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Knit directory: MS_lesions/
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source('code/ms00_utils.R')
library("knitr")
UMAP
applied to subset of 100k cells (subset because of memory limits), using parameters min_dist = 1, spread = 2
, otherwise defaults. Clusters are determined by Louvain clustering applied to the conos
graph, followed by post-hoc splitting of two clusters based on biological expectations (COPs and immune cells), and merging of very similar clusters (using SCCAF
).
include_graphics("figure/ms12_markers.Rmd/plot_umap_final_celltypes_sel-1.png", error = FALSE)
UMAP
for all celltypes annotated with MS / CTR and WM / GM.
include_graphics("figure/ms08_modules.Rmd/plot_umap_ctr_ms-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
7a285b7 | wmacnair | 2022-02-14 |
UMAP
plot of just oligodendrocyte and OPC celltypes.
include_graphics("figure/ms08_modules.Rmd/plot_umap_oligos-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
7a285b7 | wmacnair | 2022-02-14 |
Median oNMF
module score per fine celltype for OPC and oligo modules and cells. Columns are scaled to have max value equal to 1.
include_graphics("figure/ms08_modules.Rmd/plot_scores_by_type_scaled-1.png", error = FALSE)
PAGA
applied to oligodendrocytes and OPCs / COPs across all samples.
include_graphics("figure/ms11_paga.Rmd/plot_paga_olg_wm_gm-1.png", error = FALSE)
include_graphics("figure/ms99_deg_figures_gm.Rmd/plot_de_barplot_broad-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
2b68ff2 | wmacnair | 2022-02-16 |
include_graphics("figure/ms99_deg_figures_wm.Rmd/plot_de_barplot_broad-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
2b68ff2 | wmacnair | 2022-02-16 |
Dotplot of Hallmark module results for GM and WM.
include_graphics("figure/ms99_deg_figures_wm.Rmd/plot_gsea_dotplot_gm_wm-1.png", error = FALSE)
Heatmap of logFCs for interferon genes significant in oligodendroglia.
include_graphics("figure/ms99_deg_figures_wm.Rmd/plot_heatmap_logfcs-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
8e47b9f | wmacnair | 2022-02-18 |
Genetic enrichment of differentially expressed genes.
include_graphics("figure/additional_figures/de_barplots.png", error = FALSE)
Version | Author | Date |
---|---|---|
645d04b | wmacnair | 2022-03-06 |
Clustering of WM fold change profiles. Restricted to genes where at least one lesion type has FDR < 5%. Clusters split so that average logFC difference between clusters is > log(4); clusters with fewer than 5 genes not shown; clusters ordered in descending order of mean logFC.
include_graphics("figure/ms99_deg_figures_wm.Rmd/plot_fc_cluster_profiles_sel-1.png", error = FALSE)
Expression heatmap of WM genes, ordered by lesion type.
include_graphics("figure/ms15_mofa_wm.Rmd/fig_overview_expression-4.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Clustered expression heatmap of WM genes.
include_graphics("figure/ms15_mofa_wm.Rmd/fig_overview_expression-2.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Proportions of fine celltypes in healthy GM and healthy WM. Neuronal celltypes excluded. Negative binomial model fit to absolute numbers for each celltype, using total number of cells in sample as offset. FDR calculated across all celltypes.
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_wm_vs_gm-1.png", error = FALSE)
Contribution to variability in celltype abundances explained by lesion + patient in WM.
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_lrt_results-1.png", error = FALSE)
Contribution to variability in celltype abundances explained by lesion + patient in GM, including 4 layer PCs.
# include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_lrt_results-2.png", error = FALSE)
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_lrt_results-6.png", error = FALSE)
Differential abundance results for WM.
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_bootstraps_lesions_signif-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
270e5fc | wmacnair | 2021-11-26 |
Differential abundance results for GM (with layers factored out).
