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starrocks进行数据的删除

晒大太阳了 2024-06-26 阅读 33

1. 输入3列

只要前三列,第一列是行名,第二列是列名,第三列为值。

> head(df.net2.order)
       from             to   strength type
12439 CSTF2 ENST0000056844 -0.6859788  neg
12015 CSTF2 ENST0000056190 -0.5153181  neg
11208 CSTF2          GAPDH -0.4570489  neg

2. 输出数据框

行为基因调控因子,列为基因表达,值为相关系数。

> df.net2.df=df3toMatrix(df.net2.order)
> dim(df.net2.df)
[1]   27 4022
> df.net2.df[df.net2.df==0]=NA
> df.net2.df[1:4,1:5]
       ENST0000056844 ENST0000056190      GAPDH ENST0000063431       ARL6
CSTF2      -0.6859788     -0.5153181 -0.4570489     -0.4380417 -0.4351847
NUDT21             NA     -0.4719560 -0.4080007             NA -0.4125685
CPSF3      -0.4883905     -0.3955025 -0.4318929             NA -0.4517824
CPSF1              NA     -0.3722944 -0.3625508             NA -0.3016818

3. 转换函数

# from 3 columns to matrix: col1-row, col2-col, col2-value
df3toMatrix=function(df3){
  rows.id=df3[,1] |> unique()
  cols.id=df3[,2] |> unique()
  
  output=data.frame(matrix(0, nrow=length(rows.id), ncol=length(cols.id)))
  rownames(output)=rows.id
  colnames(output)=cols.id
  
  for(i in 1:nrow(df3)){
    output[df3[i, 1], df3[i, 2]]=df3[i,3]
  }
  output
}

ref

  • R语言稀疏矩阵详解 https://blog.csdn.net/jeffery0207/article/details/122507934
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