Analysis of ‘tolerance’ genes
Last updated: 2022-12-08
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Knit directory: cirrhosis-metabolism/
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| File | Version | Author | Date | Message |
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| html | 0258d2a | christianholland | 2022-12-07 | Build site. |
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| Rmd | 4715892 | christianholland | 2022-11-29 | wflow_publish("analysis/*.Rmd") |
Introduction
In this analysis I check the expression of 210 genes (in the following referred to as ‘tolerance’ genes) in the 1 year CCl4 chronic liver disease mouse model
Libraries and sources
These libraries and sources are used for this analysis.
# data wrangling
library(tidyverse)
library(readxl)
# statistics
library(fgsea)
# plotting
library(lemon)
library(tidytext)
library(plotly)
library(scales)
# colors
library(AachenColorPalette)
library(RColorBrewer)
# display tables
library(DT)
# development helpers
library(here)
library(devtools)
base_url <- "https://raw.githubusercontent.com/saezlab/liver-disease-atlas"
source_url(file.path(base_url, "master", "code", "utils-plots.R"))
source_url(file.path(base_url, "master", "code", "utils-utils.R"))Definition of global variables that are used throughout this analysis.
Annotate genes
# extract gene names
genes <- read_excel(here("data/annotation/210genes.xlsx")) |>
select(entrez = EntrezID, gene = Symbol) |>
arrange(gene)
saveRDS(genes, here(output_path, "genes_of_interest.rds"))Coverage
How many of those 210 genes are covered in the dataset?
Table of the ‘tolerance’ indicating whether the gene is covered in the dataset
Enrichment analysis
Enrichment analysis of the ‘tolerance’ genes within the 12 month CCl4 signature.
The tolerance genes are significantly enriched in the up-regulated
genes of the 12 month CCl4 signature
| Version | Author | Date |
|---|---|---|
| bacff3d | christianholland | 2022-11-29 |
Differentially expressed genes
Bar plots of the differentially expressed ‘tolerance’ genes
(abs(logFC) >= 1 & FDR <= 0.05) at time point 12 month
| Version | Author | Date |
|---|---|---|
| bacff3d | christianholland | 2022-11-29 |
Trajectories
Time course of ‘tolerance’ genes that are differentially expressed in at least one time point (either 2, 6 or 12 months). These are interactive plots. Hovering with the mouse over the dots will show the gene name.
This table summarizes the genes that are displayed in the trajectories plot
R version 4.2.1 (2022-06-23)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur ... 10.16
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
locale:
[1] de_DE.UTF-8/de_DE.UTF-8/de_DE.UTF-8/C/de_DE.UTF-8/de_DE.UTF-8
attached base packages:
[1] stats graphics grDevices datasets utils methods base
other attached packages:
[1] devtools_2.4.5.9000 usethis_2.1.6 here_1.0.1
[4] DT_0.26 RColorBrewer_1.1-3 AachenColorPalette_1.1.3
[7] scales_1.2.1 plotly_4.10.0 tidytext_0.3.4
[10] lemon_0.4.5 fgsea_1.22.0 readxl_1.4.1
[13] forcats_0.5.2 stringr_1.4.1 dplyr_1.0.10
[16] purrr_0.3.5 readr_2.1.3 tidyr_1.2.1
[19] tibble_3.1.8 ggplot2_3.3.6 tidyverse_1.3.2
[22] workflowr_1.7.0
loaded via a namespace (and not attached):
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[25] Matrix_1.4-1 fastmap_1.1.0 lazyeval_0.2.2
[28] gargle_1.2.1 cli_3.4.1 later_1.3.0
[31] htmltools_0.5.3 prettyunits_1.1.1 tools_4.2.1
[34] gtable_0.3.1 glue_1.6.2 fastmatch_1.1-3
[37] Rcpp_1.0.9 cellranger_1.1.0 jquerylib_0.1.4
[40] vctrs_0.5.0 crosstalk_1.2.0 xfun_0.34
[43] ps_1.7.1 rvest_1.0.3 mime_0.12
[46] miniUI_0.1.1.1 lifecycle_1.0.3 renv_0.16.0
[49] googlesheets4_1.0.1 getPass_0.2-2 hms_1.1.2
[52] promises_1.2.0.1 parallel_4.2.1 curl_4.3.3
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[61] tokenizers_0.2.3 pkgbuild_1.3.1 BiocParallel_1.30.4
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[67] lattice_0.20-45 labeling_0.4.2 htmlwidgets_1.5.4
[70] cowplot_1.1.1 processx_3.7.0 tidyselect_1.2.0
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[76] profvis_0.3.7 generics_0.1.3 DBI_1.1.3
[79] pillar_1.8.1 haven_2.5.1 whisker_0.4
[82] withr_2.5.0 janeaustenr_1.0.0 modelr_0.1.9
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[100] bslib_0.4.0 sessioninfo_1.2.2