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_bootstraps_lesions_signif-6.png", error = FALSE)
Version | Author | Date |
---|---|---|
270e5fc | wmacnair | 2021-11-26 |
Patient stratification via MOFA factors.
include_graphics("figure/ms15_mofa_wm.Rmd/plot_factors_heatmap_few-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Factor 1 top genes
include_graphics("figure/ms15_mofa_wm.Rmd/fig_factor1-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Factor 3 top genes
include_graphics("figure/ms15_mofa_wm.Rmd/fig_factor3-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Factor 5 top genes
include_graphics("figure/ms15_mofa_wm.Rmd/fig_factor5-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Summary of numbers of nuclei, samples and donors excluded and retained by QC procedure, split by various metadata labels. Distributions of metadata labels split by control and MS samples: age_cat is age at death binned into categories; yrs_w_ms is years with MS, binned into categories, and NA for control samples; pmi_cat is post mortem interval, binned into categories; brain_bank is the sample source; and seq_pool is the batch in which the samples were sequenced.
include_graphics("figure/ms03_SampleQC_summary.Rmd/plot_totals_split_by_meta-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
aedfb86 | wmacnair | 2022-02-09 |
Distributions of metadata labels split by control and MS samples. pmi_minutes is post mortem interval in minutes.
include_graphics("figure/ms03_SampleQC_summary.Rmd/plot_ctrl_vs_ms_metadata-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
aedfb86 | wmacnair | 2022-02-09 |
Summary of QC metrics of post-QC WM samples. donor is colour for donor ID, with grey values used for donors contributing only one sample; mito pct is the proportion of reads in the sample that are mitochondrial; pct unspliced is the proportion of reads in the sample that are unspliced as opposed to spliced mRNA. Colours in heatmap are the z-scores for each QC metric column, with colours chosen so that red is good and blue is bad (e.g. low library size, or high mitochondrial read percentage).
include_graphics("figure/ms03_SampleQC_summary.Rmd/plot_qc_summary_heatmap-1.png", error = FALSE)
Summary of QC metrics of post-QC GM samples, as for ED1c.
include_graphics("figure/ms03_SampleQC_summary.Rmd/plot_qc_summary_heatmap-2.png", error = FALSE)
Version | Author | Date |
---|---|---|
fcc465f | wmacnair | 2022-02-11 |
QC metric summaries for fine celltypes. Each point is a sample with >= 10 nuclei of that type, showing median QC metric value for those nuclei in that sample (with exception of number of nuclei).
include_graphics("figure/ms13_labelling.Rmd/plot_qc_stats_by_cluster-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
aedfb86 | wmacnair | 2022-02-09 |
UMAP
embedding (as in Fig. 1b) annotated with proportion of nuclei in binned region of UMAP
embedding coming from MS as opposed to control samples (left) and WM as opposed to GM samples (right). In both plots, white corresponds to the average proportion across all cells (i.e. 20% of nuclei are from MS samples, and 60% of nuclei are from GM samples).
include_graphics("figure/ms08_modules.Rmd/plot_umap_ctr_ms-1.png", error = FALSE)
Expression of marker genes selected for broad celltypes, and for fine celltypes. CPM indicates counts per million, number of counts of gene divided by total number of pseudobulk counts. Expression calculated across all cells and samples.
include_graphics("figure/ms12_markers.Rmd/plot_dotplot_dheeraj_compact-1.png", error = FALSE)
Comparison of clusters with Seurat clusters.
include_graphics("figure/additional_figures/Conos_celltypes_perc_of_cells_in_Seurat.png", error = FALSE)
include_graphics("figure/ms13_labelling.Rmd/plot_cluster_entropies-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
ed9415e | wmacnair | 2022-02-10 |
Expression of top genes for each oligo-OPC module (gene selected if weight >2%). Expression calculated across all cells and samples.
include_graphics("figure/ms08_modules.Rmd/plot_genes_dotplot-2.png", error = FALSE)
Distribution of model fits for genes for each broad celltype in GM. y-axis shows standard deviation of random (donor) effects for each gene. x-axis shows log2FC of lesion type with smallest p-value for each gene. Horizontal dashed lines show cutoff at SD = log(1.5); vertical dashed lines show cutoff at abs(log2FC) = log(1.5).
include_graphics("figure/ms15_mofa_gm.Rmd/fig_interesting_gs-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Distribution of model fits for genes for each broad celltype in WM. y-axis shows standard deviation of random (donor) effects for each gene. x-axis shows log2FC of lesion type with smallest p-value for each gene. Horizontal dashed lines show cutoff at SD = log(1.5); vertical dashed lines show cutoff at abs(log2FC) = log(1.5).
