Last updated: 2021-04-29

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Knit directory: MS_lesions/

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Rmd b7ecf3b wmacnair 2021-02-15 Finalized cluster splitting and merging, did modules
Rmd 5713884 wmacnair 2021-02-10 Running and checking SCCAF analysis

Setup / definitions

Libraries

Helper functions

source('code/ms00_utils.R')
source('code/ms04_conos.R')
source('code/ms06_sccaf.R')
source_python('code/ms06_sccaf_fns.py')

Inputs

sce_f       = 'data/sce_raw/ms_sce.rds'
qc_dir      = 'output/ms03_SampleQC'
qc_f        = file.path(qc_dir, 'ms_qc_dt.txt')
split_dir   = 'output/ms05_splitting'
split_f     = file.path(split_dir, 'conos_split_2021-02-12.txt')

Outputs

# define save directory
save_dir    = 'output/ms06_sccaf'
# date_tag    = '2021-02-13'
date_tag    = '2021-03-18'
if (!dir.exists(save_dir))
  dir.create(save_dir)

# save marker means
known_f     = sprintf('%s/known_markers_%s.txt', save_dir, date_tag)

# save subsample
set.seed(20210311)
n_per_conos = 2e3
subset_f    = sprintf('%s/ms_sce_subset_%s.rds', save_dir, date_tag)
adata_f     = sprintf('%s/adata_sccaf_%s.h5ad', save_dir, date_tag)

# define 
preds_f     = sprintf('%s/preds_df_%s.csv', save_dir, date_tag)
probs_f     = sprintf('%s/probs_df_%s.csv', save_dir, date_tag)

# how to merge clusters
mrg_custom  = list(
  cns03   = c('cns03', 'cns05'),
  cns24.2 = 'cns24.2',
  cns28.3 = 'cns28.3',
  cns28.4 = 'cns28.4',
  cns55.1 = c('cns55.1', 'cns55.4', 'cns55.5'),
  cns55.3 = 'cns55.3'
  # ,cns33   = c('cns33', 'cns24')
  )
v_cut       = list(single = 0.1, average = 0.1, complete = 0.1)
merges_f    = sprintf('%s/merges_dt_%s.csv', save_dir, date_tag)

# define merged outputs
sel_method  = 'complete'
merged_f    = sprintf('%s/conos_merged_dt_%s.csv', save_dir, date_tag)

# define find markers runs
tests       = c('binom', 't', 'wilcox')
fm_groups   = list(
  oligo         = "Oligodendrocytes", 
  opc           = "OPCs / COPs", 
  astro         = "Astrocytes", 
  micro_immune  = c("Microglia", "Immune"), 
  excit_neuron  = "Excitatory neurons", 
  inhib_neuron  = "Inhibitory neurons", 
  endo_peri     = c("Endothelial cells", "Pericytes")
)
assert_that(all(unlist(fm_groups) %in% broad_ord))
[1] TRUE
fm_pat    = sprintf("%s/fm_merged_%s_%s_%s.txt", save_dir, "%s", "%s", date_tag)
n_cells   = 1000

Load inputs

conos_dt    = split_f %>% fread %>% .[, conos_orig := NULL]

Processing / calculations

labels_dt   = conos_dt[, .(type_broad, conos)] %>% unique %>%
  .[, type_broad := factor(type_broad, levels = broad_ord)]
cns_annots  = calc_cns_annots(conos_dt)
prior_dt      = get_prior_dt()
marker_list   = prior_dt$symbol
marker_exp_dt = calc_marker_exp_dt(marker_list, sce_f, known_f, qc_f, conos_dt,
  cell_ids = conos_dt$cell_id) %>%
  merge(prior_dt, by = 'symbol') %>%
  merge(labels_dt, by = 'conos')
already done! loading
save_sce_subsample(sce_f, conos_dt, n_per_conos, subset_f)
already done!
NULL
make_adata_from_sce(subset_f, adata_f)
already done!
NULL
run_sccaf(adata_f, preds_f, probs_f, n_jobs = 32L)
# get SCCAF outputs
preds_dt    = load_preds_dt(preds_f, labels_dt)
probs_dt    = calc_probs_dt(probs_f, preds_dt)

# prep for plots
confuse_dt  = calc_confuse_dt(preds_dt)
probs_melt  = calc_probs_melt(probs_dt)
pairwise_dt = calc_pairwise_dt(probs_dt, confuse_dt)
  making pairs to compare
  calculating measures for 2701 pairs
  calculating SCCAF scores
# calculate merges
merged_dt   = calc_merged_dt(pairwise_dt, labels_dt,
  v_cut = v_cut, mrg_custom = mrg_custom, save_dir)
merged_errs = calc_merged_errs(probs_dt, confuse_dt, merged_dt)
  making pairs to compare
  calculating measures for 1225 pairs
  making pairs to compare
  calculating measures for 1378 pairs
  making pairs to compare
  calculating measures for 741 pairs

