Mercurial > repos > iuc > edger
comparison edger.R @ 17:fb9dc2ee2fd4 draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/edger commit 76bd257ee51e9d7b912f570fb9ced1084ef44212
| author | iuc |
|---|---|
| date | Wed, 15 Oct 2025 10:24:16 +0000 |
| parents | ae2aad0a6d50 |
| children | fd9902d118e5 |
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| 16:ae2aad0a6d50 | 17:fb9dc2ee2fd4 |
|---|---|
| 328 # Split up contrasts separated by comma into a vector then sanitise | 328 # Split up contrasts separated by comma into a vector then sanitise |
| 329 contrast_data <- unlist(strsplit(opt$contrastData, split = ",")) | 329 contrast_data <- unlist(strsplit(opt$contrastData, split = ",")) |
| 330 } | 330 } |
| 331 contrast_data <- sanitise_equation(contrast_data) | 331 contrast_data <- sanitise_equation(contrast_data) |
| 332 contrast_data <- gsub(" ", ".", contrast_data, fixed = TRUE) | 332 contrast_data <- gsub(" ", ".", contrast_data, fixed = TRUE) |
| 333 # Convert colons to dots to match design matrix column name processing | |
| 334 contrast_data <- gsub(":", ".", contrast_data, fixed = TRUE) | |
| 333 | 335 |
| 334 bcv_pdf <- make_out("bcvplot.pdf") | 336 bcv_pdf <- make_out("bcvplot.pdf") |
| 335 bcv_png <- make_out("bcvplot.png") | 337 bcv_png <- make_out("bcvplot.png") |
| 336 ql_pdf <- make_out("qlplot.pdf") | 338 ql_pdf <- make_out("qlplot.pdf") |
| 337 ql_png <- make_out("qlplot.png") | 339 ql_png <- make_out("qlplot.png") |
| 428 design <- model.matrix(formula, factors) | 430 design <- model.matrix(formula, factors) |
| 429 | 431 |
| 430 for (i in seq_along(factor_list)) { | 432 for (i in seq_along(factor_list)) { |
| 431 colnames(design) <- gsub(factor_list[i], "", colnames(design), fixed = TRUE) | 433 colnames(design) <- gsub(factor_list[i], "", colnames(design), fixed = TRUE) |
| 432 } | 434 } |
| 435 | |
| 436 # Ensure column names are syntactically valid | |
| 437 colnames(design) <- make.names(colnames(design)) | |
| 433 | 438 |
| 434 # Calculating normalising factor, estimating dispersion | 439 # Calculating normalising factor, estimating dispersion |
| 435 data <- calcNormFactors(data, method = opt$normOpt) | 440 data <- calcNormFactors(data, method = opt$normOpt) |
| 436 | 441 |
| 437 if (want_robust) { | 442 if (want_robust) { |