From 488288ba76d3cfeefbc600fdb4d2dba4f91c833e Mon Sep 17 00:00:00 2001
From: eberdan <emma.berdan@gmail.com>
Date: Tue, 21 May 2024 11:32:16 -0400
Subject: [PATCH] Update QC_nf-core.Rmd

---
 .../rnaseq/skeleton/QC/QC_nf-core.Rmd         | 20 ++++++++++++++++---
 1 file changed, 17 insertions(+), 3 deletions(-)

diff --git a/inst/rmarkdown/templates/rnaseq/skeleton/QC/QC_nf-core.Rmd b/inst/rmarkdown/templates/rnaseq/skeleton/QC/QC_nf-core.Rmd
index 1758a3c..6248c60 100644
--- a/inst/rmarkdown/templates/rnaseq/skeleton/QC/QC_nf-core.Rmd
+++ b/inst/rmarkdown/templates/rnaseq/skeleton/QC/QC_nf-core.Rmd
@@ -40,7 +40,6 @@ source(params$project_file)
 -   PI: `r PI`
 -   Analyst: `r analyst`
 -   Experiment: `r experiment`
--   Aim: `r aim`
 
 
 ```{r load_libraries, cache = FALSE, message = FALSE, warning=FALSE}
@@ -187,7 +186,19 @@ metrics <- metrics %>%
   mutate(x5_3_bias = qualimap_5_3_bias)
 
 # Sometimes we don't have rRNA due to mismatch annotation, We skip this if is the case
-gtf=rtracklayer::import(gtf_fn)
+
+if (params$genome == "hg38") {
+  gtf <- "../../data/hg38.rna.gtf"
+} elseif (params$genome == "mm10") {
+  gtf <- "../../data/mm10.rna.gtf"
+} elseif (params$genome == "mm39") {
+  gtf <- "../../data/mm39.rna.gtf"
+} elseif (params$genome == "other") {
+  gtf <- gtf_fn
+} else {
+  print("No genome provided! Please add it to params_qc_nf-core.R")
+}
+
 
 one=grep("gene_type", colnames(as.data.frame(gtf)), value = TRUE)
 another=grep("gene_biotype", colnames(as.data.frame(gtf)), value = TRUE)
@@ -414,7 +425,7 @@ metrics %>%
     ggplot(aes(x = factor(sample, level = order),
                y = r_and_t_rna_rate * 100, 
                color = .data[[factor_of_interest]])) +
-    geom_point(alpha = 0.5, size=4) +
+    geom_point(alpha = 0.5) +
     ylab("tRNA/rRNA rate, %")+
     ylim(0, rrna_ylim) + 
     ggtitle("tRNA/rRNA mapping rate") +
@@ -488,8 +499,11 @@ pca1 <- degPCA(vst, coldat_for_pca,
 pca2 <- degPCA(vst, coldat_for_pca,
               condition = factor_of_interest, data = T, pc1="PC3", pc2="PC4")[["plot"]]
 
+
+
 pca1 + scale_color_cb_friendly()
 pca2 + scale_color_cb_friendly()
+
 ```
 
 # Covariates analysis