Last updated: 2022-02-21
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Knit directory: MS_lesions/
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File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | 9d454a9 | wmacnair | 2022-02-16 | Add oligo module umap plot |
html | 9d454a9 | wmacnair | 2022-02-16 | Add oligo module umap plot |
Rmd | 7a285b7 | wmacnair | 2022-02-14 | Update UMAP calculations |
html | 7a285b7 | wmacnair | 2022-02-14 | Update UMAP calculations |
Rmd | d2a327c | wmacnair | 2022-01-20 | Fix module ordering |
html | d2a327c | wmacnair | 2022-01-20 | Fix module ordering |
Rmd | 1d30bcb | wmacnair | 2022-01-17 | Add broad-level module analysis to ms08_modules |
html | 1d30bcb | wmacnair | 2022-01-17 | Add broad-level module analysis to ms08_modules |
Rmd | 9af1539 | wmacnair | 2021-12-13 | Save GO terms associated with modules |
html | 9af1539 | wmacnair | 2021-12-13 | Save GO terms associated with modules |
html | 7fb1b95 | wmacnair | 2021-11-25 | Host with GitLab. |
Rmd | 7ddc417 | Macnair | 2021-09-24 | Add pseudobulk version of modules |
Rmd | 2b5e1cc | Macnair | 2021-09-03 | Tweak ms08_modules |
Rmd | 1342e46 | Macnair | 2021-08-24 | Update module analysis |
Rmd | eef8a1c | Macnair | 2021-04-29 | Minor tweaks to allow rerunning on Roche servers |
Rmd | 129c53d | Macnair | 2021-04-16 | Renamed a lot of things to add ms07_soup |
source('code/ms00_utils.R')
source('code/ms08_modules.R')
source_python('code/ms08_modules.py')
# base inputs
sce_f = 'data/sce_raw/ms_sce.rds'
labels_f = 'data/byhand_markers/validation_markers_2021-05-31.csv'
labelled_f = 'output/ms13_labelling/conos_labelled_2021-05-31.txt.gz'
meta_f = "data/metadata/metadata_checked_assumptions_2021-10-08.xlsx"
# define pseudobulk files
soup_dir = 'output/ms07_soup'
date_soup = '2021-06-01'
pb_fine_f = sprintf('%s/pb_sum_fine_%s.rds', soup_dir, date_soup)
prop_fine_f = sprintf('%s/pb_prop_fine_%s.rds', soup_dir, date_soup)
# broad level pseudobulk files
pb_broad_f = file.path(soup_dir, 'pb_sum_broad_2021-06-01.rds')
pb_fine_f = file.path(soup_dir, 'pb_sum_fine_2021-06-01.rds')
prop_fine_f = file.path(soup_dir, 'pb_prop_fine_2021-06-01.rds')
pb_soup_f = file.path(soup_dir, 'pb_soup_broad_maximum_2021-06-01.rds')
gtf_f = 'data/gtf/Homo_sapiens.GRCh38.96.filtered.preMRNA.gtf'
# set up directory
save_dir = 'output/ms08_modules'
date_tag = '2021-08-18'
if (!dir.exists(save_dir))
dir.create(save_dir)
n_cores = 16
# define parameters for running UMAP multiple times
conos_dir = 'output/ms04_conos'
conos_tag = '2021-02-11'
graph_f = sprintf('%s/conos_graph_%s.txt', conos_dir, conos_tag)
n_per_conos = 200
n_per_olg = 500
spread_list = c(1, 2, 4, 8)
min_list = c(1e-2, 1e-1, 1e-0)
umap_many_f = sprintf('%s/conos_umap_sub_%s.txt', save_dir, date_tag)
umap_olgs_f = sprintf('%s/conos_umap_oligo_opc_%s.txt', save_dir, date_tag)
# output file patterns
genes_pat = sprintf('%s/%s/features_%s_%s.tsv', save_dir, '%s', date_tag, '%s')