include_graphics("figure/ms15_mofa_wm.Rmd/fig_interesting_gs-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
include_graphics("figure/ms99_deg_figures_gm.Rmd/plot_de_barplot_fine-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
2b68ff2 | wmacnair | 2022-02-16 |
Heatmap of logFCs of selected genes in excitatory neurons in GM.
include_graphics("figure/ms99_deg_figures_gm.Rmd/plot_heatmap_logfcs-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
8e47b9f | wmacnair | 2022-02-18 |
include_graphics("figure/ms99_deg_figures_wm.Rmd/plot_de_barplot_fine-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
2b68ff2 | wmacnair | 2022-02-16 |
Clustered expression heatmap of GM genes.
include_graphics("figure/ms15_mofa_gm.Rmd/fig_overview_expression-2.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Cartoon giving intuition of how MOFA+ identifies tissue-level factors.
include_graphics("figure/additional_figures/mofa_cartoon_2022-02-04.png", error = FALSE)
First panel shows variation in expression for each celltype explained by MOFA+ factors in GM; second panel shows extent to which MOFA+ factors can be accounted for by metadata. Variance explained in first panel is per celltype, so the maximum total for each row is 100%. Pseudo-R2 values are calculated by fitting a mixed model to each factor, using model factor_value ~ lesion_type + sex + age_scale + pmi_cat + (1 | donor_id), and the glmmTMB
function in package glmmTMB
. Pseudo-R2 values are determined by Nakagawa’s R2, showing proportion of variance explained using fixed components only, and including a donor effect (see Methods).
include_graphics("figure/ms15_mofa_gm.Rmd/fig_factor_r2s-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
As for S6B, for WM.
include_graphics("figure/ms15_mofa_wm.Rmd/fig_factor_r2s-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Distributions of MOFA factors in GM. Colour denotes donor; grey is used where only one sample was obtained from a donor.
include_graphics("figure/ms15_mofa_gm.Rmd/fig_mofa_factors_lesions-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Factor 1 top genes in GM.
include_graphics("figure/ms15_mofa_gm.Rmd/fig_factor1-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Pairwise distributions of MOFA factors in GM. Colour denotes donor; grey is used where only one sample was obtained from a donor.
include_graphics("figure/ms15_mofa_gm.Rmd/plot_factors_pairwise-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Pairwise distributions of MOFA factors in WM. Colour denotes donor; grey is used where only one sample was obtained from a donor.
include_graphics("figure/ms15_mofa_wm.Rmd/plot_factors_pairwise-1.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Expression of marker genes identified for astrocytes. Expression calculated across all cells and samples.
include_graphics("figure/ms08_modules.Rmd/plot_genes_dotplot-6.png", error = FALSE)
Immunohistochemistry validation of number of GPR17-expressing cells in different lesion types.
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_no_gpr17_cells-1.png", error = FALSE)
Proportions of neuronal compartment per sample, split by layer-specificity of neurons. L1 and L2/L3 neurons account for relatively low proportions of NAGM samples, while L5 and L6 neurons account for high proportions of NAGM samples; vice versa for GML samples, while ctrl GM lies in the middle. This indicates that, on average, the samples are roughly ordered as follows: NAGM is deeper than ctrl GM, which is deeper than GML.
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_propns_layers-1.png", error = FALSE)
Principal components of GM neuronal layer centred log ratios (CLRs; see Methods). y-axis shows absolute Spearman correlation between PC loadings and neuronal layer numbers (excluding neuronal clusters without an assigned layer number). x-axis shows the variance explained by each PC (on a log scale). Dashed lines show thresholds at 0.2 Spearman correlation, and 1% variance explained, giving up to 7 PCs that could be relevant to layers.
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_layer_var_exp-1.png", error = FALSE)
Bootstrapped ANCOM-BC results including varying numbers of PCs as covariates. Number of PCs used varies from 0 to 7 (see S4B for rationale for 7). Grey lines show 95% bootstrapped confidence interval, coloured lines show 80% confidence interval; based on 20k bootstraps (large number taken to give reliable estimates of tails; see [ref: Hesterberg 2011]).
