MS: Identifying gene modules with non-negative matrix factorization (pseudo-bulk)
Will Macnair
Institute for Molecular Life Sciences, University of Zurich, SwitzerlandSwiss Institute of Bioinformatics (SIB), University of Zurich, SwitzerlandSeptember 28, 2021
Last updated: 2021-09-28
Checks: 4 3
Knit directory: MS_lesions/
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- plot_genes_dotplot
- plot_genes
- plot_genes_heatmap
- plot_scores_by_type_scaled_2
- plot_scores_by_type_scaled
- plot_scores_by_type_unscaled
- plot_scores_over_lesions
- plot_umap_celltypes
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| File | Version | Author | Date | Message |
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| html | 7ddc417 | Macnair | 2021-09-24 | Add pseudobulk version of modules |
Setup / definitions
Libraries
Helper functions
source('code/ms00_utils.R')
source('code/ms08_modules.R')
source_python('code/ms08_modules.py')Inputs
# 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_updated_20201127.txt'
# 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'Outputs
# set up directory
save_dir = 'output/ms08_modules'
date_tag = '2021-09-24'
if (!dir.exists(save_dir))
dir.create(save_dir)
ncores = 8
# 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/pb_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] TRUEgroup_list = names(spec_list)
# how many per fine celltype?
n_sample = 2e3
n_genes = 2e3
max_soup = 0.1
ok_types = 'protein_coding'
# umap params
umap_many_f = 'output/ms04_conos/conos_umap_sub_2021-02-11.txt'
# umap_ps = list(
# min_dist = 0.1,
# spread = 8
# )
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)Load inputs
labels_dt = load_names_dt(labels_f) %>%
.[, cluster_id := type_fine]
conos_dt = load_labelled_dt(labelled_f, labels_f)
meta_dt = load_meta_dt(meta_f)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)umap_dt = umap_many_f %>% fread %>%
.[ min_dist == umap_ps$min_dist & spread == umap_ps$spread ] %>%
.[, .(cell_id, UMAP1, UMAP2)]Processing / calculations
save_sub_sces_pb(spec_list, pb_fine_f, sce_pat, ok_gs_pat, labels_dt, contam_dt,
biotypes_dt, n_sample, n_genes, max_soup, ok_types, min_cells = 10, save_dir)already done!NULLsave_outputs_for_popalign(group_list, sce_pat, mtx_pat, genes_pat)already done!NULLrun_onmf(save_dir, date_tag, group_list, ncores = ncores)pop_list = group_list %>%
map(~get_pop_results(.x, res_pat, sce_pat, ok_gs_pat, go_pat, pop_pat,
conos_dt, labels_dt, is_pb = TRUE)) %>% setNames(group_list)Analysis
Median module scores by celltype (scaled)
for (g in group_list) {
cat('### ', g, '\n')
hm = plot_scores_by_celltype(pop_list[[g]]$scores_dt, pop_list[[g]]$k_order,
what = 'scaled')
if (!is.null(hm))
draw(hm)
cat('\n\n')
}oligo_opc
micro_immune
excitatory
inhibitory
astrocytes
endo_stromal
microglia
immune
Median module scores by celltype (proportions)