mtx_pat = sprintf('%s/%s/counts_%s_%s.mtx', save_dir, '%s', date_tag, '%s')
sce_pat = sprintf('%s/%s/sce_sub_%s_%s.rds', save_dir, '%s', date_tag, '%s')
ok_gs_pat = sprintf('%s/%s/ok_gs_%s_%s.txt', save_dir, '%s', date_tag, '%s')
pop_pat = sprintf('%s/%s/pop_%s_%s.p', save_dir, '%s', '%s', date_tag)
res_pat = sprintf('%s/%s/res_%s_%s.rds', save_dir, '%s', date_tag, '%s')
go_pat = sprintf('%s/%s/go_dt_%s_%s_%s.rds', save_dir, '%s', date_tag, '%s', '%s')
# lists of celltypes for each run
spec_list = list(
oligo_opc = list(type_broad = c('OPCs / COPs', 'Oligodendrocytes')),
micro_immune = list(type_broad = c('Microglia', 'Immune')),
excitatory = list(type_broad = 'Excitatory neurons'),
inhibitory = list(type_broad = 'Inhibitory neurons'),
astrocytes = list(type_broad = c('Astrocytes')),
endo_stromal = list(type_broad = c('Endothelial cells', 'Pericytes')),
microglia = list(type_broad = c('Microglia')),
immune = list(type_broad = c('Immune'))
)
assert_that(length(spec_list) == length(unique(names(spec_list))))
[1] TRUE
group_list = names(spec_list)
# how many per fine celltype?
n_sample = 2e3
n_genes = 2e3
max_soup = 0.1
ok_types = 'protein_coding'
# define spec for broad level markers
broad_spec = list(broad_level = list(type_broad = broad_ord))
broad_name = names(broad_spec)
n_per_broad = 5e2
all_list = c(broad_name, group_list)
# umap params
umap_ps = list(
min_dist = 1,
spread = 2
)
# define xls file to save
xl_f = sprintf('%s/modules_genes_%s.xlsx', save_dir, date_tag)
go_xl_f = sprintf('%s/modules_go_terms_%s.xlsx', save_dir, date_tag)
labels_dt = load_names_dt(labels_f) %>%
.[, cluster_id := type_fine]
meta_dt = load_meta_dt_from_xls(meta_f)
conos_dt = load_labelled_dt(labelled_f, labels_f) %>%
.[, conos := NULL ]
pb_soup = pb_soup_f %>% readRDS
pb_broad = pb_broad_f %>% readRDS
contam_dt = calc_contam_dt(pb_soup, pb_broad, min_cells = 10)
rm(pb_soup, pb_broad)
biotypes_dt = get_biotypes_dt(gtf_f)
fine_dt = load_fine_dt(pb_fine_f, prop_fine_f, labels_dt)
set.seed(20210818)
conos_sub = calc_conos_sub(conos_dt, meta_dt,
n_per_conos, meta_vars = 'lesion_type')
umap_all = calc_conos_and_umap_on_subset(conos_sub, sce_f, umap_many_f,
spread_list, min_list, n_cores = n_cores, seed = 20210818)
set.seed(20210818)
conos_olgs = conos_dt[ str_detect(type_broad, c("(Olig|OPC)")) ] %>%
calc_conos_sub(meta_dt, n_per_conos = n_per_olg, meta_vars = 'lesion_type')
umap_olgs = calc_conos_and_umap_on_subset(conos_olgs, sce_f, umap_olgs_f,
spread_list, min_list, n_cores = n_cores, seed = 20210818)
umap_dt = umap_many_f %>% fread %>%
.[ min_dist == umap_ps$min_dist & spread == umap_ps$spread ] %>%
.[, .(cell_id, UMAP1, UMAP2)]
save_sub_sces(spec_list, sce_f, sce_pat, ok_gs_pat, conos_dt, contam_dt,
biotypes_dt, n_sample, n_genes, max_soup, ok_types, save_dir)
already done!
NULL
save_outputs_for_popalign(group_list, sce_pat, mtx_pat, genes_pat)
already done!