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_effect_of_pcs_lesions-1.png", error = FALSE)
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_effect_of_pcs_lesions-2.png", error = FALSE)
[“To infer potential mechanisms, we examined the genes whose changes in expression were responsible for each factor, and noted that genes in each cell type that contribute to individual factors are mostly not shared between cell types, suggesting coordinated tissue-level responses”]
[Heatmaps of expression of top 20-50 genes from each of the 8 broad cell type contributing to each of the 5 factors. 8 cell types x 5 factors= 40 heatmaps in one PDF/r markdown]
[DEGs for each broad cell type (fdr <0.01 & log FC > 1.5) with same annotation (specific to cell types, shared between lesions within a cell type and shared between cell types)]
[MAGMA MS genes (fdr < 0.05) which are DEGs in pericytes, endo and opc/cops]
Proportions of all non-contaminated genes with MS effect and / or donor effect, in WM. MS effect defined as: FDR < 1% for at least one lesion type, and abs(logFC) > log(1.5) (i.e. expression change of +/-50%). Donor effect defined as: ANOVA for inclusion of random effect in model has FDR < 1%, and SD(random effects) > log(1.5).
include_graphics("figure/ms99_deg_figures_wm.Rmd/plot_causes_of_variability-1.png", error = FALSE)
Proportions of all non-contaminated genes with MS effect and / or donor effect, in GM. MS effect defined as: FDR < 1% for at least one lesion type, and abs(logFC) > log(1.5) (i.e. expression change of +/-50%). Donor effect defined as: ANOVA for inclusion of random effect in model has FDR < 1%, and SD(random effects) > log(1.5).
include_graphics("figure/ms99_deg_figures_gm.Rmd/plot_causes_of_variability-1.png", error = FALSE)
[show absence of WM oligo pattern in GM: maybe take WM PCs, apply to GM?]
[IN PRODUCTION: plot extent of overlap between factor genes in WM]
DA results for GM, no layers
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_bootstraps_lesions-2.png", error = FALSE)
GM oligodendroglia proportions barplot
include_graphics("figure/ms09_ancombc_mixed.Rmd/plot_sample_splits_bars_oligos-2.png", error = FALSE)
Illustration of random effects model
include_graphics("figure/ms15_mofa_wm.Rmd/fig_random_effects_example-3.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
Manhattan plot of MAGMA differentially expressed genes
include_graphics("figure/gwas_figures/manhattan.png", error = FALSE)
Version | Author | Date |
---|---|---|
b1e52a7 | wmacnair | 2022-01-06 |
Example of a coloc gene that is differentially expressed
include_graphics("figure/gwas_figures/coloc_example_gene_NR1H3_microglia.png", error = FALSE)
Version | Author | Date |
---|---|---|
b1e52a7 | wmacnair | 2022-01-06 |
Patient stratification
include_graphics("figure/ms15_mofa_wm.Rmd/fig_f1_vs_f2-3.png", error = FALSE)
