Mc4r in postnatal mouse PVN

workflowr

• Summary
• Checks
• Past versions

Last updated: 2021-05-20

Checks: 7 0

Knit directory: mc4r/

This reproducible R Markdown analysis was created with workflowr (version 1.6.2). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

---

R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Environment: empty

Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.

Seed: set.seed(20210511)

The command set.seed(20210511) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.

Session information: recorded

Great job! Recording the operating system, R version, and package versions is critical for reproducibility.

Cache: none

Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.

File paths: relative

Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.

Repository version: 639b6e1

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version 639b6e1. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:

Ignored files:
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    code/2021-05-12_morning-plots.Rhistory
    Ignored:    data/2021-05-13_001-086-446-605-669_adult_mm10-hypothalamus-pvn_alk-thinness-paper-subset-srt4-obj-umap.h5seurat
    Ignored:    data/2021-05-13_001-086-446-605-669_adult_mm10-hypothalamus-pvn_bottom-lh-excl-srt4-obj-sct-umap.h5seurat
    Ignored:    data/2021-05-13_001-086-446-605-669_adult_mm10-hypothalamus_srt4-obj-umap.h5seurat
    Ignored:    data/2021-05-13_001-086-446-605-669_mm10-hypothalamus_srt4-obj-umap.h5seurat
    Ignored:    data/2021-05-18_001-086-446-605-669_adult_mm10-hypothalamus-pvn_alk-thinness-paper-subset-srt4-obj-umap.h5seurat
    Ignored:    data/2021-05-18_001-086-446-605-669_adult_mm10-hypothalamus_srt4-obj-umap.h5seurat
    Ignored:    data/2021-05-18_001-086-446-605-669_mm10-hypothalamus_srt4-obj-umap.h5seurat
    Ignored:    data/oldCCA_nae_srt.rds
    Ignored:    data/subset_cca_to_velo.rds
    Ignored:    output/tables/2021-05-13_001-086-446-605-669_adult_mm10-hypothalamus-pvn_alk-thinness-paper-subset-srt4-obj-umap.rds
    Ignored:    output/tables/2021-05-13_001-086-446-605-669_adult_mm10-hypothalamus-pvn_bottom-lh-excl-srt4-obj-sct-umap.rds
    Ignored:    output/tables/2021-05-13_001-086-446-605-669_adult_mm10-hypothalamus_srt4-obj-umap.rds
    Ignored:    output/tables/2021-05-13_001-086-446-605-669_mm10-hypothalamus_srt4-obj-umap.rds
    Ignored:    output/tables/2021-05-18_001-086-446-605-669_adult_mm10-hypothalamus-pvn_alk-thinness-paper-subset-srt4-obj-umap.rds
    Ignored:    output/tables/2021-05-18_001-086-446-605-669_adult_mm10-hypothalamus_srt4-obj-umap.rds
    Ignored:    output/tables/2021-05-18_001-086-446-605-669_mm10-hypothalamus_srt4-obj-umap.rds
    Ignored:    renv/library/
    Ignored:    renv/local/
    Ignored:    renv/staging/

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

---

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/2021-05-14_pr_adult_pvn_neurons_mc4r.Rmd) and HTML (docs/2021-05-14_pr_adult_pvn_neurons_mc4r.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
Rmd	639b6e1	EugOT	2021-05-20	optimise to present
Rmd	1ab4c6e	EugOT	2021-05-18	workflowr::wflow_git_commit(all = TRUE)
html	1ab4c6e	EugOT	2021-05-18	workflowr::wflow_git_commit(all = TRUE)

---

Published subset of adult hypothalamic data (Nature + Cell datasets)

The following `from` values were not present in `x`: 26, 31, 43

Past versions of published-adult-sc-hypothalamus-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Past versions of published-adult-sc-hypothalamus-2.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Step back to see stratification by sequencing samples

Past versions of published-adult-sc-hypothalamus-by-samples-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Past versions of published-adult-sc-hypothalamus-by-samples-2.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

PVN neurons?

Past versions of plot-integrated-pvn-neurons-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

What we showed could be even better

Past versions of integrate-pvn-neurons-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Past versions of integrate-pvn-neurons-2.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Past versions of integrate-pvn-neurons-3.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Past versions of integrate-pvn-neurons-4.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Past versions of integrate-pvn-neurons-5.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

PVN neurons

Warning: CombinePlots is being deprecated. Plots should now be combined using
the patchwork system.

Past versions of plot-integrated-pvn-split-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

MC-Rs genes

Warning: Could not find Mc1r in the default search locations, found in RNA assay
instead

Warning: Could not find Mc2r in the default search locations, found in RNA assay
instead

Warning: Could not find Mc3r in the default search locations, found in RNA assay
instead

Warning in FeaturePlot(rar2020.srt.pvn, features = mcr_genes, pt.size = 0.7, :
All cells have the same value (0) of RNA_Mc2r.