NULL
run_onmf(save_dir, date_tag, group_list, ncores = n_cores)
pop_list = group_list %>%
map(~get_pop_results(.x, res_pat, sce_pat, ok_gs_pat, go_pat, pop_pat,
conos_dt)) %>% setNames(group_list)
# save subset and outputs for popalign
save_sub_sces(broad_spec, sce_f, sce_pat, ok_gs_pat, conos_dt, contam_dt,
biotypes_dt, n_per_broad, n_genes, max_soup, ok_types, save_dir)
already done!
NULL
save_outputs_for_popalign(broad_name, sce_pat, mtx_pat, genes_pat)
already done!
NULL
# run onmf
run_onmf(save_dir, date_tag, broad_spec, ncores = n_cores)
# extract results
broad_res = get_pop_results(broad_name, res_pat, sce_pat, ok_gs_pat, go_pat, pop_pat,
conos_dt)
# add to pop_list
pop_list = c(list(broad_res), pop_list) %>% setNames(all_list)
g = broad_name
for (what in c('scaled', 'propns')) {
cat('### ', what, '\n')
hm = plot_scores_by_celltype(pop_list[[g]], what = what)
if (!is.null(hm))
draw(hm, heatmap_legend_side = "bottom")
cat('\n\n')
}
for (g in group_list) {
cat('### ', g, '\n')
hm = plot_scores_by_celltype(pop_list[[g]], what = 'scaled')
if (!is.null(hm))
draw(hm, heatmap_legend_side = "bottom")
cat('\n\n')
}
for (g in group_list) {
cat('### ', g, '\n')
hm = plot_scores_by_celltype(pop_list[[g]], what = 'propns')
if (!is.null(hm))
draw(hm, heatmap_legend_side = "bottom")
cat('\n\n')
}
UMAP
for (g in all_list) {
cat('### ', g, '\n')
print(plot_scores_over_umap(pop_list[[g]]$scores_dt, umap_dt))
cat('\n\n')
}
UMAP
, oligos only(plot_scores_over_umap(pop_list[["oligo_opc"]]$scores_dt, umap_olgs))
Version | Author | Date |
---|---|---|
9d454a9 | wmacnair | 2022-02-16 |
g = broad_name
cat('### ', g, '\n')
print(plot_biggest_genes_dotplot(g, broad_spec,
pop_list[[g]]$w_mat, fine_dt, w2_cut = 0.02))
cat('\n\n')
for (g in group_list) {
cat('### ', g, '\n')
print(plot_biggest_genes_dotplot(g, spec_list, pop_list[[g]]$w_mat,
fine_dt, w2_cut = 0.02))
cat('\n\n')
}
UMAP
for (g in all_list) {
cat('### ', g, '\n')
print(plot_genes_over_umap(pop_list[[g]]$genes_dt, umap_dt))
cat('\n\n')
}
for (g in group_list) {
cat('### ', g, '\n')
hm = plot_scores_by_celltype(pop_list[[g]], what = 'scaled')
if (!is.null(hm))
draw(hm, heatmap_legend_side = "bottom")
cat('\n\n')
}
for (g in all_list) {
cat('### ', g, '\n')
hm = plot_enriched_sets(pop_list[[g]]$go_std_dt)
if (!is.null(hm))
draw(hm, heatmap_legend_side = "bottom")
cat('\n\n')
}
for (g in all_list) {
cat('### ', g, '\n')
hm = plot_enriched_sets(pop_list[[g]]$go_all_dt)
if (!is.null(hm))
draw(hm, heatmap_legend_side = "bottom")
cat('\n\n')
}
UMAP
celltype reference(plot_umap_celltypes(umap_dt, conos_dt))
UMAP
oligodendroglia only(plot_umap_oligos(umap_olgs, conos_dt, umap_ps$min_dist, umap_ps$spread))
