这是我第一次使用read.table遇到此问题：对于具有大量列的行条目，read.table将列条目循环到下一行。
我有一个.txt文件，其中行的长度可变且不相等。作为参考，这是我正在阅读的.txt文件：http ://www.broadinstitute.org/gsea/msigdb/download_file.jsp?filePath=/resources/msigdb/4.0/c5.bp.v4.0.symbols.gmt
这是我的代码：
tabsep <- gsub("\\\\t", "\t", "\\t")
MSigDB.collection = read.table(fileName, header = FALSE, fill = TRUE, as.is = TRUE, sep = tabsep)
部分输出：第一列
V1 V2 V3 V4 V5 V6
1 TRNA_PROCESSING http://www.broadinstitute.org/gsea/msigdb/cards/TRNA_PROCESSING ADAT1 TRNT1 FARS2
2 REGULATION_OF_BIOLOGICAL_QUALITY http://www.broadinstitute.org/gsea/msigdb/cards/REGULATION_OF_BIOLOGICAL_QUALITY DLC1 ALS2 SLC9A7
3 DNA_METABOLIC_PROCESS http://www.broadinstitute.org/gsea/msigdb/cards/DNA_METABOLIC_PROCESS XRCC5 XRCC4 RAD51C
4 AMINO_SUGAR_METABOLIC_PROCESS http://www.broadinstitute.org/gsea/msigdb/cards/AMINO_SUGAR_METABOLIC_PROCESS UAP1 CHIA GNPDA1
5 BIOPOLYMER_CATABOLIC_PROCESS http://www.broadinstitute.org/gsea/msigdb/cards/BIOPOLYMER_CATABOLIC_PROCESS BTRC HNRNPD USE1
6 RNA_METABOLIC_PROCESS http://www.broadinstitute.org/gsea/msigdb/cards/RNA_METABOLIC_PROCESS HNRNPF HNRNPD SYNCRIP
7 INTS6 LSM5 LSM4 LSM3 LSM1
8 CRK
9 GLUCAN_METABOLIC_PROCESS http://www.broadinstitute.org/gsea/msigdb/cards/GLUCAN_METABOLIC_PROCESS GCK PYGM GSK3B
10 PROTEIN_POLYUBIQUITINATION http://www.broadinstitute.org/gsea/msigdb/cards/PROTEIN_POLYUBIQUITINATION ERCC8 HUWE1 DZIP3
...
部分输出：最后一列
V403 V404 V405 V406 V407 V408 V409 V410 V411 V412 V413 V414 V415 V416 V417 V418 V419 V420 V421
1
2 CALCA CALCB FAM107A CDK11A RASGRP4 CDK11B SYN3 GP1BA TNN ENO1 PTPRC MTL5 ISOC2 RHAG VWF GPI HPX SLC5A7 F2R
3
4
5
6 IRF2 IRF3 SLC2A4RG LSM6 XRCC6 INTS1 HOXD13 RP9 INTS2 ZNF638 INTS3 ZNF254 CITED1 CITED2 INTS9 INTS8 INTS5 INTS4 INTS7
7 POU1F1 TCF7L2 TNFRSF1A NPAS2 HAND1 HAND2 NUDT21 APEX1 ENO1 ERF DTX1 SOX30 CBY1 DIS3 SP1 SP2 SP3 SP4 NFIC
8
9
10
例如，第6行的列条目被循环填充以填充第7行和第8行。对于列数非常多的行条目，我似乎仅是这个问题。其他.txt文件也会发生这种情况，但在不同的列号处会中断。我检查了发生中断的所有行条目，并且条目中没有异常字符（它们都是标准的大写基因符号）。
我已经尝试了read.table和read.delim，结果相同。如果我先将.txt文件转换为.csv并使用相同的代码，则不会出现此问题（请参见下面的等效输出）。但是我不想首先转换每个文件。csv，实际上我只是想了解发生了什么。
如果我转换为.csv文件，则输出正确：
MSigDB.collection = read.table(fileName, header = FALSE, fill = TRUE, as.is = TRUE, sep = ",")
V1 V2 V3 V4 V5 V6
1 TRNA_PROCESSING http://www.broadinstitute.org/gsea/msigdb/cards/TRNA_PROCESSING ADAT1 TRNT1 FARS2 METTL1
2 REGULATION_OF_BIOLOGICAL_QUALITY http://www.broadinstitute.org/gsea/msigdb/cards/REGULATION_OF_BIOLOGICAL_QUALITY DLC1 ALS2 SLC9A7 PTGS2
3 DNA_METABOLIC_PROCESS http://www.broadinstitute.org/gsea/msigdb/cards/DNA_METABOLIC_PROCESS XRCC5 XRCC4 RAD51C XRCC3
4 AMINO_SUGAR_METABOLIC_PROCESS http://www.broadinstitute.org/gsea/msigdb/cards/AMINO_SUGAR_METABOLIC_PROCESS UAP1 CHIA GNPDA1 GNE
5 BIOPOLYMER_CATABOLIC_PROCESS http://www.broadinstitute.org/gsea/msigdb/cards/BIOPOLYMER_CATABOLIC_PROCESS BTRC HNRNPD USE1 RNASEH1
6 RNA_METABOLIC_PROCESS http://www.broadinstitute.org/gsea/msigdb/cards/RNA_METABOLIC_PROCESS HNRNPF HNRNPD SYNCRIP MED24
7 GLUCAN_METABOLIC_PROCESS http://www.broadinstitute.org/gsea/msigdb/cards/GLUCAN_METABOLIC_PROCESS GCK PYGM GSK3B EPM2A
8 PROTEIN_POLYUBIQUITINATION http://www.broadinstitute.org/gsea/msigdb/cards/PROTEIN_POLYUBIQUITINATION ERCC8 HUWE1 DZIP3 DDB2
9 PROTEIN_OLIGOMERIZATION http://www.broadinstitute.org/gsea/msigdb/cards/PROTEIN_OLIGOMERIZATION SYT1 AASS TP63 HPRT1
详细阐述我的评论...
