I am using R
to cbind about ~11000 files using:
dat <- do.call('bind_cols',lapply(lfiles,read.delim))
which is unbelievably slow. I am using R because my downstream processing like creating plots etc is in R. What are some fast alternatives to concatenating thousands of files by columns?
I have three types of files for which I want this done. They look like this:
[centos@ip data]$ head C021_0011_001786_tumor_RNASeq.abundance.tsv
target_id length eff_length est_counts tpm
ENST00000619216.1 68 26.6432 10.9074 5.69241
ENST00000473358.1 712 525.473 0 0
ENST00000469289.1 535 348.721 0 0
ENST00000607096.1 138 15.8599 0 0
ENST00000417324.1 1187 1000.44 0.0673096 0.000935515
ENST00000461467.1 590 403.565 3.22654 0.11117
ENST00000335137.3 918 731.448 0 0
ENST00000466430.5 2748 2561.44 162.535 0.882322
ENST00000495576.1 1319 1132.44 0 0
[centos@ip data]$ head C021_0011_001786_tumor_RNASeq.rsem.genes.norm_counts.hugo.tab
gene_id C021_0011_001786_tumor_RNASeq
TSPAN6 1979.7185
TNMD 1.321
DPM1 1878.8831
SCYL3 452.0372
C1orf112 203.6125
FGR 494.049
CFH 509.8964
FUCA2 1821.6096
GCLC 1557.4431
[centos@ip data]$ head CPBT_0009_1_tumor_RNASeq.rsem.genes.norm_counts.tab
gene_id CPBT_0009_1_tumor_RNASeq
ENSG00000000003.14 2005.0934
ENSG00000000005.5 5.0934
ENSG00000000419.12 1100.1698
ENSG00000000457.13 2376.9100
ENSG00000000460.16 1536.5025
ENSG00000000938.12 443.1239
ENSG00000000971.15 1186.5365
ENSG00000001036.13 1091.6808
ENSG00000001084.10 1602.7165
Thanks!
For fast reading of files, we can use fread
from data.table
and then rbind
the list
of data.table
using rbindlist
specifying the idcol=TRUE
to provide a grouping variable to identify each of the datasets
library(data.table)
DT <- rbindlist(lapply(lfiles, fread), idcol=TRUE)
If you have all numerical data, you can convert to matrix first, which can be quite a bit faster than data frames:
> microbenchmark(
do.call(cbind, rep(list(sleep), 1000)),
do.call(cbind, rep(list(as.matrix(sleep)), 1000))
)
Unit: microseconds
expr min lq mean
do.call(cbind, rep(list(sleep), 1000)) 6978.635 7496.690 8038.21531
do.call(cbind, rep(list(as.matrix(sleep)), 1000)) 636.282 722.814 862.01125
median uq max neval
7864.180 8397.8595 12213.473 100
744.647 793.0695 7416.430 100
Alternatively, if you want a data frame, you can cheat by using unlist
and then setting the class manually:
df <- unlist(rep(list(sleep), 1000), recursive=FALSE)
class(df) <- 'data.frame'
来源:https://stackoverflow.com/questions/38835892/fast-concatenation-of-thousands-of-files-by-columns