Remove check for ref ann file as now optional

bin/merge_kallisto_counts.py

@@ -41,7 +41,7 @@ def merge_counts(
     gene_lengths = gene_lengths.rename(columns={"feature_id": "locus_tag"})
     quant_merged = quant_merged[["feature_id"] + metadata["sample"].tolist()]
     # export merged counts
-    outf1 = os.path.join(out_dir, "gene_counts.tsv")
+    outf1 = os.path.join(out_dir, "gene_counts1.tsv")
     quant_merged.to_csv(outf1, index=False, sep="\t")
     # # gene annotation df for extracting protein-coding genes
     # annot_dat = (gffpd.read_gff3(gff_f)).df

bin/normalise_counts.R

@@ -36,7 +36,7 @@ outdir <- opt$outdir
 #     stringsAsFactors = FALSE
 # )
 
-counts_tab <- read_tsv("gene_counts_pc1.tsv")
+counts_tab <- read_tsv("gene_counts_pc.tsv")
 ref_gene_tab <- read_tsv("ref_gene_df.tsv")
 
 gene_names <- counts_tab[["feature_id"]]

bin/pca.R

@@ -57,25 +57,16 @@ meta_tab$group <- as.factor(as.character(meta_tab$group))
 ## order rows to match counts columns
 meta_tab <- meta_tab[match(colnames(norm_counts), meta_tab$sample), ]
 
-cat(colnames(norm_counts), file = stderr())
-cat(dim(norm_counts), file = stderr())
 
 
 ## ------------------------------------------------------------------------------
 ## PCA
 ## ------------------------------------------------------------------------------
 pca_counts <- prcomp(t(norm_counts), center = TRUE, scale = FALSE)
 
-cat(colnames(pca_counts), file = stderr())
-cat(dim(pca_counts), file = stderr())
-
 pca_coords <- data.frame(pca_counts$x)
 pca_coords$sample <- rownames(pca_coords)
 
-cat(colnames(pca_coords), file = stderr())
-cat(dim(pca_coords), file = stderr())
-
-
 # move sample to first column
 pca_coords <- pca_coords[c(
     "sample", colnames(pca_coords)[1:ncol(pca_coords) - 1]