Past versions of plot-integrated-pvn-mcrs-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Differential Gene Expression (DGE) test of published groups

Idents(rar2020.srt.pvn) <- "ident"

all_markers_pvn_wtree_final %>% 
    group_by(cluster) %>% 
    filter(p_val_adj < 0.01) %>% 
    slice_max(n = 7, order_by = avg_log2FC) %>% 
    print(., n = 35)

# A tibble: 35 x 7
# Groups:   cluster [5]
      p_val avg_log2FC pct.1 pct.2 p_val_adj cluster gene         
      <dbl>      <dbl> <dbl> <dbl>     <dbl> <chr>   <chr>        
 1 2.76e-22       6.25 0.972 0.572  3.65e-18 mneOXY  Oxt          
 2 1.28e-28       2.73 0.917 0.181  1.69e-24 mneOXY  Gm28928      
 3 1.50e-15       2.17 0.917 0.446  1.98e-11 mneOXY  Fam19a1      
 4 3.67e-12       2.03 0.944 0.612  4.86e- 8 mneOXY  Gpc5         
 5 2.11e-24       1.88 1     0.27   2.79e-20 mneOXY  Foxp2        
 6 1.82e-31       1.87 0.806 0.1    2.41e-27 mneOXY  S100a10      
 7 7.47e-18       1.50 1     0.42   9.87e-14 mneOXY  A830018L16Rik
 8 7.19e-40       6.63 0.978 0.768  9.50e-36 mneVAS  Avp          
 9 7.62e-41       2.48 1     0.732  1.01e-36 mneVAS  Pde4b        
10 4.03e-33       2.12 1     0.829  5.33e-29 mneVAS  Galntl6      
11 5.66e-22       1.84 0.888 0.521  7.48e-18 mneVAS  Zfp804a      
12 1.22e-15       1.68 0.685 0.302  1.61e-11 mneVAS  Gal          
13 4.35e-21       1.64 0.966 0.591  5.75e-17 mneVAS  Zfp804b      
14 4.31e-43       1.62 0.91  0.165  5.70e-39 mneVAS  Stxbp6       
15 1.53e-33       2.39 0.462 0.014  2.02e-29 pneCRH  Crh          
16 3.90e-25       1.65 0.877 0.369  5.16e-21 pneCRH  Nr3c2        
17 6.31e-16       1.39 0.846 0.511  8.35e-12 pneCRH  Fmnl2        
18 1.65e-15       1.34 1     0.759  2.19e-11 pneCRH  Nrxn3        
19 1.76e-14       1.32 0.908 0.591  2.33e-10 pneCRH  Gpc5         
20 1.93e-24       1.15 0.554 0.077  2.55e-20 pneCRH  Zbtb16       
21 1.58e-15       1.05 0.431 0.08   2.09e-11 pneCRH  Ppp1r17      
22 8.85e-38       5.55 1     0.198  1.17e-33 pneSS   Sst          
23 1.22e-19       2.38 1     0.557  1.61e-15 pneSS   Trpm3        
24 2.62e-17       2.07 0.974 0.509  3.46e-13 pneSS   Sorcs1       
25 1.29e-15       1.99 1     0.673  1.70e-11 pneSS   Ghr          
26 2.92e-14       1.77 0.842 0.359  3.87e-10 pneSS   Alk          
27 1.37e-15       1.75 0.868 0.359  1.81e-11 pneSS   Col25a1      
28 9.32e- 8       1.50 0.684 0.369  1.23e- 3 pneSS   Cntn3        
29 3.21e-42       2.38 0.968 0.689  4.25e-38 pneTRH  Lingo2       
30 8.87e-43       1.98 0.947 0.57   1.17e-38 pneTRH  March1       
31 2.97e-43       1.95 0.64  0.013  3.93e-39 pneTRH  Cbln2        
32 3.98e-39       1.95 0.884 0.456  5.26e-35 pneTRH  Nav3         
33 2.07e- 8       1.88 0.561 0.382  2.74e- 4 pneTRH  Il1rapl2     
34 1.79e-23       1.69 0.757 0.311  2.37e-19 pneTRH  Pcdh11x      
35 4.58e-29       1.68 0.788 0.219  6.06e-25 pneTRH  Trh          

Percent of cells expressing MC-Rs in these cells (very low?)