for (g in group_list) {
cat('### ', g, '\n')
hm = plot_scores_by_celltype(pop_list[[g]]$scores_dt, pop_list[[g]]$k_order,
what = 'propns')
if (!is.null(hm))
draw(hm)
cat('\n\n')
}oligo_opc
micro_immune
excitatory
inhibitory
astrocytes
endo_stromal
microglia
immune
Most important genes per module, dotplot
for (g in group_list) {
cat('### ', g, '\n')
print(plot_biggest_genes_dotplot(g, spec_list, pop_list[[g]]$w_mat,
pop_list[[g]]$k_order, fine_dt, w2_cut = 0.02))
cat('\n\n')
}oligo_opc
micro_immune
excitatory
inhibitory
astrocytes
endo_stromal
microglia
immune
Most important genes per module, heatmap
for (g in group_list) {
cat('### ', g, '\n')
hm = plot_biggest_genes_heatmap(g, sce_pat, pop_list[[g]]$w_mat,
pop_list[[g]]$k_order, meta_dt, labels_dt, w2_cut = 0.01)
if (!is.null(hm))
draw(hm, merge_legend = TRUE)
cat('\n\n')
}oligo_opc
micro_immune
excitatory
inhibitory
astrocytes
endo_stromal
microglia
immune
Median module scores by celltype (scaled)
for (g in group_list) {
cat('### ', g, '\n')
hm = plot_scores_by_celltype(pop_list[[g]]$scores_dt, pop_list[[g]]$k_order,
what = 'scaled')
if (!is.null(hm))
draw(hm)
cat('\n\n')
}oligo_opc
micro_immune
excitatory
inhibitory
astrocytes
endo_stromal
microglia
immune
Enriched GO terms per module (using 2k genes for GSEA)
for (g in group_list) {
cat('### ', g, '\n')
hm = plot_enriched_sets(pop_list[[g]]$go_std_dt, pop_list[[g]]$k_order)
if (!is.null(hm))
draw(hm)
cat('\n\n')
}
Enriched GO terms per module (using more genes for GSEA)
for (g in group_list) {
cat('### ', g, '\n')
hm = plot_enriched_sets(pop_list[[g]]$go_all_dt, pop_list[[g]]$k_order)
if (!is.null(hm))
draw(hm)
cat('\n\n')
}
UMAP celltype reference
(plot_umap_celltypes(umap_dt, conos_dt))
feat_list = scores_dt$feat %>% unique %>% sort %>% .[k_order]
for (f in feat_list) {
cat('### ', f, '\n')
print(plot_scores_over_lesions(scores_dt, f, meta_dt))
cat('\n\n')
}Distribution of fine celltypes over UMAP
for (g in group_list) {
cat('### ', g, '\n')
print(plot_celltypes_over_umap(spec_list[[g]], conos_dt, umap_dt))
cat('\n\n')
}oligo_opc
micro_immune
excitatory
inhibitory
astrocytes
endo_stromal
microglia
immune
Outputs
save_module_genes_to_xl(pop_list, xl_f) broad_type symbol K01 K02 K03 K04
1: oligo_opc PLP1 2.531141e-02 2.532711e-14 1.029482e-14 2.037848e-02
2: oligo_opc DSCAM 2.274387e-18 6.132759e-02 1.197744e-02 1.965392e-18
3: oligo_opc CTNNA3 1.456599e-01 1.848812e-14 6.967282e-15 6.473713e-03
4: oligo_opc OPCML 2.274387e-18 1.852172e-02 4.558979e-02 1.965392e-18
5: oligo_opc ST18 1.490506e-01 1.861083e-14 7.252551e-15 8.745914e-03
---
1996: oligo_opc ARL4A 2.274387e-18 7.160648e-10 5.156852e-11 1.965392e-18
1997: oligo_opc SLC25A25 2.274387e-18 4.743476e-11 2.610729e-02 1.965392e-18
1998: oligo_opc NEDD4 9.946457e-08 3.733592e-02 1.627897e-02 7.060745e-06