UMAP
(all)(plot_celltypes_over_umap(broad_spec[[broad_name]], conos_dt, umap_dt))
UMAP
for (g in group_list) {
cat('### ', g, '\n')
print(plot_celltypes_over_umap(spec_list[[g]], conos_dt, umap_dt))
cat('\n\n')
}
UMAP
CTR/MS and WM/GM status(plot_umap_ctr_ms(umap_dt, meta_dt))
Version | Author | Date |
---|---|---|
7a285b7 | wmacnair | 2022-02-14 |
save_module_genes_to_xl(pop_list, xl_f)
NULL
save_module_go_terms_to_xl(group_list, go_pat, go_xl_f)
NULL
UMAP
g = 'oligo_opc'
sel_genes = c("TNR", "LRP1B", "CAMK2D", "QKI", "NCAM2", "NLGN1", "KIRREL3",
"MBP", "GLUL", "ELL2")
(plot_sel_genes_over_umap(g, pop_list, sce_pat, umap_dt, sel_genes))
devtools::session_info()
Registered S3 method overwritten by 'cli':
method from
print.boxx spatstat.geom
- 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 2022-02-14
- Packages -------------------------------------------------------------------
! package * version date lib
abind 1.4-5 2016-07-21 [2]
annotate 1.68.0 2020-10-27 [1]
AnnotationDbi 1.52.0 2020-10-27 [1]
assertthat * 0.2.1 2019-03-21 [2]
backports 1.2.1 2020-12-09 [2]
beachmat 2.6.4 2020-12-20 [1]
beeswarm 0.4.0 2021-06-01 [1]
Biobase * 2.50.0 2020-10-27 [1]
BiocGenerics * 0.36.1 2021-04-16 [1]
BiocManager 1.30.16 2021-06-15 [1]
BiocNeighbors 1.8.2 2020-12-07 [1]
BiocParallel * 1.24.1 2020-11-06 [1]
BiocSingular 1.6.0 2020-10-27 [1]
BiocStyle * 2.18.1 2020-11-24 [1]
Biostrings 2.58.0 2020-10-27 [1]
bit 4.0.4 2020-08-04 [2]
bit64 4.0.5 2020-08-30 [2]
bitops 1.0-7 2021-04-24 [2]
blme 1.0-5 2021-01-05 [1]
blob 1.2.2 2021-07-23 [2]
boot 1.3-28 2021-05-03 [2]
brew 1.0-6 2011-04-13 [1]
broom 0.7.9 2021-07-27 [2]
bslib 0.3.1 2021-10-06 [2]
cachem 1.0.6 2021-08-19 [1]
Cairo 1.5-12.2 2020-07-07 [2]
callr 3.7.0 2021-04-20 [2]
caTools 1.18.2 2021-03-28 [2]
cellranger 1.1.0 2016-07-27 [2]
circlize * 0.4.13 2021-06-09 [1]
cli 3.0.1 2021-07-17 [1]
clue 0.3-60 2021-10-11 [1]
cluster 2.1.2 2021-04-17 [2]
codetools 0.2-18 2020-11-04 [2]
colorout * 1.2-2 2021-04-15 [1]
colorRamps 2.3 2012-10-29 [1]
colorspace 2.0-2 2021-06-24 [1]
ComplexHeatmap * 2.6.2 2020-11-12 [1]
conos * 1.4.3 2021-08-07 [1]
cowplot 1.1.1 2020-12-30 [2]
crayon 1.4.1 2021-02-08 [2]
data.table * 1.14.2 2021-09-27 [2]
DBI 1.1.1 2021-01-15 [2]
DelayedArray 0.16.3 2021-03-24 [1]
DelayedMatrixStats 1.12.3 2021-02-03 [1]
deldir 1.0-6 2021-10-23 [2]
dendsort 0.3.4 2021-04-20 [1]
desc 1.4.0 2021-09-28 [1]
DESeq2 1.30.1 2021-02-19 [1]
devtools 2.4.2 2021-06-07 [1]
digest 0.6.28 2021-09-23 [2]
doParallel 1.0.16 2020-10-16 [1]
dplyr 1.0.7 2021-06-18 [2]
drat 0.2.1 2021-07-10 [1]
edgeR 3.32.1 2021-01-14 [1]
ellipsis 0.3.2 2021-04-29 [2]