Analysis

SCCAF confusion matrix

for (v in c('prop', 'logit')) {
  cat('### ', v, '\n')
  draw(plot_confusion(confuse_dt, v, cns_annots))
  cat('\n\n')
}

prop

logit

SCCAF entropies

(plot_sccaf_entropies(confuse_dt))

Possible merging metrics

for (v in c('error', 'H_norm', 'sccaf_val')) {
  cat('### ', v, '\n')
  draw(plot_merging_metrics(pairwise_dt, labels_dt, v))
  cat('\n\n')
}

error

H_norm

sccaf_val

Summary of cluster merges

knitr::kable(calc_merges_summary(merged_dt, labels_dt))
type_broad unmerged single average complete
Oligodendrocytes 14 3 7 8
OPCs / COPs 5 3 3 4
Astrocytes 9 4 6 6
Microglia 4 1 1 1
Excitatory neurons 24 16 19 20
Inhibitory neurons 8 7 7 7
Endothelial cells 3 1 2 2
Pericytes 1 1 1 1
Immune 6 3 4 4

Proposed cluster merges

for (m in names(v_cut)) {
  cat('### ', m, '\n')
  draw(plot_merged_markers_heatmap(marker_exp_dt, merged_dt, m), merge_legend = TRUE, 
    heatmap_legend_side = "bottom", annotation_legend_side = "bottom")
  cat('\n\n')
}

single

average

complete

List of proposed cluster merges

for (m in names(v_cut)) {
  cat('### ', m, '\n')
  print(knitr::kable(merged_dt[method == m]))
  cat('\n\n')
}

single

method type_broad conos_merge N_merge conos metric merge_clust
single Oligodendrocytes cns01 14 cns01 error 31
single Oligodendrocytes cns01 14 cns04 error 31
single Oligodendrocytes cns01 14 cns07 error 31
single Oligodendrocytes cns01 14 cns10 error 31
single Oligodendrocytes cns01 14 cns11 error 31
single Oligodendrocytes cns01 14 cns15 error 31
single Oligodendrocytes cns01 14 cns16 error 31
single Oligodendrocytes cns01 14 cns18 error 31
single Oligodendrocytes cns01 14 cns20 error 31
single Excitatory neurons cns01 14 cns24.1 error 31
single Astrocytes cns01 14 cns31 error 31
single Oligodendrocytes cns01 14 cns33 error 31
single Oligodendrocytes cns01 14 cns36 error 31
single Oligodendrocytes cns01 14 cns40 error 31
single Astrocytes cns02 5 cns02 error 3
single Astrocytes cns02 5 cns06 error 3
single Astrocytes cns02 5 cns17 error 3
single Astrocytes cns02 5 cns35 error 3
single Astrocytes cns02 5 cns44 error 3
single Microglia cns08 5 cns08 error 1
single Microglia cns08 5 cns09 error 1
single Microglia cns08 5 cns43 error 1
single Microglia cns08 5 cns46 error 1
single Immune cns08 5 cns55.2 error 1
single Excitatory neurons cns12 5 cns12 error 4
single Excitatory neurons cns12 5 cns21 error 4
single Excitatory neurons cns12 5 cns27 error 4
single Excitatory neurons cns12 5 cns30 error 4
single Excitatory neurons cns12 5 cns34 error 4
single OPCs / COPs cns14 3 cns14 error 2
single OPCs / COPs cns14 3 cns28.1 error 2
single OPCs / COPs cns14 3 cns28.2 error 2
single Excitatory neurons cns22 3 cns22 error 24
single Excitatory neurons cns22 3 cns29 error 24
single Excitatory neurons cns22 3 cns58 error 24
single Endothelial cells cns38 3 cns38 error 6
single Endothelial cells cns38 3 cns49 error 6
single Endothelial cells cns38 3 cns52 error 6
single Immune cns55.1 3 cns55.1 error cns55.1
single Immune cns55.1 3 cns55.4 error cns55.1
single Immune cns55.1 3 cns55.5 error cns55.1
single Excitatory neurons cns03 2 cns03 error cns03
single Excitatory neurons cns03 2 cns05 error cns03
single Inhibitory neurons cns37 2 cns37 error 13
single Inhibitory neurons cns37 2 cns39 error 13
single Oligodendrocytes cns13 1 cns13 error 32
single Inhibitory neurons cns19 1 cns19 error 23
single Excitatory neurons cns23 1 cns23 error 30
single Excitatory neurons cns24.2 1 cns24.2 error cns24.2
single Excitatory neurons cns24.3 1 cns24.3 error 27
single Excitatory neurons cns25 1 cns25 error 14
single Excitatory neurons cns26 1 cns26 error 21
single OPCs / COPs cns28.3 1 cns28.3 error cns28.3
single OPCs / COPs cns28.4 1 cns28.4 error cns28.4
single Excitatory neurons cns32 1 cns32 error 29
single Inhibitory neurons cns41 1 cns41 error 22
single Inhibitory neurons cns42 1 cns42 error 19
single Inhibitory neurons cns45 1 cns45 error 18
single Excitatory neurons cns47 1 cns47 error 16
single Pericytes cns48 1 cns48 error 8
single Inhibitory neurons cns50 1 cns50 error 20
single Excitatory neurons cns51 1 cns51 error 25
single Excitatory neurons cns53 1 cns53 error 15
single Excitatory neurons cns54 1 cns54 error 26
single Immune cns55.3 1 cns55.3 error cns55.3
single Immune cns55.6 1 cns55.6 error 7
single Excitatory neurons cns56 1 cns56 error 5
single Excitatory neurons cns57 1 cns57 error 10
single Excitatory neurons cns59 1 cns59 error 28
single Inhibitory neurons cns60 1 cns60 error 17
single Astrocytes cns61 1 cns61 error 11
single Oligodendrocytes cns62 1 cns62 error 33
single Astrocytes cns63 1 cns63 error 12
single Astrocytes cns64 1 cns64 error 9