Version | Author | Date |
---|---|---|
74935aa | wmacnair | 2022-03-06 |
devtools::session_info()
- Session info ---------------------------------------------------------------
setting value
version R version 4.0.5 (2021-03-31)
os CentOS Linux 7 (Core)
system x86_64, linux-gnu
ui X11
language (EN)
collate en_US.UTF-8
ctype C
tz Europe/Zurich
date 2022-02-21
- Packages -------------------------------------------------------------------
package * version date lib source
assertthat * 0.2.1 2019-03-21 [2] CRAN (R 4.0.0)
BiocManager 1.30.16 2021-06-15 [1] CRAN (R 4.0.3)
BiocStyle * 2.18.1 2020-11-24 [1] Bioconductor
bslib 0.3.1 2021-10-06 [2] CRAN (R 4.0.5)
cachem 1.0.6 2021-08-19 [1] CRAN (R 4.0.5)
callr 3.7.0 2021-04-20 [2] CRAN (R 4.0.3)
cellranger 1.1.0 2016-07-27 [2] CRAN (R 4.0.0)
circlize * 0.4.13 2021-06-09 [1] CRAN (R 4.0.3)
cli 3.0.1 2021-07-17 [1] CRAN (R 4.0.3)
codetools 0.2-18 2020-11-04 [2] CRAN (R 4.0.3)
colorout * 1.2-2 2021-04-15 [1] Github (jalvesaq/colorout@79931fd)
colorspace 2.0-2 2021-06-24 [1] CRAN (R 4.0.3)
crayon 1.4.1 2021-02-08 [2] CRAN (R 4.0.3)
data.table * 1.14.2 2021-09-27 [2] CRAN (R 4.0.5)
DBI 1.1.1 2021-01-15 [2] CRAN (R 4.0.3)
desc 1.4.0 2021-09-28 [1] CRAN (R 4.0.5)
devtools 2.4.2 2021-06-07 [1] CRAN (R 4.0.3)
digest 0.6.28 2021-09-23 [2] CRAN (R 4.0.5)
dplyr 1.0.7 2021-06-18 [2] CRAN (R 4.0.3)
ellipsis 0.3.2 2021-04-29 [2] CRAN (R 4.0.3)
evaluate 0.14 2019-05-28 [2] CRAN (R 4.0.0)
fansi 0.5.0 2021-05-25 [2] CRAN (R 4.0.3)
fastmap 1.1.0 2021-01-25 [2] CRAN (R 4.0.3)
forcats * 0.5.1 2021-01-27 [2] CRAN (R 4.0.3)
fs 1.5.0 2020-07-31 [2] CRAN (R 4.0.2)
generics 0.1.1 2021-10-25 [2] CRAN (R 4.0.5)
ggplot2 * 3.3.5 2021-06-25 [1] CRAN (R 4.0.3)
git2r 0.28.0 2021-01-10 [1] CRAN (R 4.0.3)
GlobalOptions 0.1.2 2020-06-10 [1] CRAN (R 4.0.3)
glue 1.4.2 2020-08-27 [2] CRAN (R 4.0.3)
gridExtra 2.3 2017-09-09 [2] CRAN (R 4.0.0)
gtable 0.3.0 2019-03-25 [2] CRAN (R 4.0.0)
highr 0.9 2021-04-16 [2] CRAN (R 4.0.3)
htmltools 0.5.2 2021-08-25 [2] CRAN (R 4.0.5)
httpuv 1.6.3 2021-09-09 [2] CRAN (R 4.0.5)
jquerylib 0.1.4 2021-04-26 [2] CRAN (R 4.0.3)
jsonlite 1.7.2 2020-12-09 [2] CRAN (R 4.0.3)
knitr * 1.36 2021-09-29 [1] CRAN (R 4.0.5)
later 1.3.0 2021-08-18 [2] CRAN (R 4.0.5)
lifecycle 1.0.1 2021-09-24 [2] CRAN (R 4.0.5)
magrittr * 2.0.1 2020-11-17 [1] CRAN (R 4.0.3)
memoise 2.0.0 2021-01-26 [1] CRAN (R 4.0.3)
munsell 0.5.0 2018-06-12 [2] CRAN (R 4.0.0)
pillar 1.6.4 2021-10-18 [1] CRAN (R 4.0.5)
pkgbuild 1.2.0 2020-12-15 [1] CRAN (R 4.0.3)
pkgconfig 2.0.3 2019-09-22 [2] CRAN (R 4.0.0)
pkgload 1.2.3 2021-10-13 [2] CRAN (R 4.0.5)
prettyunits 1.1.1 2020-01-24 [2] CRAN (R 4.0.0)
processx 3.5.2 2021-04-30 [2] CRAN (R 4.0.3)
promises 1.2.0.1 2021-02-11 [2] CRAN (R 4.0.3)
ps 1.6.0 2021-02-28 [2] CRAN (R 4.0.3)
purrr 0.3.4 2020-04-17 [2] CRAN (R 4.0.0)
