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第一步 下载所需的参考数据集
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| mkdir Human_Multiple_Cortical_Areas_SMART-seq && cd Human_Multiple_Cortical_Areas_SMART-seq
wget https://idk-etl-prod-download-bucket.s3.amazonaws.com/aibs_human_ctx_smart-seq/matrix.csv
wget https://idk-etl-prod-download-bucket.s3.amazonaws.com/aibs_human_ctx_smart-seq/metadata.csv
AWK
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第二步 读入下载的参考数据集与注释
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| ref_meta <- read.csv("/home/rqzhang/zlliu/R_data/human_M1_10x/metadata.csv")
ref_counts <- read.csv("/home/rqzhang/zlliu/R_data/human_M1_10x/matrix.csv")
APPLESCRIPT
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| ref2_meta <- read.csv("/home/rqzhang/zlliu/R_data/Human_Multiple_Cortical_Areas_SMART-seq/metadata.csv")
ref2_counts <- read.csv("/home/rqzhang/zlliu/R_data/Human_Multiple_Cortical_Areas_SMART-seq/matrix.csv")
APPLESCRIPT
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第三步 转置矩阵
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| now_t <- Sys.time ()
ref_t_counts <- t(ref_counts) #超级慢，15分钟，似乎没有其他解决方案
Sys.time () - now_t
now_t <- Sys.time ()
ref2_t_counts <- t(ref2_counts) #超级慢，10分钟，似乎没有其他解决方案
Sys.time () - now_t
ref_d_counts <- data.frame(ref_t_counts[-1,], stringsAsFactors = F)
ref2_d_counts <- data.frame(ref2_t_counts[-1,], stringsAsFactors = F)
colnames(ref_d_counts) <- ref_t_counts[1,]
colnames(ref2_d_counts) <- ref2_t_counts[1,]
ref_d_counts <- as.data.frame(lapply(ref_d_counts, as.integer))
ref2_d_counts <- as.data.frame(lapply(ref2_d_counts, as.integer))
HASKELL
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第四步 加载程辑包并计算SummarizedExperiment
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| library(SummarizedExperiment)
library(scater)
ref_d_counts <- SummarizedExperiment(assays=list(counts=ref_d_counts))
ref2_d_counts <- SummarizedExperiment(assays=list(counts=ref2_d_counts))
ref_d_counts <- logNormCounts(ref_d_counts)
ref2_d_counts <- logNormCounts(ref2_d_counts)
ISBL
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| ref_d_counts$meta <- ref_meta
ref2_d_counts$meta <- ref2_meta
ANGELSCRIPT
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SingleR (一) 参考数据集的构建方法
https://b.limour.top/656.html