average

method type_broad conos_merge N_merge conos metric merge_clust
average Oligodendrocytes cns11 5 cns11 error 44
average Oligodendrocytes cns11 5 cns16 error 44
average Oligodendrocytes cns11 5 cns20 error 44
average Oligodendrocytes cns11 5 cns36 error 44
average Oligodendrocytes cns11 5 cns40 error 44
average Microglia cns08 4 cns08 error 1
average Microglia cns08 4 cns09 error 1
average Microglia cns08 4 cns43 error 1
average Microglia cns08 4 cns46 error 1
average Oligodendrocytes cns10 4 cns10 error 43
average Excitatory neurons cns10 4 cns24.1 error 43
average Astrocytes cns10 4 cns31 error 43
average Oligodendrocytes cns10 4 cns33 error 43
average OPCs / COPs cns14 3 cns14 error 2
average OPCs / COPs cns14 3 cns28.1 error 2
average OPCs / COPs cns14 3 cns28.2 error 2
average Astrocytes cns17 3 cns17 error 3
average Astrocytes cns17 3 cns35 error 3
average Astrocytes cns17 3 cns44 error 3
average Excitatory neurons cns21 3 cns21 error 5
average Excitatory neurons cns21 3 cns27 error 5
average Excitatory neurons cns21 3 cns30 error 5
average Immune cns55.1 3 cns55.1 error cns55.1
average Immune cns55.1 3 cns55.4 error cns55.1
average Immune cns55.1 3 cns55.5 error cns55.1
average Oligodendrocytes cns01 2 cns01 error 42
average Oligodendrocytes cns01 2 cns04 error 42
average Excitatory neurons cns03 2 cns03 error cns03
average Excitatory neurons cns03 2 cns05 error cns03
average Oligodendrocytes cns07 2 cns07 error 38
average Oligodendrocytes cns07 2 cns18 error 38
average Excitatory neurons cns22 2 cns22 error 30
average Excitatory neurons cns22 2 cns29 error 30
average Inhibitory neurons cns37 2 cns37 error 19
average Inhibitory neurons cns37 2 cns39 error 19
average Endothelial cells cns38 2 cns38 error 10
average Endothelial cells cns38 2 cns49 error 10
average Astrocytes cns02 1 cns02 error 11
average Astrocytes cns06 1 cns06 error 8
average Excitatory neurons cns12 1 cns12 error 7
average Oligodendrocytes cns13 1 cns13 error 39
average Oligodendrocytes cns15 1 cns15 error 41
average Inhibitory neurons cns19 1 cns19 error 29
average Excitatory neurons cns23 1 cns23 error 37
average Excitatory neurons cns24.2 1 cns24.2 error cns24.2
average Excitatory neurons cns24.3 1 cns24.3 error 33
average Excitatory neurons cns25 1 cns25 error 20
average Excitatory neurons cns26 1 cns26 error 27
average OPCs / COPs cns28.3 1 cns28.3 error cns28.3
average OPCs / COPs cns28.4 1 cns28.4 error cns28.4
average Excitatory neurons cns32 1 cns32 error 36
average Excitatory neurons cns34 1 cns34 error 6
average Inhibitory neurons cns41 1 cns41 error 28
average Inhibitory neurons cns42 1 cns42 error 25
average Inhibitory neurons cns45 1 cns45 error 24
average Excitatory neurons cns47 1 cns47 error 22
average Pericytes cns48 1 cns48 error 14
average Inhibitory neurons cns50 1 cns50 error 26
average Excitatory neurons cns51 1 cns51 error 31
average Endothelial cells cns52 1 cns52 error 12
average Excitatory neurons cns53 1 cns53 error 21
average Excitatory neurons cns54 1 cns54 error 32
average Immune cns55.2 1 cns55.2 error 4
average Immune cns55.3 1 cns55.3 error cns55.3
average Immune cns55.6 1 cns55.6 error 13
average Excitatory neurons cns56 1 cns56 error 9
average Excitatory neurons cns57 1 cns57 error 16
average Excitatory neurons cns58 1 cns58 error 35
average Excitatory neurons cns59 1 cns59 error 34
average Inhibitory neurons cns60 1 cns60 error 23
average Astrocytes cns61 1 cns61 error 17
average Oligodendrocytes cns62 1 cns62 error 40
average Astrocytes cns63 1 cns63 error 18
average Astrocytes cns64 1 cns64 error 15