从帮助页面到read.table：
数据列的数量是通过查看输入的前五行（如果文件少于五行，则查看整个文件）来确定的，或者通过
col.names指定它的长度或更长来确定的。可以想象这是错误的，如果是fill或是blank.lines.skip正确的，请col.names在必要时指定（如“示例”中所述）。
要解决未知数据集的问题，请使用count.fields确定文件中分隔符的数量，并使用该分隔符来创建col.names以read.table供使用：
x <- max(count.fields("~/Downloads/c5.bp.v4.0.symbols.gmt", "\t"))
Names <- paste("V", sequence(x), sep = "")
y <- read.table("~/Downloads/c5.bp.v4.0.symbols.gmt", col.names=Names, sep = "\t", fill = TRUE)
检查前几行。我将给您实际的全面检查。
y[1:6, 1:10]
# V1
# 1 TRNA_PROCESSING
# 2 REGULATION_OF_BIOLOGICAL_QUALITY
# 3 DNA_METABOLIC_PROCESS
# 4 AMINO_SUGAR_METABOLIC_PROCESS
# 5 BIOPOLYMER_CATABOLIC_PROCESS
# 6 RNA_METABOLIC_PROCESS
# V2 V3 V4
# 1 http://www.broadinstitute.org/gsea/msigdb/cards/TRNA_PROCESSING ADAT1 TRNT1
# 2 http://www.broadinstitute.org/gsea/msigdb/cards/REGULATION_OF_BIOLOGICAL_QUALITY DLC1 ALS2
# 3 http://www.broadinstitute.org/gsea/msigdb/cards/DNA_METABOLIC_PROCESS XRCC5 XRCC4
# 4 http://www.broadinstitute.org/gsea/msigdb/cards/AMINO_SUGAR_METABOLIC_PROCESS UAP1 CHIA
# 5 http://www.broadinstitute.org/gsea/msigdb/cards/BIOPOLYMER_CATABOLIC_PROCESS BTRC HNRNPD
# 6 http://www.broadinstitute.org/gsea/msigdb/cards/RNA_METABOLIC_PROCESS HNRNPF HNRNPD
# V5 V6 V7 V8 V9 V10
# 1 FARS2 METTL1 SARS AARS THG1L SSB
# 2 SLC9A7 PTGS2 PTGS1 MPV17 SGMS1 AGTR1
# 3 RAD51C XRCC3 XRCC2 XRCC6 ISG20 PRIM1
# 4 GNPDA1 GNE CSGALNACT1 CHST2 CHST4 CHST5
# 5 USE1 RNASEH1 RNF217 ISG20 CDKN2A CPA2
# 6 SYNCRIP MED24 RORB MED23 REST MED21
nrow(y)
# [1] 825
对于那些不想下载另一个文件来尝试的人来说，这是一个最小的示例。
创建一个6行CSV文件，其中最后一行比前5行包含更多字段，并尝试read.table在其上使用：
cat("1,2,3,4", "1,2,3,4", "1,2,3,4", "1,2,3,4",
"1,2,3,4", "1,2,3,4,5", file = "test1.txt",
sep = "\n")
read.table("test1.txt", header = FALSE, sep = ",", fill = TRUE)
# V1 V2 V3 V4
# 1 1 2 3 4
# 2 1 2 3 4
# 3 1 2 3 4
# 4 1 2 3 4
# 5 1 2 3 4
# 6 1 2 3 4
# 7 5 NA NA NA
注意最长的行在文件的前五行中的区别：
cat("1,2,3,4", "1,2,3,4,5", "1,2,3,4", "1,2,3,4",
"1,2,3,4", "1,2,3,4", file = "test2.txt",
sep = "\n")
read.table("test2.txt", header = FALSE, sep = ",", fill = TRUE)
# V1 V2 V3 V4 V5
# 1 1 2 3 4 NA
# 2 1 2 3 4 5
# 3 1 2 3 4 NA
# 4 1 2 3 4 NA
# 5 1 2 3 4 NA
# 6 1 2 3 4 NA
为了解决这个问题，我们使用count.fields它返回每行中检测到的字段数的向量。我们从中max获取并将其传递给的col.names参数read.table。
x <- count.fields("test1.txt", sep=",")
x
# [1] 4 4 4 4 4 5
read.table("test.txt", header = FALSE, sep = ",", fill = TRUE,
col.names = paste("V", sequence(max(x)), sep = ""))
# V1 V2 V3 V4 V5
# 1 1 2 3 4 NA
# 2 1 2 3 4 NA
# 3 1 2 3 4 NA
# 4 1 2 3 4 NA
# 5 1 2 3 4 NA
# 6 1 2 3 4 5