R6 2.5.1 2021-08-19 [2] CRAN (R 4.0.5)
RColorBrewer * 1.1-2 2014-12-07 [2] CRAN (R 4.0.0)
Rcpp 1.0.7 2021-07-07 [1] CRAN (R 4.0.3)
readxl * 1.3.1 2019-03-13 [2] CRAN (R 4.0.0)
remotes 2.4.1 2021-09-29 [1] CRAN (R 4.0.5)
rlang 0.4.12 2021-10-18 [2] CRAN (R 4.0.5)
rmarkdown 2.11 2021-09-14 [1] CRAN (R 4.0.5)
rprojroot 2.0.2 2020-11-15 [2] CRAN (R 4.0.3)
sass 0.4.0 2021-05-12 [2] CRAN (R 4.0.3)
scales * 1.1.1 2020-05-11 [2] CRAN (R 4.0.0)
sessioninfo 1.1.1 2018-11-05 [1] CRAN (R 4.0.3)
shape 1.4.6 2021-05-19 [1] CRAN (R 4.0.1)
stringi 1.7.4 2021-08-25 [1] CRAN (R 4.0.5)
stringr * 1.4.0 2019-02-10 [2] CRAN (R 4.0.0)
testthat 3.1.0 2021-10-04 [2] CRAN (R 4.0.5)
tibble 3.1.5 2021-09-30 [1] CRAN (R 4.0.5)
tidyselect 1.1.1 2021-04-30 [2] CRAN (R 4.0.3)
usethis 2.1.2 2021-10-25 [1] CRAN (R 4.0.5)
utf8 1.2.2 2021-07-24 [1] CRAN (R 4.0.3)
vctrs 0.3.8 2021-04-29 [2] CRAN (R 4.0.3)
viridis * 0.6.2 2021-10-13 [1] CRAN (R 4.0.5)
viridisLite * 0.4.0 2021-04-13 [1] CRAN (R 4.0.1)
whisker 0.4 2019-08-28 [1] CRAN (R 4.0.3)
withr 2.4.2 2021-04-18 [2] CRAN (R 4.0.3)
workflowr * 1.6.2 2020-04-30 [1] CRAN (R 4.0.3)
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yaml 2.2.1 2020-02-01 [2] CRAN (R 4.0.3)
[1] /pstore/home/macnairw/lib/conda_r3.12
[2] /pstore/home/macnairw/.conda/envs/r_4.0.3/lib/R/library
sessionInfo()
R version 4.0.5 (2021-03-31)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
BLAS/LAPACK: /pstore/home/macnairw/.conda/envs/r_4.0.3/lib/libopenblasp-r0.3.12.so
locale:
[1] LC_CTYPE=C LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] knitr_1.36 readxl_1.3.1 forcats_0.5.1 ggplot2_3.3.5
[5] scales_1.1.1 viridis_0.6.2 viridisLite_0.4.0 assertthat_0.2.1
[9] stringr_1.4.0 data.table_1.14.2 magrittr_2.0.1 circlize_0.4.13
[13] RColorBrewer_1.1-2 BiocStyle_2.18.1 colorout_1.2-2 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.7 prettyunits_1.1.1 ps_1.6.0
[4] rprojroot_2.0.2 digest_0.6.28 utf8_1.2.2
[7] R6_2.5.1 cellranger_1.1.0 evaluate_0.14
[10] highr_0.9 pillar_1.6.4 GlobalOptions_0.1.2
[13] rlang_0.4.12 callr_3.7.0 whisker_0.4
[16] jquerylib_0.1.4 rmarkdown_2.11 desc_1.4.0
[19] devtools_2.4.2 munsell_0.5.0 compiler_4.0.5
[22] httpuv_1.6.3 xfun_0.27 pkgconfig_2.0.3
[25] pkgbuild_1.2.0 shape_1.4.6 htmltools_0.5.2
[28] tidyselect_1.1.1 tibble_3.1.5 gridExtra_2.3
[31] codetools_0.2-18 fansi_0.5.0 crayon_1.4.1
[34] dplyr_1.0.7 withr_2.4.2 later_1.3.0
[37] grid_4.0.5 jsonlite_1.7.2 gtable_0.3.0
[40] lifecycle_1.0.1 DBI_1.1.1 git2r_0.28.0
[43] cli_3.0.1 stringi_1.7.4 cachem_1.0.6
[46] remotes_2.4.1 fs_1.5.0 promises_1.2.0.1
[49] testthat_3.1.0 bslib_0.3.1 ellipsis_0.3.2
[52] generics_0.1.1 vctrs_0.3.8 tools_4.0.5
[55] glue_1.4.2 purrr_0.3.4 pkgload_1.2.3
[58] processx_3.5.2 fastmap_1.1.0 yaml_2.2.1
[61] colorspace_2.0-2 BiocManager_1.30.16 sessioninfo_1.1.1
[64] memoise_2.0.0 usethis_2.1.2 sass_0.4.0