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Merge pull request #44 from bcbio/length_scaled_usage
add comment to make the user aware of options
2 parents da523a9 + ae0aadc commit dc1dc66

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00_params/params.R

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@@ -6,6 +6,10 @@ basedir <- "./" # where to write down output files
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# This is the file used to run nf-core or compatible to that
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coldata_fn <- "/Path/to/metadata/meta.csv"
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# This file is inside star_salmon/ folder
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# Use gene_counts_length_scaled.tsv if you want to detect Differential Gene Usage from the gene counts data
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# See more here: https://bioconductor.org/packages/devel/bioc/vignettes/tximport/inst/doc/tximport.html#Downstream_DGE_in_Bioconductor
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# This is correct because in nf-core/rnaseq this files is created with tximport argument countsFromAbundance="lengthScaledTPM"
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# https://github.com/nf-core/rnaseq/blob/0bb032c1e3b1e1ff0b0a72192b9118fdb5062489/modules/nf-core/tximeta/tximport/templates/tximport.r#L152
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counts_fn <- "/path/to/nf-core/output/star_salmon/salmon.merged.gene_counts.tsv"
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# This folder called "multiqc_report_data" is inside the output directory star_salmon inside multiqc folder
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multiqc_data_dir <- "/path/to/nf-core/output/multiqc/star_salmon/multiqc_report_data"

02_differential_expression/DEG.qmd

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@@ -860,7 +860,9 @@ fa_gsea_list <- lapply(de_list, function(contrast) {
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input = input_entrezid, # Query for the GSEA analysis
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all_in_life = all_in_life
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) # Annotation databases to query against
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tb %>% filter(padj < 0.05) %>% arrange(padj) # Filter and sort the GSEA output for results with an adjust p-value less than 0.05 and return them
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tb %>%
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filter(padj < 0.05) %>%
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arrange(padj) # Filter and sort the GSEA output for results with an adjust p-value less than 0.05 and return them
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})
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```
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dt_list <- list()
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for (contrast in names(de_list)) {
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res_sig <- fa_list[[contrast]][["all"]] %>%
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filter(padj < 0.05) %>% arrange(padj) # Filter and sort
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filter(padj < 0.05) %>%
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arrange(padj) # Filter and sort
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dt_list <- c(
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dt_list,
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list(h3(contrast)),

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