evaluate 0.14 2019-05-28 [2]
fansi 0.5.0 2021-05-25 [2]
farver 2.1.0 2021-02-28 [2]
fastmap 1.1.0 2021-01-25 [2]
fastmatch 1.1-3 2021-07-23 [1]
fgsea * 1.16.0 2020-10-27 [1]
fitdistrplus 1.1-6 2021-09-28 [2]
forcats * 0.5.1 2021-01-27 [2]
foreach 1.5.1 2020-10-15 [2]
fs 1.5.0 2020-07-31 [2]
future * 1.22.1 2021-08-25 [2]
future.apply 1.8.1 2021-08-10 [2]
genefilter 1.72.1 2021-01-21 [1]
geneplotter 1.68.0 2020-10-27 [1]
generics 0.1.1 2021-10-25 [2]
GenomeInfoDb * 1.26.7 2021-04-08 [1]
GenomeInfoDbData 1.2.4 2021-04-15 [1]
GenomicAlignments 1.26.0 2020-10-27 [1]
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RANN 2.6.1 2019-01-08 [2]
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RColorBrewer * 1.1-2 2014-12-07 [2]
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reticulate * 1.22 2021-09-17 [2]
rjson 0.2.20 2018-06-08 [1]
rlang 0.4.12 2021-10-18 [2]
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sctransform 0.3.2 2020-12-16 [2]
scuttle 1.0.4 2020-12-17 [1]
seriation * 1.3.1 2021-10-16 [1]
sessioninfo 1.1.1 2018-11-05 [1]
Seurat * 4.0.5 2021-10-17 [2]
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shape 1.4.6 2021-05-19 [1]
shiny 1.7.1 2021-10-02 [2]
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snakecase 0.11.0 2019-05-25 [1]
sparseMatrixStats 1.2.1 2021-02-02 [1]
spatstat.core 2.3-0 2021-07-16 [2]
spatstat.data 2.1-0 2021-03-21 [2]
spatstat.geom 2.3-0 2021-10-09 [2]
spatstat.sparse 2.0-0 2021-03-16 [2]
spatstat.utils 2.2-0 2021-06-14 [2]
stringi 1.7.4 2021-08-25 [1]
stringr * 1.4.0 2019-02-10 [2]
SummarizedExperiment * 1.20.0 2020-10-27 [1]
survival 3.2-13 2021-08-24 [2]
tensor 1.5 2012-05-05 [2]
testthat 3.1.0 2021-10-04 [2]
tibble 3.1.5 2021-09-30 [1]
tidyr 1.1.4 2021-09-27 [2]
tidyselect 1.1.1 2021-04-30 [2]
TMB 1.7.22 2021-09-28 [1]
triebeard 0.3.0 2016-08-04 [2]
TSP 1.1-11 2021-10-06 [1]
urltools 1.7.3 2019-04-14 [2]
usethis 2.1.2 2021-10-25 [1]
utf8 1.2.2 2021-07-24 [1]
uwot 0.1.10 2020-12-15 [2]
variancePartition 1.20.0 2020-10-27 [1]
vctrs 0.3.8 2021-04-29 [2]
vipor 0.4.5 2017-03-22 [1]
viridis * 0.6.2 2021-10-13 [1]
viridisLite * 0.4.0 2021-04-13 [1]
whisker 0.4 2019-08-28 [1]
withr 2.4.2 2021-04-18 [2]
workflowr * 1.6.2 2020-04-30 [1]
writexl * 1.4.0 2021-04-20 [1]
xfun 0.27 2021-10-18 [1]
XML 3.99-0.8 2021-09-17 [1]
xtable 1.8-4 2019-04-21 [2]
XVector 0.30.0 2020-10-27 [1]
yaml 2.2.1 2020-02-01 [2]
zlibbioc 1.36.0 2020-10-27 [1]
zoo 1.8-9 2021-03-09 [2]
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[1] /pstore/home/macnairw/lib/conda_r3.12
[2] /pstore/home/macnairw/.conda/envs/r_4.0.3/lib/R/library
R -- Package was removed from disk.