complete

method type_broad conos_merge N_merge conos metric merge_clust
complete Microglia cns08 4 cns08 error 1
complete Microglia cns08 4 cns09 error 1
complete Microglia cns08 4 cns43 error 1
complete Microglia cns08 4 cns46 error 1
complete Oligodendrocytes cns10 3 cns10 error 44
complete Oligodendrocytes cns10 3 cns18 error 44
complete Astrocytes cns10 3 cns31 error 44
complete Oligodendrocytes cns11 3 cns11 error 46
complete Oligodendrocytes cns11 3 cns36 error 46
complete Oligodendrocytes cns11 3 cns40 error 46
complete Excitatory neurons cns21 3 cns21 error 5
complete Excitatory neurons cns21 3 cns27 error 5
complete Excitatory neurons cns21 3 cns30 error 5
complete Immune cns55.1 3 cns55.1 error cns55.1
complete Immune cns55.1 3 cns55.4 error cns55.1
complete Immune cns55.1 3 cns55.5 error cns55.1
complete Oligodendrocytes cns01 2 cns01 error 43
complete Oligodendrocytes cns01 2 cns04 error 43
complete Astrocytes cns02 2 cns02 error 12
complete Astrocytes cns02 2 cns17 error 12
complete Excitatory neurons cns03 2 cns03 error cns03
complete Excitatory neurons cns03 2 cns05 error cns03
complete Oligodendrocytes cns16 2 cns16 error 45
complete Oligodendrocytes cns16 2 cns20 error 45
complete Excitatory neurons cns22 2 cns22 error 31
complete Excitatory neurons cns22 2 cns29 error 31
complete Excitatory neurons cns24.1 2 cns24.1 error 47
complete Oligodendrocytes cns24.1 2 cns33 error 47
complete OPCs / COPs cns28.1 2 cns28.1 error 2
complete OPCs / COPs cns28.1 2 cns28.2 error 2
complete Astrocytes cns35 2 cns35 error 3
complete Astrocytes cns35 2 cns44 error 3
complete Inhibitory neurons cns37 2 cns37 error 20
complete Inhibitory neurons cns37 2 cns39 error 20
complete Endothelial cells cns38 2 cns38 error 11
complete Endothelial cells cns38 2 cns49 error 11
complete Astrocytes cns06 1 cns06 error 9
complete Oligodendrocytes cns07 1 cns07 error 39
complete Excitatory neurons cns12 1 cns12 error 8
complete Oligodendrocytes cns13 1 cns13 error 40
complete OPCs / COPs cns14 1 cns14 error 6
complete Oligodendrocytes cns15 1 cns15 error 42
complete Inhibitory neurons cns19 1 cns19 error 30
complete Excitatory neurons cns23 1 cns23 error 38
complete Excitatory neurons cns24.2 1 cns24.2 error cns24.2
complete Excitatory neurons cns24.3 1 cns24.3 error 34
complete Excitatory neurons cns25 1 cns25 error 21
complete Excitatory neurons cns26 1 cns26 error 28
complete OPCs / COPs cns28.3 1 cns28.3 error cns28.3
complete OPCs / COPs cns28.4 1 cns28.4 error cns28.4
complete Excitatory neurons cns32 1 cns32 error 37
complete Excitatory neurons cns34 1 cns34 error 7
complete Inhibitory neurons cns41 1 cns41 error 29
complete Inhibitory neurons cns42 1 cns42 error 26
complete Inhibitory neurons cns45 1 cns45 error 25
complete Excitatory neurons cns47 1 cns47 error 23
complete Pericytes cns48 1 cns48 error 15
complete Inhibitory neurons cns50 1 cns50 error 27
complete Excitatory neurons cns51 1 cns51 error 32
complete Endothelial cells cns52 1 cns52 error 13
complete Excitatory neurons cns53 1 cns53 error 22
complete Excitatory neurons cns54 1 cns54 error 33
complete Immune cns55.2 1 cns55.2 error 4
complete Immune cns55.3 1 cns55.3 error cns55.3
complete Immune cns55.6 1 cns55.6 error 14
complete Excitatory neurons cns56 1 cns56 error 10
complete Excitatory neurons cns57 1 cns57 error 17
complete Excitatory neurons cns58 1 cns58 error 36
complete Excitatory neurons cns59 1 cns59 error 35
complete Inhibitory neurons cns60 1 cns60 error 24
complete Astrocytes cns61 1 cns61 error 18
complete Oligodendrocytes cns62 1 cns62 error 41
complete Astrocytes cns63 1 cns63 error 19
complete Astrocytes cns64 1 cns64 error 16

