Commit 983bd279 authored by Anne  BITON's avatar Anne BITON
Browse files

Fix YS_01.load.Rmd such it works with new data loading

parent c0b95d37
......@@ -212,7 +212,7 @@ mcounts <- Matrix(as.matrix(umicounts[,-1]))
rownames(mcounts) <- umicounts$gene
umis <- CreateSeuratObject(counts = mcounts,
meta.data = data.frame(annot))
meta.data = data.frame(annot, row.names = 'cellID'))
rm(mcounts)
......@@ -225,7 +225,7 @@ umis$condition_halfplate <- factor(umis$condition_halfplate, levels = unique(umi
VlnPlot(object = umis, features = c("nFeature_RNA", "nCount_RNA", "percent.mito"),
ncol = 1, group.by = 'condition_halfplate', pt.size = .05,
cols = annot_ys$nextseq500_run[match(levels(umis$condition_halfplate), annot_ys$condition_halfplate)]+1)
cols = annot$nextseq500_run[match(levels(umis$condition_halfplate), annot$condition_halfplate)]+1)
#as.character(umis$nextseq500_run))
dir.create(paste0(dirdata,'/derived/YS_library123/'))
......@@ -234,20 +234,6 @@ save(umis, file=paste0(dirdata,'derived/YS_library123/YS_library123_umis.rda'))
```
## Boxplots of number of UMIs and number of detected genes
```{r, fig.width=12}
par(mar=c(10,5,4,4)); boxplot(umis$nCount_RNA ~ umis$date_of_sort_yyyy_mm_dd, ylab='#UMIs')
par(mar=c(10,5,4,4)); boxplot(umis$nCount_RNA ~ umis$condition_halfplate, las=2, ylab='#UMIs', xlab='', col = annot_ys$nextseq500_run[match(levels(umis$condition_halfplate), paste(annot_ys$condition, annot_ys$halfplate,sep='_'))]+1)
par(mar=c(5,5,4,4)); boxplot(umis$nCount_RNA ~ umis$nextseq500_run, ylab='#UMIs')
par(mar=c(5,5,4,4)); boxplot(umis$nCount_RNA ~ umis$sequencing_date_yyyy_mm_dd, ylab='#UMIs')
par(mar=c(10,5,4,4)); boxplot(umis$nFeature_RNA ~ umis$date_of_sort_yyyy_mm_dd, ylab='#detected genes', )
par(mar=c(10,5,4,4)); boxplot(umis$nFeature_RNA ~ umis$condition_halfplate, las=2, ylab='#UMIs', xlab='', col = annot_ys$nextseq500_run[match(levels(umis$condition_halfplate), paste(annot_ys$condition, annot_ys$halfplate,sep='_'))]+1)
par(mar=c(5,5,4,4)); boxplot(umis$nFeature_RNA ~ umis$nextseq500_run, ylab='#detected genes')
par(mar=c(5,5,4,4)); boxplot(umis$nFeature_RNA ~ umis$sequencing_date_yyyy_mm_dd, ylab='#detected genes')
```
## Histogram of number of detected genes
......@@ -359,13 +345,11 @@ The number of cells selected per condition and genotype is: `r table(sceall$cond
```{r}
colData(sce) <- annot[match(colnames(sce), annot$cellID),]
#colData(sce) <- annot[match(colnames(sce), annot$cellID),]
save(sce, file=paste0(dirdata,'derived/YS_library123/YS_library123_sce.rda'))
```
The number of selected cells per replicate selected for each facs annotation is: `r table(sceall$condition_replicate_plate) %>% knitr::kable()`.
The number of selected cells per replicate selected for each facs annotation is: `r table(sceall$FACS) %>% knitr::kable()`.
The UMI counts of the data remaining after this first filtering step are available in `data/derived/YS_library123/YS_library123_sce.rda`.
......
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