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] grid parallel stats4 stats graphics grDevices utils
[8] datasets methods base
other attached packages:
[1] writexl_1.4.0 reticulate_1.22
[3] fgsea_1.16.0 BiocParallel_1.24.1
[5] ggplot.multistats_1.0.0 seriation_1.3.1
[7] ComplexHeatmap_2.6.2 pagoda2_1.0.6
[9] conos_1.4.3 igraph_1.2.7
[11] SeuratObject_4.0.2 Seurat_4.0.5
[13] future_1.22.1 Matrix_1.3-4
[15] SingleCellExperiment_1.12.0 SummarizedExperiment_1.20.0
[17] Biobase_2.50.0 GenomicRanges_1.42.0
[19] GenomeInfoDb_1.26.7 IRanges_2.24.1
[21] S4Vectors_0.28.1 BiocGenerics_0.36.1
[23] MatrixGenerics_1.2.1 matrixStats_0.61.0
[25] purrr_0.3.4 readxl_1.3.1
[27] forcats_0.5.1 ggplot2_3.3.5
[29] scales_1.1.1 viridis_0.6.2
[31] viridisLite_0.4.0 assertthat_0.2.1
[33] stringr_1.4.0 data.table_1.14.2
[35] magrittr_2.0.1 circlize_0.4.13
[37] RColorBrewer_1.1-2 BiocStyle_2.18.1
[39] colorout_1.2-2 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] rsvd_1.0.5 ica_1.0-2
[3] ps_1.6.0 Rsamtools_2.6.0
[5] foreach_1.5.1 lmtest_0.9-38
[7] rprojroot_2.0.2 crayon_1.4.1
[9] spatstat.core_2.3-0 MASS_7.3-54
[11] Matrix.utils_0.9.8 nlme_3.1-153
[13] backports_1.2.1 rlang_0.4.12
[15] XVector_0.30.0 ROCR_1.0-11
[17] irlba_2.3.3 nloptr_1.2.2.2
[19] callr_3.7.0 limma_3.46.0
[21] scater_1.18.6 rjson_0.2.20
[23] bit64_4.0.5 glue_1.4.2
[25] sctransform_0.3.2 pbkrtest_0.5.1
[27] processx_3.5.2 vipor_0.4.5
[29] spatstat.sparse_2.0-0 AnnotationDbi_1.52.0
[31] muscat_1.5.1 spatstat.geom_2.3-0
[33] tidyselect_1.1.1 usethis_2.1.2
[35] fitdistrplus_1.1-6 variancePartition_1.20.0
[37] XML_3.99-0.8 tidyr_1.1.4
[39] zoo_1.8-9 GenomicAlignments_1.26.0
[41] xtable_1.8-4 evaluate_0.14
[43] scuttle_1.0.4 cli_3.0.1
[45] zlibbioc_1.36.0 miniUI_0.1.1.1
[47] whisker_0.4 bslib_0.3.1
[49] rpart_4.1-15 fastmatch_1.1-3
[51] shiny_1.7.1 BiocSingular_1.6.0
[53] xfun_0.27 clue_0.3-60
[55] pkgbuild_1.2.0 cluster_2.1.2
[57] caTools_1.18.2 TSP_1.1-11
[59] tibble_3.1.5 ggrepel_0.9.1
[61] listenv_0.8.0 Biostrings_2.58.0
[63] png_0.1-7 withr_2.4.2
[65] bitops_1.0-7 plyr_1.8.6
[67] cellranger_1.1.0 pillar_1.6.4
[69] gplots_3.1.1 GlobalOptions_0.1.2
[71] cachem_1.0.6 fs_1.5.0
[73] GetoptLong_1.0.5 DelayedMatrixStats_1.12.3
[75] vctrs_0.3.8 ellipsis_0.3.2