Past versions of make-dotplot-mcrs-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

NULL

Marker genes for these clusters

Past versions of make-dotplot-pvn-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Particular combinations of markers in Mc4r containing cells (n sets = 10)

Past versions of plot-upset-10-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Particular combinations of markers in Mc4r containing cells (n sets = 5)

Past versions of plot-upset-5-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Particular combinations of markers in Mc4r containing cells (n sets = 3)

Past versions of plot-upset-3-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Absolute correlation of Mc4r expression with Slc17a6

Past versions of plot-Slc17a6-correlations-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Absolute correlation of Mc4r expression with Alk

Past versions of plot-Alk-correlations-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Absolute correlation of Mc4r expression with Crh

Past versions of plot-Crh-correlations-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Absolute correlation of Mc4r expression with Trh

Past versions of plot-Trh-correlations-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Absolute correlation of Mc4r expression with Sst

Past versions of plot-Sst-correlations-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Absolute correlation of Mc4r expression with Avp

Past versions of plot-Avp-correlations-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Absolute correlation of Mc4r expression with Oxt

Past versions of plot-Oxt-correlations-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Density of Mc4r expressing cells in UMAP (cells similarity) space

Past versions of plot-density-mc4r-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Density of expressing cells in UMAP space for whole MC-R gene family

Past versions of plot-density-mcrs-on-original-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Step back to estimate density of Mc4r and Alk expression across whole adult dataset

Warning: CombinePlots is being deprecated. Plots should now be combined using
the patchwork system.

Past versions of plot-density-c-mc4r-alk-on-original-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Examine shared attributes density in PVN (example)

Warning: CombinePlots is being deprecated. Plots should now be combined using
the patchwork system.

Past versions of plot-density-cj-mc4r-alk-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Density of main PVN markers expressing cells -

Past versions of plot-density-Sst-alk-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Density of main PVN markers expressing cells -

Past versions of plot-density-Avp-alk-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Density of main PVN markers expressing cells -

Past versions of plot-density-Oxt-alk-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Density of main PVN markers expressing cells -

Past versions of plot-density-Trh-alk-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Checking expectation for high density of shared Crh and Mc4r we again see contradiction

Warning: CombinePlots is being deprecated. Plots should now be combined using
the patchwork system.

Past versions of plot-density-cj-mc4r-crh-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

It’s on the edge

Past versions of plot-density-j-mc4r-crh-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Wierd Trh part of Crh cluster

Warning: CombinePlots is being deprecated. Plots should now be combined using
the patchwork system.

Past versions of plot-density-cj-trh-crh-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Small lyrical digression about Trh patterns: Onecut3+Trh density (1/4)

Past versions of plot-density-j-onecut3-trh-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Small lyrical digression about Trh patterns: Zic5+Trh density (2/4)

Past versions of plot-density-j-zic5-trh-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Small lyrical digression about Trh patterns: Onecut3-> Zic5 -> Trh density (3/4)

Warning: CombinePlots is being deprecated. Plots should now be combined using
the patchwork system.

Past versions of plot-density-cj-onecut3-zic5-trh-on-original-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Small lyrical digression about Trh patterns: Onecut3-> Zic5 -> Trh density (4/4)

Excluded from original publication

Back to Mc4r: blend plots of Mc4r and Trh expression

Past versions of plot-blend-mcr4-trh-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Back to Mc4r: blend plots of Mc4r and Crh expression

Past versions of plot-blend-mcr4-crh-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Back to Mc4r: blend plots of Trh and Crh expression

Past versions of plot-blend-trh-crh-umap-1.png

Version	Author	Date
1ab4c6e	EugOT	2021-05-18

Back to Mc4r: Particular combinations of markers in PVN

NULL

Session information

R version 4.1.0 (2021-05-18)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.10

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.10.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=de_AT.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=de_AT.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=de_AT.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=de_AT.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices datasets  utils     methods   base     

other attached packages:
 [1] Nebulosa_1.2.0        patchwork_1.1.1       UpSetR_1.4.0         
 [4] SeuratDisk_0.0.0.9019 SeuratWrappers_0.3.0  SeuratObject_4.0.1   
 [7] Seurat_4.0.1          future_1.21.0         magrittr_2.0.1       
[10] forcats_0.5.1         stringr_1.4.0         dplyr_1.0.6          
[13] purrr_0.3.4           readr_1.4.0           tidyr_1.1.3          
[16] tibble_3.1.2          ggplot2_3.3.3         tidyverse_1.3.1      
[19] here_1.0.1            workflowr_1.6.2      

