Reanalise after QC

Set-up

library(here) # for reproducible paths
library(SingleCellExperiment)
library(scater) # For qcs
library(scran) # for normalisation, feature selection
library(ggplot2) # To add titles to plots
library(batchelor) # Batch correction
library(patchwork) # agregate plots
library(pals) # for palettes with large n

project <- "fire-mice"
sce <- readRDS(here("processed", project, "sce_clusterQC.RDS"))
source(here("src/colours.R"))
levels(sce$genotype) <- levels(c("WT", "HET", "KO"))

The object has 23719 genes and 51194 cells.

Cell QC

Previous thresholds were: detected genes: 429 - 7111 sum umi: 462 - 19024 mt: 14.37%

Click to expand plots

Violin plots

Split by sample

plotColData(sce, x = "Sample", y = "subsets_mt_percent") +
  scale_y_log10() + ggtitle("mt genes") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +  scale_color_manual(values = cols)

## Warning: Transformation introduced infinite values in continuous y-axis
## Transformation introduced infinite values in continuous y-axis

## Warning: Removed 6 rows containing non-finite values (stat_ydensity).

## Warning: Removed 6 rows containing missing values (geom_point).

plotColData(sce, x = "Sample", y = "detected") +
  scale_y_log10() + ggtitle("Detected genes log scale") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +  scale_color_manual(values = cols)

plotColData(sce, x = "Sample", y = "sum") +
  scale_y_log10() + ggtitle("Total count log scale") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +  scale_color_manual(values = cols)

Split by cell type

#mt
plotColData(sce, x = "cluster_names", y = "subsets_mt_percent", colour_by = "Sample") +
scale_y_continuous(breaks = scales::pretty_breaks(n = 10)) +
   ggtitle("mt genes") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) + 
  scale_color_manual(values = cols)

## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.

#detected
plotColData(sce, x = "cluster_names", y = "detected",  colour_by = "Sample") +
  scale_y_continuous(breaks = scales::pretty_breaks(n = 10)) +
   ggtitle("Detected genes") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) + 
  scale_color_manual(values = cols)

## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.

#sum
plotColData(sce, x = "cluster_names", y = "sum",  colour_by = "Sample") +
  scale_y_continuous(breaks = scales::pretty_breaks(n = 10)) +
  ggtitle("Total count") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) + 
  scale_color_manual(values = cols)

## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.

Split by cell type, log scales

plotColData(sce, x = "cluster_names", y = "detected",  colour_by = "Sample") +
  scale_y_log10(breaks = scales::pretty_breaks(n = 12)) + 
  ggtitle("Detected genes log scale") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +  scale_color_manual(values = cols) 

## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.

plotColData(sce, x = "cluster_names", y = "sum",  colour_by = "Sample") +
 scale_y_log10(breaks = scales::pretty_breaks(n = 12))+
  ggtitle("Total count log scale") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) + 
  scale_color_manual(values = cols)

## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.

Split by sample type, facet wrap

# detected
plotColData(sce, x = "Sample", y = "detected",  colour_by = "genotype", other_fields = "cluster_names") +
  scale_y_log10(breaks = scales::pretty_breaks(n = 12)) + 
  ggtitle("Detected genes log scale") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) +           scale_color_manual(values = col_wt_het_ko)  + facet_wrap(~cluster_names)

## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.

## Warning: Groups with fewer than two data points have been dropped.
## Groups with fewer than two data points have been dropped.
## Groups with fewer than two data points have been dropped.

# sum
plotColData(sce, x = "Sample", y = "sum",  colour_by = "genotype", other_fields = "cluster_names") +
 scale_y_log10(breaks = scales::pretty_breaks(n = 12))+
  ggtitle("Total count log scale") +
  theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust = 1)) + 
  scale_color_manual(values = col_wt_het_ko)+ facet_wrap(~cluster_names)

## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.

## Warning: Groups with fewer than two data points have been dropped.
## Groups with fewer than two data points have been dropped.
## Groups with fewer than two data points have been dropped.

hist(
  sce$detected,
  breaks = 100
)

hist(
  sce$sum,
  breaks = 100
)

hist(
  sce$subsets_mt_percent,
  breaks = 100
)

Scatter plots

plotColData(sce, x = "sum", y = "subsets_mt_percent", colour_by = "genotype", other_fields = "cluster_names") + facet_wrap(~cluster_names) + 
  scale_color_manual(values = col_wt_het_ko)

## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.

plotColData(sce, x = "sum", y = "detected", colour_by = "genotype", other_fields = "cluster_names") + facet_wrap(~cluster_names) + 
  scale_color_manual(values = col_wt_het_ko)

## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.

plotColData(sce, x = "sum", y = "subsets_mt_percent", colour_by = "Sample", other_fields = "cluster_names") + facet_wrap(~cluster_names) + 
  scale_color_manual(values = cols)

## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.

plotColData(sce, x = "sum", y = "detected", colour_by = "Sample", other_fields = "cluster_names") + facet_wrap(~cluster_names) + 
  scale_color_manual(values = cols)

## Scale for 'colour' is already present. Adding another scale for 'colour',
## which will replace the existing scale.