureDimPlot(<\/p>\n

srt = pancreas_sub, features = c(“Ins1”, “Gcg”, “Sst”, “Ghrl”),<\/p>\n

compare_features = TRUE, label = TRUE, label_insitu = TRUE,<\/p>\n

reduction = “UMAP”, theme_use = “theme_blank”<\/p>\n

)<\/p>\n

<\/p>\n

##\u7ec6\u80de\u7c7b\u578b\u3001\u767e\u5206\u6bd4\u548c\u7ec6\u80de\u5468\u671f<\/p>\n

ht <- GroupHeatmap(<\/p>\n

srt = pancreas_sub,<\/p>\n

features = c(<\/p>\n

“Sox9”, “Anxa2”, # Ductal<\/p>\n

“Neurog3”, “Hes6”, # EPs<\/p>\n

“Fev”, “Neurod1”, # Pre-endocrine<\/p>\n

“Rbp4”, “Pyy”, # Endocrine<\/p>\n

“Ins1”, “Gcg”, “Sst”, “Ghrl” # Beta, Alpha, Delta, Epsilon<\/p>\n

),<\/p>\n

group.by = c(“CellType”, “SubCellType”),<\/p>\n

heatmap_palette = “YlOrRd”,<\/p>\n

cell_annotation = c(“Phase”, “G2M_score”, “Cdh2”),<\/p>\n

cell_annotation_palette = c(“Dark2”, “Paired”, “Paired”),<\/p>\n

show_row_names = TRUE, row_names_side = “left”,<\/p>\n

add_dot = TRUE, add_reticle = TRUE<\/p>\n

)<\/p>\n

print(ht$plot)<\/p>\n

<\/p>\n

##\u8d28\u63a7<\/p>\n

## conda install -c bioconda bioconductor-scdblfinder \u4f9d\u8d56\u4e0d\u9002\u914d<\/strong><\/p>\n

# \u5b89\u88c5\u8def\u5f84<\/strong><\/p>\n

pancreas_sub <- RunCellQC(srt = pancreas_sub)<\/p>\n

CellDimPlot(srt = pancreas_sub, group.by = “CellQC”, reduction = “UMAP”)<\/p>\n

<\/p>\n

CellStatPlot(srt = pancreas_sub, stat.by = “CellQC”, group.by = “CellType”, label = TRUE)<\/p>\n

<\/p>\n

CellStatPlot(<\/p>\n

srt = pancreas_sub,<\/p>\n

stat.by = c(<\/p>\n

“db_qc”, “outlier_qc”, “umi_qc”, “gene_qc”,<\/p>\n

“mito_qc”, “ribo_qc”, “ribo_mito_ratio_qc”, “species_qc”<\/p>\n

),<\/p>\n

plot_type = “upset”, stat_level = “Fail”<\/p>\n

)<\/p>\n

<\/p>\n

##\u6807\u51c6\u6d41\u7a0b<\/strong><\/p>\n

pancreas_sub <- Standard_SCP(srt = pancreas_sub)<\/p>\n

CellDimPlot(<\/p>\n

srt = pancreas_sub, group.by = c(“CellType”, “SubCellType”),<\/p>\n

reduction = “StandardUMAP2D”, theme_use = “theme_blank”<\/p>\n

)<\/p>\n

<\/p>\n

\u5728\u8fd9\u4e4b\u540e\u8fd8\u6709\u975e\u5e38\u591a\u8fdb\u9636\u4e14\u7f8e\u89c2\u7684\u4ee3\u7801\uff0c\u5c0f\u679c\u7684\u7b14\u8bb0\u672c\u6709\u6240\u9650\u5236\u5c31\u4e0d\u4e00\u4e00\u5c55\u793a\u5566\uff0c\u628a\u4ee3\u7801\u5c55\u793a\u7ed9\u5927\u5bb6\uff0c\u540e\u7eed\u7684\u7ed3\u679c\u56fe\u5c0f\u679c\u4f1a\u6253\u5305\u6210\u538b\u7f29\u6587\u4ef6\u5939\u5728\u6587\u7ae0\u7ed3\u5c3e\u5206\u4eab\u7ed9\u5927\u5bb6\u54e6\uff01<\/p>\n

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