loaded via a namespace (and not attached):
  [1] utf8_1.2.1                  reticulate_1.20            
  [3] ks_1.12.0                   tidyselect_1.1.1           
  [5] htmlwidgets_1.5.3           grid_4.1.0                 
  [7] Rtsne_0.15                  munsell_0.5.0              
  [9] codetools_0.2-17            ica_1.0-2                  
 [11] miniUI_0.1.1.1              withr_2.4.2                
 [13] colorspace_2.0-1            Biobase_2.52.0             
 [15] highr_0.9                   knitr_1.33                 
 [17] rstudioapi_0.13             stats4_4.1.0               
 [19] SingleCellExperiment_1.14.0 ROCR_1.0-11                
 [21] tensor_1.5                  listenv_0.8.0              
 [23] MatrixGenerics_1.4.0        labeling_0.4.2             
 [25] git2r_0.28.0                GenomeInfoDbData_1.2.6     
 [27] polyclip_1.10-0             bit64_4.0.5                
 [29] farver_2.1.0                rprojroot_2.0.2            
 [31] parallelly_1.25.0           vctrs_0.3.8                
 [33] generics_0.1.0              xfun_0.23                  
 [35] R6_2.5.0                    GenomeInfoDb_1.28.0        
 [37] rsvd_1.0.5                  hdf5r_1.3.3                
 [39] bitops_1.0-7                spatstat.utils_2.1-0       
 [41] DelayedArray_0.18.0         assertthat_0.2.1           
 [43] promises_1.2.0.1            scales_1.1.1               
 [45] gtable_0.3.0                globals_0.14.0             
 [47] goftest_1.2-2               rlang_0.4.11               
 [49] splines_4.1.0               lazyeval_0.2.2             
 [51] spatstat.geom_2.1-0         broom_0.7.6                
 [53] BiocManager_1.30.15         yaml_2.2.1                 
 [55] reshape2_1.4.4              abind_1.4-5                
 [57] modelr_0.1.8                backports_1.2.1            
 [59] httpuv_1.6.1                tools_4.1.0                
 [61] ellipsis_0.3.2              spatstat.core_2.1-2        
 [63] jquerylib_0.1.4             RColorBrewer_1.1-2         
 [65] BiocGenerics_0.38.0         ggridges_0.5.3             
 [67] Rcpp_1.0.6                  plyr_1.8.6                 
 [69] zlibbioc_1.38.0             RCurl_1.98-1.3             
 [71] rpart_4.1-15                deldir_0.2-10              
 [73] pbapply_1.4-3               cowplot_1.1.1              
 [75] S4Vectors_0.30.0            zoo_1.8-9                  
 [77] SummarizedExperiment_1.22.0 haven_2.4.1                
 [79] ggrepel_0.9.1               cluster_2.1.2              
 [81] fs_1.5.0                    data.table_1.14.0          
 [83] scattermore_0.7             lmtest_0.9-38              
 [85] reprex_2.0.0                RANN_2.6.1                 
 [87] mvtnorm_1.1-1               whisker_0.4                
 [89] fitdistrplus_1.1-3          matrixStats_0.58.0         
 [91] hms_1.1.0                   mime_0.10                  
 [93] evaluate_0.14               xtable_1.8-4               
 [95] mclust_5.4.7                readxl_1.3.1               
 [97] IRanges_2.26.0              gridExtra_2.3              
 [99] compiler_4.1.0              KernSmooth_2.23-20         
[101] crayon_1.4.1                htmltools_0.5.1.1          
[103] mgcv_1.8-35                 later_1.2.0                
[105] lubridate_1.7.10            DBI_1.1.1                  
[107] dbplyr_2.1.1                MASS_7.3-54                
[109] Matrix_1.3-3                cli_2.5.0                  
[111] parallel_4.1.0              igraph_1.2.6               
[113] GenomicRanges_1.44.0        pkgconfig_2.0.3            
[115] plotly_4.9.3                spatstat.sparse_2.0-0      
[117] xml2_1.3.2                  bslib_0.2.5.1              
[119] XVector_0.32.0              rvest_1.0.0                
[121] digest_0.6.27               sctransform_0.3.2          
[123] RcppAnnoy_0.0.18            spatstat.data_2.1-0        
[125] rmarkdown_2.8               cellranger_1.1.0           
[127] leiden_0.3.7                uwot_0.1.10                
[129] shiny_1.6.0                 lifecycle_1.0.0            
[131] nlme_3.1-152                jsonlite_1.7.2             
[133] viridisLite_0.4.0           fansi_0.4.2                
[135] pillar_1.6.1                lattice_0.20-44            
[137] fastmap_1.1.0               httr_1.4.2                 
[139] survival_3.2-11             glue_1.4.2                 
[141] remotes_2.3.0               png_0.1-7                  
[143] bit_4.0.4                   stringi_1.6.2              
[145] sass_0.4.0                  renv_0.13.2                
[147] irlba_2.3.3                 future.apply_1.7.0