title: 【迁移】Rclone备份 VPS 数据到 onedrive urlname: Rclone-bei-fen-VPS-shu-ju-dao-onedrive date: 2023-01-30 23:00:16 index_img: https://api.limour.top/randomImg?d=2023-01-30 23:00:16
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#!/bin/bash
tar -zcPf /root/tmp/ngpm_live.tar.gz /root/base/NGPM/letsencrypt/live
# tar -tzvPf /root/tmp/ngpm_live.tar.gz
rclone sync --progress --ignore-errors --transfers=2 \
--exclude='/.*/**' \
--exclude='/.*' \
--exclude='/app/ServerStatus/serverstatus-monthtraffic/**' \
--exclude='/app/WordPress/www/wp-content/cache/**' \
--exclude='/base/NGPM/letsencrypt/live/**' \
--exclude='/base/NGPM/data/logs/**' \
/root od_lk:backup/lk
nano /root/backup.sh && chmod +x /root/backup.sh
/root/backup.sh
crontab -e
# 30 2 * * 2,4,6 /root/backup.sh
crontab -l
之前在自己的小机器上分析,现在需要在学校集群进行分析,因此需要在两个没有公网ip且不互联的服务器之间转移大量数据。因此计划使用Rclone,通过OneDrive进行中转。
data <- list()
ref_sce <- readRDS('~/upload/zl_liu/data/pca.rds')
data$zyy_umi <- ref_sce@assays$RNA@counts
data$zyy_meta <- ref_sce@meta.data
ref_sce <- readRDS('~/work_st/Prognosis/idea_2/fig3.2/fig6/sce.rds')
data$ch_umi <- ref_sce@assays$originalexp@counts
data$ch_meta <- ref_sce@meta.data
# tp_dir <- list(
# SRX6887739 = '~/work_st/sce/GSE137829/res/SRX6887739/outs/filtered_feature_bc_matrix',
# SRX6887740 = '~/work_st/sce/GSE137829/res/SRX6887740/outs/filtered_feature_bc_matrix',
# SRX6887741 = '~/work_st/sce/GSE137829/res/SRX6887741/outs/filtered_feature_bc_matrix',
# SRX6887742 = '~/work_st/sce/GSE137829/res/SRX6887742/outs/filtered_feature_bc_matrix',
# SRX8890105 = '~/work_st/sce/GSE137829/res/SRX8890105/outs/filtered_feature_bc_matrix',
# SRX8890106 = '~/work_st/sce/GSE137829/res/SRX8890106/outs/filtered_feature_bc_matrix'
# )
# counts <- Seurat::Read10X(data.dir = unlist(tp_dir))
# sce <- Seurat::CreateSeuratObject(counts, project = 'GSE137829',
# min.cells = 3, min.features = 200)
# data$GSE137829_umi <- sce@assays$RNA@counts
# data$GSE137829_meta <- sce@meta.data
tp_dir <- list(
P1 = '~/work/GSE137829/GSM4089151_P1_gene_cell_exprs_table.txt.gz',
P2 = '~/work/GSE137829/GSM4089152_P2_gene_cell_exprs_table.txt.gz',
P3 = '~/work/GSE137829/GSM4089153_P3_gene_cell_exprs_table.txt.gz',
P4 = '~/work/GSE137829/GSM4089154_P4_gene_cell_exprs_table.txt.gz',
P5 = '~/work/GSE137829/GSM4711414_P5_gene_cell_exprs_table.txt.gz',
P6 = '~/work/GSE137829/GSM4711415_P6_gene_cell_exprs_table.txt.gz'
)
sce <- list()
for (i in names(tp_dir)){
tmp <- read.table(gzfile(tp_dir[[i]]), header = T)
umi <- Matrix::as.matrix(x = tmp[-c(1,2)])
umi <- Matrix::Matrix(data = umi, sparse = T)
rownames(umi) <- tmp$Symbol
sce[[i]] <- Seurat::CreateSeuratObject(umi, project = i,
min.cells = 3, min.features = 200)
}
sce <- Reduce(merge, sce)
data$geo_umi <- sce@assays$RNA@counts
data$geo_meta <- sce@meta.data
saveRDS(data, '22.10.04.rds')
在两台服务器上挂载同一个OneDrive,第二台可以直接使用第一台的配置,文件路径在 ~/.config/rclone/rclone.conf