version bump

Author: drewjbeh

build/lib/mimseq/deseq.R

@@ -270,17 +270,19 @@ for (type in c("cyto", "mito")) {
           geom_point(size=3) +
           xlab(paste0("PC1: ",percentVar[1],"% variance")) +
           ylab(paste0("PC2: ",percentVar[2],"% variance")) + 
-          coord_fixed()
-        ggsave(paste(subdir_anticodon, "qc-pca.png", sep="/"), height = 7, width = 8)
+          coord_fixed() +
+          theme_bw()
+        ggsave(paste(subdir_anticodon, "qc-pca.pdf", sep="/"), height = 7, width = 8)
 
         pcaData_isodecoder <- plotPCA(vsd_isodecoder, intgroup="condition", returnData=TRUE)
         percentVar <- round(100 * attr(pcaData_isodecoder, "percentVar"))
         ggplot(pcaData_isodecoder, aes(PC1, PC2, color=condition)) +
           geom_point(size=3) +
           xlab(paste0("PC1: ",percentVar[1],"% variance")) +
           ylab(paste0("PC2: ",percentVar[2],"% variance")) + 
-          coord_fixed()
-        ggsave(paste(subdir_isodecoder, "qc-pca.png", sep="/"), height = 7, width = 8)
+          coord_fixed() +
+          theme_bw()
+        ggsave(paste(subdir_isodecoder, "qc-pca.pdf", sep="/"), height = 7, width = 8)
 
         # Get combinations of coditions for various DE contrasts
         ordered_levels = levels(lastlevel(unique(dds_anticodon$condition), control_cond))
@@ -345,7 +347,7 @@ for (type in c("cyto", "mito")) {
             scale_x_log10() + scale_y_log10() + 
             #geom_smooth(method = 'lm', se = TRUE, alpha = 0.5, color = '#3182bd', fill = 'grey') +
             geom_abline(intercept = 0, slope = 1, linetype = 'dashed', color = '#3182bd', alpha = 0.8) + 
-            scale_color_manual(paste('Differential expression\n(adj-p <=',p_adj, ')'), labels = c("None", "Down", "Up"), values = c("FALSE"="darkgrey", "TRUE-1"="#f28f3b", "TRUE1"="#4daf4a")) + 
+            scale_color_manual(paste('Differential expression\n(adj-p <=',p_adj, ')'), labels = c("None", "Down", "Up"), values = c("FALSE"="darkgrey", "TRUE-1"="#9970ab", "TRUE1"="#55ae61")) + 
             scale_shape_manual(paste('Differential expression\n(adj-p <=',p_adj, ')'), labels = c("None", "Down", "Up"), values = c("FALSE"=19, "TRUE-1"=17, "TRUE1"=17)) + 
             scale_size_manual(values = c(1,2), guide = "none") + theme_bw() +
             labs(x = paste('log10', combinations[[i]][2], 'counts', sep = ' '), y = paste('log10', combinations[[i]][1], 'counts', sep = ' ')) +
@@ -356,7 +358,7 @@ for (type in c("cyto", "mito")) {
             scale_x_log10() + scale_y_log10() + 
             #geom_smooth(method = 'lm', se = TRUE, alpha = 0.5, color = '#3182bd', fill = 'grey') +
             geom_abline(intercept = 0, slope = 1, linetype = 'dashed', color = '#3182bd', alpha = 0.8) + 
-            scale_color_manual(paste('Differential expression\n(adj-p <=',p_adj, ')'), labels = c("None", "Down", "Up"), values = c("FALSE"="darkgrey", "TRUE-1"="#f28f3b", "TRUE1"="#4daf4a")) + 
+            scale_color_manual(paste('Differential expression\n(adj-p <=',p_adj, ')'), labels = c("None", "Down", "Up"), values = c("FALSE"="darkgrey", "TRUE-1"="#9970ab", "TRUE1"="#55ae61")) + 
             scale_shape_manual(paste('Differential expression\n(adj-p <=',p_adj, ')'), labels = c("None", "Down", "Up"), values = c("FALSE"=19, "TRUE-1"=17, "TRUE1"=17)) + 
             scale_size_manual(values = c(1,2), guide = "none") + theme_bw() +
             labs(x = paste('log10', combinations[[i]][2], 'counts', sep = ' '), y = paste('log10', combinations[[i]][1], 'counts', sep = ' ')) +
@@ -427,7 +429,7 @@ for (type in c("cyto", "mito")) {
 
         # Heatmaps
         # note that all tables and plots only built if DE tables are not empty
-        col_fun = colorRamp2(c(-3, 0, 3), c("#CC5803", "#f7f7f7", "#36682B"))
+        col_fun = colorRamp2(c(-3, 0, 3), c("#762a83", "#f7f7f7", "#1b7837"))
 
         # Annotation for baseMean counts
         if (nrow(comb_isodecoder) != 0) {

build/lib/mimseq/modPlot.R

@@ -689,7 +689,7 @@ if (length(unique(mods$condition)) > 1) {
       # only draw if temp consists of something other than 0s
       if (length(temp[which(temp != 0)]) > 0) {
         # create new variable for adding info about mito to plot names
-        col_fun = colorRamp2(c(max(abs(temp)), 0, -max(abs(temp))), c("#36682B", "#f7f7f7","#CC5803"))
+        col_fun = colorRamp2(c(max(abs(temp)), 0, -max(abs(temp))), c("#1b7837", "#f7f7f7","#762a83"))
         if (type == "mito") {
           write.csv(temp, file=paste(out, "mods_logOR/", paste("organelle", comp,"logOR.csv",sep="_"), sep=""))
           pdf(paste(out, 'mods_logOR/', paste("organelle", comp, "logOR.pdf", sep = "_"), sep = ''), width = 14, height = 12)

build/lib/mimseq/version.py

@@ -1 +1 @@
-__version__ = "v1.1.4"
+__version__ = "v1.1.5"

dist/mimseq-1.1.4.tar.gz

@@ -1,11 +1,12 @@
-Metadata-Version: 2.1
+Metadata-Version: 1.1
 Name: mimseq
-Version: 1.1.4
+Version: 1.1.5
 Summary: Custom high-throughput tRNA sequencing alignment and quantification pipeline based on modification induced misincorporation cDNA synthesis.
 Home-page: https://github.com/nedialkova-lab/mim-tRNAseq
 Author: Drew Behrens
 Author-email: [email protected]
 License: GPLv3
+Description: UNKNOWN
 Platform: UNKNOWN
 Classifier: Development Status :: 4 - Beta
 Classifier: Environment :: Console
@@ -14,7 +15,3 @@ Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
 Classifier: Natural Language :: English
 Classifier: Programming Language :: Python :: 3
 Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
-License-File: LICENSE.txt
-
-UNKNOWN
-

dist/mimseq-1.1.4-py3-none-any.whl renamed to dist/mimseq-1.1.5-py3-none-any.whl

@@ -1 +1 @@
-__version__ = "v1.1.4"
+__version__ = "v1.1.5"