Heatmaps of errors between merged clusters

Note that the following clusters were hardcoded:

print(mrg_custom)

$cns03 [1] “cns03” “cns05”

$cns24.2 [1] “cns24.2”

$cns28.3 [1] “cns28.3”

$cns28.4 [1] “cns28.4”

$cns55.1 [1] “cns55.1” “cns55.4” “cns55.5”

$cns55.3 [1] “cns55.3”

for (m in names(v_cut)) {
  cat('### ', m, '\n')
  labels_tmp   = merged_dt[method == m] %>% 
    .[, .(type_broad = sort(type_broad)[[1]]), by = .(conos = conos_merge)]
  draw(plot_merging_metrics(merged_errs[method == m], labels_tmp, v = 'error'))
  cat('\n\n')
}

single

average

complete

Outputs

# save merges
merged_dt %>% fwrite(file = merges_f)

# make merged conos
conos_merged  = calc_conos_merged(conos_dt, merged_dt, sel_method)
conos_merged %>% fwrite(file = merged_f)
save_find_markers_merged(conos_merged, fm_groups, fm_pat, tests, sce_f, n_cells, n_cores = 16)
already done for oligo!
  skipping
already done for opc!
  skipping
already done for astro!
  skipping
already done for micro_immune!
  skipping
already done for excit_neuron!
  skipping
already done for inhib_neuron!
  skipping
already done for endo_peri!
  skipping
devtools::session_info()
Registered S3 method overwritten by 'cli':
  method     from         
  print.boxx spatstat.geom
- Session info ---------------------------------------------------------------
 setting  value                       
 version  R version 4.0.3 (2020-10-10)
 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     2021-04-29                  

