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Hello.
I have read the published paper. The comparison of normalization methods is very interesting.
I think I can learn a lot from it.
I tried to use the released R script to check the effect of CTF and CUF normalization, but the script did not work.
What could be the problem?
Hello.
I have read the published paper. The comparison of normalization methods is very interesting.
I think I can learn a lot from it.
I tried to use the released R script to check the effect of CTF and CUF normalization, but the script did not work.
What could be the problem?
$ Rscript src/gene_filtering_by_cpm.R cpm/
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
✔ ggplot2 3.3.0 ✔ purrr 0.3.4
✔ tibble 3.0.1 ✔ dplyr 0.8.5
✔ tidyr 1.0.2 ✔ stringr 1.4.0
✔ readr 1.3.1 ✔ forcats 0.5.0
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
Error: 'NA' does not exist in current working directory ('/data').
Execution halted
R was tested with 3.6.3 and 4.1.4 of tidyverse provided by rocker.
https://hub.docker.com/r/rocker/tidyverse/tags
#3.6.3
sudo docker run --rm -itv $PWD:/data rocker/tidyverse:3.6.3 /bin/bash
And installed edgeR via BiocManager with the R console.
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