colnamesInt(i, unname(on), check_dups = FALSE) 中的错误：指定列的参数指定不存在的列：cols[1]='ID_REF'答案

【问题标题】：Error in colnamesInt(i, unname(on), check_dups = FALSE) : argument specifying columns specify non existing column(s): cols[1]='ID_REF'colnamesInt(i, unname(on), check_dups = FALSE) 中的错误：指定列的参数指定不存在的列：cols[1]='ID_REF'
【发布时间】：2021-10-08 09:20:33
【问题描述】：

我有两个文件，dat（samp.matrix是它的数据矩阵）和它对应的注解文件ann。我删除了samp.matrix 中的异常值，现在想通过删除相应的异常值来更新ann（如ann.filtered）。如何更新ann？

samp.matrix <- data.matrix(dat[, (3:ncol(dat))])

# Remove Outlier(s) 
samp.matrix <- samp.matrix[, -(grep(names(outlier), colnames(samp.matrix)))]

# Eliminating probes with rowMeans less than 0 on a log2 scale
dat.fil <- subset(samp.matrix, log2(rowMeans(samp.matrix)) > 0)
removed <- nrow(samp.matrix) - nrow(dat.fil)

# Eliminate probes with rowMeans less than 3 on a log2 scale
dat.filtered <- subset(dat.fil, rowMeans(dat.fil) > 3)
dat.filtered <- as.data.frame(dat.filtered)
removed  <- nrow(dat.fil) - nrow(dat.filtered)


# Update annotation file
ID_REF <- rownames(ann)
ann <- cbind(ID_REF, ann)
rownames(ann) <- NULL
ann <- ann %>%  as.data.table()
dat.filtered <- dat.filtered %>%  as.data.table() 
ann.filtered <- ann[dat.filtered, on=.("ID_REF")] %>%

select(ID_REF, Gene.title, Gene.symbol)

colnamesInt(i, unname(on), check_dups = FALSE) 中的错误：参数指定列指定不存在的列：cols[1]='ID_REF'

dat

ID_REF	IDENTIFIER	GSM97800	GSM97804
1007_s_at	MIR4640	4701.5	4735.0
1053_at	RFC2	282.7	347.9
117_at	HSPA6	769.6	287.9
121_at	PAX8	1616.3	1527.2

dat.filtered

ID_REF	IDENTIFIER	GSM97800	GSM97804
1007_s_at	MIR4640	4701.5	4735.0
1053_at	RFC2	282.7	347.9

ann

ID_REF	Gene.title	Gene.symbol	Gene.ID
1007_s_at	microRNA 4640//discoidin domain receptor	MIR4640//DDR1	100616
1053_at	replication factor C subunit 2	RFC2	5982
117_at	heat shock protein family A (Hsp70)	HSPA6	3310
121_at	paired box 8	PAX8	7849

预期输出 ann.filtered

ID_REF	Gene.title	Gene.symbol	Gene.ID
1007_s_at	microRNA 4640//discoidin domain receptor	MIR4640//DDR1	100616
1053_at	replication factor C subunit 2	RFC2	5982

【问题讨论】：

标签： r dataframe filter statistics

【解决方案1】：

最简单的方法是加入这个表 ...与data.table 包

library(data.table)
library(dplyr)
ann <- ann %>%  as.data.table() ##convert to data.table
dat.filtered <- dat.filtered %>%  as.data.table() ##convert to data.table

ann[dat.filtered] %>% ##join
  select(ID_REF, Gene.title, Gene.symbol, Gene.ID) ##remove cols except selected

【讨论】：

我尝试了您的代码，但改用了ann[dat.filtered] %>% select(c(ID_REF, colnames(ann)))。我收到一个错误Error in [.data.table(ann, dat.filtered) : When i is a data.table (or character vector), the columns to join by must be specified using 'on=' argument (see ?data.table), by keying x (i.e. sorted, and, marked as sorted, see ?setkey), or by sharing column names between x and i (i.e., a natural join). Keyed joins might have further speed benefits on very large data due to x being sorted in RAM.
假设您忘记了ann 中的第一个 col (ID_REF)。具有正确名称ann[dat.filtered, on = 'ID_REF']
即使我添加了 colname ID_REF，我仍然收到 colname 不存在的错误。我已经更新了我上面的问题。

【解决方案2】：

由于您在两个数据框中都有一些共同的列，您可以进行左连接，然后只保留 ann 的列

library(dplyr)

#rename the first column to prevent having a blank column name in ann 
colnames(ann) <- c("ID_REF","Gene.title","Gene.symbol","Gene.ID") 

### join both dataframes keeping only rows rows avaiable from dat.filtered
### And keep only the original columns from ann
ann.filetered <- dat.filtered %>%
  left_join(ann, by=c("ID_REF","Gene.symbol","Gene.ID")) %>%
  select(ID_REF,Gene.title,Gene.symbol,Gene.ID)

【讨论】：