1999: oligo_opc PFKP 2.274387e-18 1.553894e-09 2.652903e-02 1.965392e-18
2000: oligo_opc DEF8 5.791248e-09 2.552419e-14 1.150755e-14 3.035459e-02
K05 K06 K07 K08 K09
1: 3.723254e-02 2.428265e-02 2.915411e-14 2.971436e-04 1.212193e-02
2: 1.036054e-16 3.954935e-16 1.626423e-01 1.877257e-15 1.268171e-14
3: 3.980145e-02 7.756134e-02 2.182454e-14 2.201967e-03 3.286886e-02
4: 1.176240e-16 4.172401e-16 1.639750e-01 2.009148e-15 1.341245e-14
5: 3.764663e-02 4.555172e-02 2.208063e-14 9.908231e-04 3.416832e-02
---
1996: 1.450351e-16 7.944858e-16 8.565232e-05 2.933553e-15 1.928638e-14
1997: 2.288599e-16 6.115882e-16 2.543156e-05 3.089683e-15 1.835894e-14
1998: 1.723502e-06 4.795918e-14 6.936898e-03 6.338921e-02 1.623833e-11
1999: 1.763338e-16 6.891431e-16 1.045625e-05 3.424790e-15 1.718074e-14
2000: 1.788383e-02 3.520216e-08 2.683608e-14 3.496097e-03 2.714472e-07
K10 K11 K12 K13 K14
1: 2.161668e-01 1.640635e-02 7.412329e-15 1.103322e-02 7.621034e-03
2: 3.197928e-16 2.801745e-18 1.618601e-02 5.479059e-16 1.034362e-15
3: 1.112941e-02 2.341694e-02 4.522436e-15 6.236107e-02 6.998470e-03
4: 3.330870e-16 2.801745e-18 1.411016e-02 5.754238e-16 1.113395e-15
5: 6.136724e-03 1.718269e-02 4.662111e-15 9.602691e-02 1.615993e-03
---
1996: 7.586993e-16 2.801745e-18 2.646886e-02 9.283631e-16 1.872646e-15
1997: 3.772933e-16 2.801745e-18 1.184959e-05 8.639841e-16 1.535963e-15
1998: 4.408682e-14 7.028420e-14 2.506440e-03 1.803488e-07 2.313040e-12
1999: 4.582206e-16 2.801745e-18 1.385212e-09 1.236200e-15 1.361230e-15
2000: 1.150903e-05 7.643018e-14 8.742920e-15 9.467129e-03 4.035168e-05
broad_type symbol K01 K02 K03 K04
1: micro_immune PLXDC2 2.971594e-15 3.356741e-02 3.046753e-14 4.511489e-14
2: micro_immune DOCK4 2.756175e-15 4.358403e-03 3.044887e-14 4.541235e-14
3: micro_immune LRMDA 2.861045e-15 1.663837e-02 2.963549e-14 4.500699e-14
4: micro_immune FRMD4A 2.519641e-15 2.320878e-03 2.906520e-14 4.529767e-14
5: micro_immune ARHGAP24 2.917386e-15 5.605814e-03 3.049001e-14 4.529346e-14
---
1996: micro_immune WDR11 3.614304e-15 4.632794e-02 3.008912e-14 4.575960e-14
1997: micro_immune CXCR6 4.213801e-14 2.395118e-15 2.313236e-14 3.451279e-14
1998: micro_immune ANKRD13C 1.787968e-15 3.985755e-03 3.093736e-14 4.493011e-14
1999: micro_immune STS 4.762052e-14 6.450192e-16 3.201081e-02 3.647128e-14
2000: micro_immune MRPL16 4.499333e-14 3.719664e-16 2.535796e-02 3.805978e-14
K05 K06 K07 K08 K09
1: 2.787768e-14 4.536529e-02 6.927349e-02 6.645358e-02 2.576226e-14
2: 2.771203e-14 2.158446e-02 2.437016e-02 7.092336e-02 2.581333e-14
3: 2.703245e-14 1.598062e-02 5.751332e-02 9.652253e-02 2.465578e-14
4: 2.728917e-14 2.258228e-02 1.262044e-02 1.378379e-01 2.448238e-14
5: 2.746952e-14 1.227421e-02 8.875956e-02 5.140470e-02 2.558731e-14
---
1996: 3.323119e-14 9.464583e-03 3.246135e-03 4.987695e-05 2.801802e-14
1997: 3.565611e-02 1.310000e-15 1.215800e-15 1.859823e-15 4.252692e-14