- Packages -------------------------------------------------------------------
 package              * version  date       lib
 abind                  1.4-5    2016-07-21 [2]
 assertthat           * 0.2.1    2019-03-21 [2]
 beachmat               2.6.4    2020-12-20 [1]
 beeswarm               0.3.1    2021-03-07 [1]
 Biobase              * 2.50.0   2020-10-27 [1]
 BiocGenerics         * 0.36.1   2021-04-16 [1]
 BiocManager            1.30.12  2021-03-28 [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]
 bitops                 1.0-6    2013-08-17 [2]
 bluster                1.0.0    2020-10-27 [1]
 bslib                  0.2.4    2021-01-25 [2]
 cachem                 1.0.4    2021-02-13 [2]
 Cairo                  1.5-12.2 2020-07-07 [2]
 callr                  3.6.0    2021-03-28 [2]
 circlize             * 0.4.12   2021-01-08 [1]
 cli                    2.4.0    2021-04-05 [2]
 clue                   0.3-59   2021-04-16 [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]
 colorspace             2.0-0    2020-11-11 [2]
 ComplexHeatmap       * 2.6.2    2020-11-12 [1]
 conos                * 1.4.0    2021-02-23 [1]
 cowplot                1.1.1    2020-12-30 [2]
 crayon                 1.4.1    2021-02-08 [2]
 data.table           * 1.14.0   2021-02-21 [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                 0.2-10   2021-02-16 [2]
 desc                   1.3.0    2021-03-05 [2]
 devtools               2.4.0    2021-04-07 [1]
 digest                 0.6.27   2020-10-24 [2]
 dplyr                  1.0.5    2021-03-05 [2]
 dqrng                  0.2.1    2019-05-17 [2]
 edgeR                  3.32.1   2021-01-14 [1]
 ellipsis               0.3.1    2020-05-15 [2]
 evaluate               0.14     2019-05-28 [2]
 fansi                  0.4.2    2021-01-15 [2]
 farver                 2.1.0    2021-02-28 [2]
 fastmap                1.1.0    2021-01-25 [2]
 fitdistrplus           1.1-3    2020-12-05 [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                 1.21.0   2020-12-10 [2]
 future.apply           1.7.0    2021-01-04 [2]
 generics               0.1.0    2020-10-31 [2]
 GenomeInfoDb         * 1.26.7   2021-04-08 [1]
 GenomeInfoDbData       1.2.4    2021-04-15 [1]
 GenomicRanges        * 1.42.0   2020-10-27 [1]
 GetoptLong             1.0.5    2020-12-15 [1]
 ggbeeswarm             0.6.0    2017-08-07 [1]
 ggplot.multistats    * 1.0.0    2019-10-28 [1]
 ggplot2              * 3.3.3    2020-12-30 [2]
 ggrepel                0.9.1    2021-01-15 [2]
 ggridges               0.5.3    2021-01-08 [2]
 git2r                  0.28.0   2021-01-10 [1]
 GlobalOptions          0.1.2    2020-06-10 [1]
 globals                0.14.0   2020-11-22 [2]
 glue                   1.4.2    2020-08-27 [2]
 goftest                1.2-2    2019-12-02 [2]
 gridExtra              2.3      2017-09-09 [2]
 grr                    0.9.5    2016-08-26 [1]
 gtable                 0.3.0    2019-03-25 [2]
 hexbin                 1.28.2   2021-01-08 [2]
 highr                  0.9      2021-04-16 [2]
 htmltools              0.5.1.1  2021-01-22 [2]
 htmlwidgets            1.5.3    2020-12-10 [2]
 httpuv                 1.5.5    2021-01-13 [2]
 httr                   1.4.2    2020-07-20 [2]
 ica                    1.0-2    2018-05-24 [2]
 igraph               * 1.2.6    2020-10-06 [2]
 IRanges              * 2.24.1   2020-12-12 [1]
 irlba                  2.3.3    2019-02-05 [2]
 iterators              1.0.13   2020-10-15 [2]
 jquerylib              0.1.3    2020-12-17 [2]
 jsonlite               1.7.2    2020-12-09 [2]
 KernSmooth             2.23-18  2020-10-29 [2]
 knitr                  1.32     2021-04-14 [1]
 later                  1.1.0.1  2020-06-05 [2]
 lattice                0.20-41  2020-04-02 [2]
 lazyeval               0.2.2    2019-03-15 [2]
 leiden                 0.3.7    2021-01-26 [2]
 leidenAlg              0.1.1    2021-03-03 [1]
 lifecycle              1.0.0    2021-02-15 [2]
 limma                  3.46.0   2020-10-27 [1]
 listenv                0.8.0    2019-12-05 [2]
 lmtest                 0.9-38   2020-09-09 [2]
 locfit                 1.5-9.4  2020-03-25 [1]
 magrittr             * 2.0.1    2020-11-17 [1]
 MASS                   7.3-53.1 2021-02-12 [2]
 Matrix               * 1.3-2    2021-01-06 [2]
 Matrix.utils           0.9.8    2020-02-26 [1]
 MatrixGenerics       * 1.2.1    2021-01-30 [1]
 matrixStats          * 0.58.0   2021-01-29 [2]
 memoise                2.0.0    2021-01-26 [1]
 mgcv                   1.8-35   2021-04-18 [2]
 mime                   0.10     2021-02-13 [2]
 miniUI                 0.1.1.1  2018-05-18 [2]
 munsell                0.5.0    2018-06-12 [2]
 nlme                   3.1-152  2021-02-04 [2]
 parallelly             1.24.0   2021-03-14 [2]
 patchwork            * 1.1.1    2020-12-17 [2]
 pbapply                1.4-3    2020-08-18 [2]
 pillar                 1.6.0    2021-04-13 [2]
 pkgbuild               1.2.0    2020-12-15 [1]
 pkgconfig              2.0.3    2019-09-22 [2]
 pkgload                1.2.1    2021-04-06 [2]
 plotly                 4.9.3    2021-01-10 [2]
 plotROC              * 2.2.1    2018-06-23 [1]
 plyr                   1.8.6    2020-03-03 [2]
 png                    0.1-7    2013-12-03 [2]
 polyclip               1.10-0   2019-03-14 [2]
 prettyunits            1.1.1    2020-01-24 [2]
 processx               3.5.1    2021-04-04 [2]
 promises               1.2.0.1  2021-02-11 [2]
 ps                     1.6.0    2021-02-28 [2]
 purrr                  0.3.4    2020-04-17 [2]
 R6                     2.5.0    2020-10-28 [2]
 RANN                   2.6.1    2019-01-08 [2]
 rappdirs               0.3.3    2021-01-31 [2]
 RColorBrewer         * 1.1-2    2014-12-07 [2]
 Rcpp                   1.0.6    2021-01-15 [2]
 RcppAnnoy              0.0.18   2020-12-15 [2]
 RCurl                  1.98-1.3 2021-03-16 [1]
 registry               0.5-1    2019-03-05 [1]
 remotes                2.3.0    2021-04-01 [1]
 reshape2               1.4.4    2020-04-09 [2]
 reticulate           * 1.18     2020-10-25 [2]
 rjson                  0.2.20   2018-06-08 [1]
 rlang                  0.4.10   2020-12-30 [2]
 rmarkdown              2.7      2021-02-19 [2]
 ROCR                   1.0-11   2020-05-02 [2]
 rpart                  4.1-15   2019-04-12 [2]
 rprojroot              2.0.2    2020-11-15 [2]
 rsvd                   1.0.5    2021-04-16 [1]
 Rtsne                  0.15     2018-11-10 [2]
 S4Vectors            * 0.28.1   2020-12-09 [1]
 sass                   0.3.1    2021-01-24 [2]
 scales               * 1.1.1    2020-05-11 [2]
 scater               * 1.18.6   2021-02-26 [1]
 scattermore            0.7      2020-11-24 [2]
 sccore                 0.1.2    2021-02-23 [1]
 scran                * 1.18.7   2021-04-16 [1]
 sctransform            0.3.2    2020-12-16 [2]
 scuttle                1.0.4    2020-12-17 [1]
 seriation            * 1.2-9    2020-10-01 [1]
 sessioninfo            1.1.1    2018-11-05 [1]
 Seurat               * 4.0.1    2021-03-18 [2]
 SeuratObject         * 4.0.0    2021-01-15 [2]
 shape                  1.4.5    2020-09-13 [2]
 shiny                  1.6.0    2021-01-25 [2]
 SingleCellExperiment * 1.12.0   2020-10-27 [1]
 sparseMatrixStats      1.2.1    2021-02-02 [1]
 spatstat.core          2.1-2    2021-04-18 [2]
 spatstat.data          2.1-0    2021-03-21 [2]
 spatstat.geom          2.1-0    2021-04-15 [2]
 spatstat.sparse        2.0-0    2021-03-16 [2]
 spatstat.utils         2.1-0    2021-03-15 [2]
 statmod                1.4.35   2020-10-19 [1]
 stringi                1.5.3    2020-09-09 [2]
 stringr              * 1.4.0    2019-02-10 [2]
 SummarizedExperiment * 1.20.0   2020-10-27 [1]
 survival               3.2-10   2021-03-16 [2]
 tensor                 1.5      2012-05-05 [2]
 testthat               3.0.2    2021-02-14 [2]
 tibble                 3.1.1    2021-04-18 [2]
 tidyr                  1.1.3    2021-03-03 [2]
 tidyselect             1.1.0    2020-05-11 [2]
 TSP                    1.1-10   2020-04-17 [1]
 usethis                2.0.1    2021-02-10 [1]
 utf8                   1.2.1    2021-03-12 [2]
 uwot                 * 0.1.10   2020-12-15 [2]
 vctrs                  0.3.7    2021-03-29 [2]
 vipor                  0.4.5    2017-03-22 [1]
 viridis              * 0.6.0    2021-04-15 [1]
 viridisLite          * 0.4.0    2021-04-13 [2]
 whisker                0.4      2019-08-28 [1]
 withr                  2.4.2    2021-04-18 [2]
 workflowr            * 1.6.2    2020-04-30 [1]
 xfun                   0.22     2021-03-11 [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

