In stemangiola/sccompTemp: Outlier-aware and Count-based Compositional Analysis of Single-cell Data.

knitr::opts_chunk$set( fig.path = "man/figures/")

library(dplyr)
library(sccomp)
library(ggplot2)
library(forcats)
data("seurat_obj")
data("sce_obj")
data("counts_obj")

Installation

devtools::install_github("stemangiola/sccomp")

Analysis

From Seurat Object

res =
  seurat_obj %>%
  sccomp_glm(  ~ type, sample, cell_group )

From SingleCellExperiment Object

res =
  sce_obj %>%
  sccomp_glm( ~ type, sample, cell_group)

From data.frame

res =
  seurat_obj[[]] %>%
  sccomp_glm(~ type, sample, cell_group )

From counts

res =
  counts_obj %>%
  sccomp_glm( ~ type, sample, cell_group, count)

Outliers identified

data_for_plot = 
  res %>% 
    tidyr::unnest(outliers) %>%
    left_join(counts_obj, by = c("cell_group", "sample")) %>%
    group_by(sample) %>%
    mutate(proportion = (count+1)/sum(count+1)) %>%
    ungroup(sample) 

 ggplot() +
  geom_boxplot(
    aes(type, proportion, fill=significant),
    outlier.shape = NA, 
    data = data_for_plot %>% filter(!outlier)
  ) + 
  geom_jitter(aes(type, proportion, color=outlier), size = 1, data = data_for_plot) + 
  facet_wrap(~ interaction(cell_group), scale="free_y") +
  scale_y_continuous(trans="logit") +
  scale_color_manual(values = c("black", "#e11f28")) +
  scale_fill_manual(values = c("white", "#E2D379")) +
  xlab("Biological condition") + 
  ylab("Cell-group proportion") + 
  theme_bw() +
  theme(strip.background =element_rect(fill="white"))

Credible intervals

res %>%
  ggplot(aes(x=`.median_typecancer`, y=fct_reorder(cell_group, .median_typecancer))) +
  geom_vline(xintercept = 0, colour="grey") +
  geom_errorbar(aes(xmin=`.lower_typecancer`, xmax=`.upper_typecancer`, color=significant)) +
  geom_point() +
  scale_color_brewer(palette = "Set1") +
  theme_bw() +
  xlab("Credible interval of the slope") +
  ylab("Cell group") +
  ggtitle("After outlier filtering") +
  theme(legend.position = "bottom")

stemangiola/sccompTemp documentation built on Dec. 23, 2021, 5:30 a.m.