[77] generics_0.1.1 urltools_1.7.3
[79] devtools_2.4.2 tools_4.0.5
[81] beeswarm_0.4.0 munsell_0.5.0
[83] DelayedArray_0.16.3 fastmap_1.1.0
[85] compiler_4.0.5 pkgload_1.2.3
[87] abind_1.4-5 httpuv_1.6.3
[89] rtracklayer_1.50.0 sessioninfo_1.1.1
[91] plotly_4.10.0 GenomeInfoDbData_1.2.4
[93] gridExtra_2.3 glmmTMB_1.1.2.3
[95] edgeR_3.32.1 lattice_0.20-45
[97] deldir_1.0-6 utf8_1.2.2
[99] later_1.3.0 dplyr_1.0.7
[101] jsonlite_1.7.2 dendsort_0.3.4
[103] pbapply_1.5-0 sparseMatrixStats_1.2.1
[105] genefilter_1.72.1 lazyeval_0.2.2
[107] promises_1.2.0.1 doParallel_1.0.16
[109] R.utils_2.11.0 goftest_1.2-3
[111] spatstat.utils_2.2-0 brew_1.0-6
[113] rmarkdown_2.11 cowplot_1.1.1
[115] blme_1.0-5 Rtsne_0.15
[117] uwot_0.1.10 Rook_1.1-1
[119] survival_3.2-13 numDeriv_2016.8-1.1
[121] yaml_2.2.1 htmltools_0.5.2
[123] memoise_2.0.0 locfit_1.5-9.4
[125] here_1.0.1 digest_0.6.28
[127] mime_0.12 rappdirs_0.3.3
[129] registry_0.5-1 N2R_0.1.1
[131] RSQLite_2.2.8 future.apply_1.8.1
[133] remotes_2.4.1 blob_1.2.2
[135] R.oo_1.24.0 drat_0.2.1
[137] splines_4.0.5 labeling_0.4.2
[139] Cairo_1.5-12.2 RCurl_1.98-1.5
[141] broom_0.7.9 hms_1.1.1
[143] colorspace_2.0-2 BiocManager_1.30.16
[145] ggbeeswarm_0.6.0 shape_1.4.6
[147] sass_0.4.0 Rcpp_1.0.7
[149] RANN_2.6.1 fansi_0.5.0
[151] parallelly_1.28.1 R6_2.5.1
[153] ggridges_0.5.3 lifecycle_1.0.1
[155] minqa_1.2.4 leiden_0.3.8
[157] testthat_3.1.0 jquerylib_0.1.4
[159] snakecase_0.11.0 desc_1.4.0
[161] RcppAnnoy_0.0.19 iterators_1.0.13
[163] TMB_1.7.22 htmlwidgets_1.5.4
[165] beachmat_2.6.4 polyclip_1.10-0
[167] triebeard_0.3.0 RMTstat_0.3
[169] mgcv_1.8-38 globals_0.14.0
[171] leidenAlg_0.1.1 patchwork_1.1.1
[173] codetools_0.2-18 lubridate_1.8.0
[175] gtools_3.9.2 prettyunits_1.1.1
[177] R.methodsS3_1.8.1 gtable_0.3.0
[179] DBI_1.1.1 git2r_0.28.0
[181] tensor_1.5 httr_1.4.2
[183] highr_0.9 KernSmooth_2.23-20
[185] stringi_1.7.4 progress_1.2.2
[187] reshape2_1.4.4 farver_2.1.0
[189] annotate_1.68.0 hexbin_1.28.2
[191] magick_2.7.3 colorRamps_2.3
[193] sccore_1.0.0 boot_1.3-28
[195] grr_0.9.5 BiocNeighbors_1.8.2
[197] lme4_1.1-27.1 geneplotter_1.68.0
[199] scattermore_0.7 DESeq2_1.30.1
[201] bit_4.0.4 spatstat.data_2.1-0
[203] janitor_2.1.0 pkgconfig_2.0.3
[205] lmerTest_3.1-3 knitr_1.36