sessionInfo()
R version 4.0.3 (2020-10-10)
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] parallel  stats4    grid      stats     graphics  grDevices utils    
 [8] datasets  methods   base     

other attached packages:
 [1] plotROC_2.2.1               reticulate_1.18            
 [3] scran_1.18.7                uwot_0.1.10                
 [5] scater_1.18.6               SingleCellExperiment_1.12.0
 [7] SummarizedExperiment_1.20.0 Biobase_2.50.0             
 [9] GenomicRanges_1.42.0        GenomeInfoDb_1.26.7        
[11] IRanges_2.24.1              S4Vectors_0.28.1           
[13] BiocGenerics_0.36.1         MatrixGenerics_1.2.1       
[15] matrixStats_0.58.0          BiocParallel_1.24.1        
[17] ggplot.multistats_1.0.0     patchwork_1.1.1            
[19] seriation_1.2-9             ComplexHeatmap_2.6.2       
[21] SeuratObject_4.0.0          Seurat_4.0.1               
[23] conos_1.4.0                 igraph_1.2.6               
[25] Matrix_1.3-2                forcats_0.5.1              
[27] ggplot2_3.3.3               scales_1.1.1               
[29] viridis_0.6.0               viridisLite_0.4.0          
[31] assertthat_0.2.1            stringr_1.4.0              
[33] data.table_1.14.0           magrittr_2.0.1             
[35] circlize_0.4.12             RColorBrewer_1.1-2         
[37] BiocStyle_2.18.1            colorout_1.2-2             
[39] workflowr_1.6.2            

loaded via a namespace (and not attached):
  [1] utf8_1.2.1                tidyselect_1.1.0         
  [3] htmlwidgets_1.5.3         TSP_1.1-10               
  [5] Rtsne_0.15                devtools_2.4.0           
  [7] munsell_0.5.0             codetools_0.2-18         
  [9] ica_1.0-2                 statmod_1.4.35           
 [11] future_1.21.0             miniUI_0.1.1.1           
 [13] withr_2.4.2               colorspace_2.0-0         
 [15] highr_0.9                 knitr_1.32               
 [17] rstudioapi_0.13           ROCR_1.0-11              
 [19] tensor_1.5                listenv_0.8.0            
 [21] git2r_0.28.0              GenomeInfoDbData_1.2.4   
 [23] polyclip_1.10-0           farver_2.1.0             
 [25] rprojroot_2.0.2           parallelly_1.24.0        
 [27] Matrix.utils_0.9.8        vctrs_0.3.7              
 [29] generics_0.1.0            xfun_0.22                
 [31] R6_2.5.0                  ggbeeswarm_0.6.0         
 [33] clue_0.3-59               rsvd_1.0.5               
 [35] locfit_1.5-9.4            cachem_1.0.4             
 [37] bitops_1.0-6              spatstat.utils_2.1-0     
 [39] DelayedArray_0.16.3       promises_1.2.0.1         
 [41] beeswarm_0.3.1            gtable_0.3.0             
 [43] beachmat_2.6.4            Cairo_1.5-12.2           
 [45] globals_0.14.0            processx_3.5.1           
 [47] goftest_1.2-2             rlang_0.4.10             
 [49] GlobalOptions_0.1.2       splines_4.0.3            
 [51] lazyeval_0.2.2            hexbin_1.28.2            
 [53] spatstat.geom_2.1-0       BiocManager_1.30.12      
 [55] yaml_2.2.1                reshape2_1.4.4           
 [57] abind_1.4-5               httpuv_1.5.5             
 [59] usethis_2.0.1             tools_4.0.3              
 [61] sccore_0.1.2              ellipsis_0.3.1           
 [63] spatstat.core_2.1-2       jquerylib_0.1.3          
 [65] sessioninfo_1.1.1         ggridges_0.5.3           
 [67] Rcpp_1.0.6                plyr_1.8.6               
 [69] sparseMatrixStats_1.2.1   zlibbioc_1.36.0          
 [71] purrr_0.3.4               RCurl_1.98-1.3           
 [73] prettyunits_1.1.1         ps_1.6.0                 
 [75] rpart_4.1-15              deldir_0.2-10            
 [77] pbapply_1.4-3             GetoptLong_1.0.5         
 [79] cowplot_1.1.1             zoo_1.8-9                
 [81] grr_0.9.5                 ggrepel_0.9.1            
 [83] cluster_2.1.2             fs_1.5.0                 
 [85] scattermore_0.7           lmtest_0.9-38            
 [87] RANN_2.6.1                whisker_0.4              
 [89] fitdistrplus_1.1-3        pkgload_1.2.1            
 [91] mime_0.10                 evaluate_0.14            
 [93] xtable_1.8-4              gridExtra_2.3            
 [95] shape_1.4.5               testthat_3.0.2           
 [97] compiler_4.0.3            tibble_3.1.1             
 [99] KernSmooth_2.23-18        crayon_1.4.1             
[101] htmltools_0.5.1.1         mgcv_1.8-35              
[103] later_1.1.0.1             tidyr_1.1.3              
[105] DBI_1.1.1                 rappdirs_0.3.3           
[107] MASS_7.3-53.1             cli_2.4.0                
[109] pkgconfig_2.0.3           registry_0.5-1           
[111] plotly_4.9.3              scuttle_1.0.4            
[113] spatstat.sparse_2.0-0     foreach_1.5.1            
[115] vipor_0.4.5               bslib_0.2.4              
[117] dqrng_0.2.1               XVector_0.30.0           
[119] leidenAlg_0.1.1           callr_3.6.0              
[121] digest_0.6.27             sctransform_0.3.2        
[123] RcppAnnoy_0.0.18          spatstat.data_2.1-0      
[125] rmarkdown_2.7             leiden_0.3.7             
[127] edgeR_3.32.1              DelayedMatrixStats_1.12.3
[129] shiny_1.6.0               rjson_0.2.20             
[131] lifecycle_1.0.0           nlme_3.1-152             
[133] jsonlite_1.7.2            BiocNeighbors_1.8.2      
[135] desc_1.3.0                limma_3.46.0             
[137] fansi_0.4.2               pillar_1.6.0             
[139] lattice_0.20-41           pkgbuild_1.2.0           
[141] fastmap_1.1.0             httr_1.4.2               
[143] survival_3.2-10           remotes_2.3.0            
[145] glue_1.4.2                png_0.1-7                
[147] iterators_1.0.13          bluster_1.0.0            
[149] stringi_1.5.3             sass_0.3.1               
[151] BiocSingular_1.6.0        memoise_2.0.0            
[153] dplyr_1.0.5               irlba_2.3.3              
[155] future.apply_1.7.0