1998: 3.076467e-14 1.577903e-04 4.375728e-10 2.123337e-03 2.784958e-14
1999: 3.611007e-14 3.243046e-16 3.660373e-16 2.910363e-16 7.802335e-05
2000: 1.319431e-02 1.092124e-16 1.185605e-16 2.518976e-16 3.101694e-13
K10 K11 K12
1: 4.284580e-03 3.681819e-14 1.356428e-02
2: 6.901694e-02 3.715605e-14 1.901650e-02
3: 4.032546e-03 3.599121e-14 8.674188e-03
4: 2.552147e-03 3.535350e-14 6.859777e-03
5: 1.118627e-02 3.741381e-14 1.494528e-02
---
1996: 3.260142e-03 3.873906e-14 5.072674e-14
1997: 1.518235e-15 4.017456e-14 1.375073e-15
1998: 4.038375e-02 3.426563e-14 5.132631e-14
1999: 2.856163e-16 3.520260e-14 3.546619e-18
2000: 3.810621e-16 4.208703e-03 1.209523e-17
broad_type symbol K01 K02 K03 K04
1: excitatory RORB 5.219785e-14 5.293619e-14 5.454697e-14 1.442586e-01
2: excitatory CUX2 5.131399e-14 5.392069e-14 6.178847e-02 5.056010e-14
3: excitatory IL1RAPL2 4.816518e-14 5.007263e-14 4.479094e-14 1.554495e-01
4: excitatory EPHA6 2.029934e-13 3.120833e-13 8.929167e-03 4.975029e-14
5: excitatory MEIS2 8.820663e-13 6.329072e-03 1.212507e-01 4.798831e-14
---
1996: excitatory CTNND1 8.744264e-08 6.687883e-09 6.168749e-08 2.941387e-02
1997: excitatory KLRD1 1.932750e-03 1.561749e-04 2.786574e-03 7.417891e-03
1998: excitatory ARCN1 6.058628e-08 6.412455e-06 7.208118e-05 1.343437e-03
1999: excitatory ACP2 5.137812e-14 1.778866e-09 1.772055e-06 2.038307e-10
2000: excitatory FAM81A 1.107749e-03 2.445363e-05 1.041774e-02 8.679680e-03
K05 K06 K07 K08 K09
1: 4.501555e-06 6.486706e-12 3.115896e-09 5.519004e-14 5.543619e-14
2: 6.092540e-14 1.036341e-01 3.165341e-11 5.306260e-14 5.716459e-14
3: 2.555155e-09 5.320712e-14 4.719281e-14 5.108116e-14 5.439786e-14
4: 6.600230e-14 1.915057e-01 4.080109e-11 5.373688e-14 5.525468e-14
5: 5.977909e-14 2.026135e-07 4.881992e-14 3.405423e-12 5.437775e-14
---
1996: 1.544422e-06 5.761799e-07 5.441063e-04 6.184462e-03 2.917239e-06
1997: 5.098564e-06 1.794280e-03 9.804848e-11 2.129459e-07 1.535254e-02
1998: 4.267390e-04 1.540929e-07 2.566357e-02 2.298687e-02 6.366950e-07
1999: 8.634757e-08 8.078235e-14 2.412781e-03 2.831961e-02 2.224490e-08
2000: 3.464352e-04 2.025131e-02 5.616256e-03 5.225664e-05 2.585959e-02
K10 K11 K12
1: 4.815794e-02 2.166414e-02 5.438591e-14
2: 1.152249e-08 7.476621e-06 5.310929e-14
3: 2.600455e-11 5.985460e-13 5.141438e-14
4: 2.889447e-10 1.277245e-11 5.524635e-14
5: 6.002455e-14 5.435667e-14 1.769529e-03
---
1996: 3.726710e-05 7.212366e-02 5.321210e-04
1997: 2.202306e-02 1.658209e-03 3.513505e-04
1998: 1.212861e-06 3.638522e-06 1.065393e-03
1999: 6.602095e-14 8.299553e-11 8.755509e-11
2000: 4.450144e-02 4.819948e-02 5.622873e-06
broad_type symbol K01 K02 K03 K04
1: inhibitory ADARB2 2.766723e-01 5.991360e-14 5.152359e-14 4.492247e-14
2: inhibitory CXCL14 1.379377e-01 5.571658e-14 4.773595e-14 4.462466e-14
3: inhibitory RELN 1.508838e-01 6.109794e-10 4.931309e-14 5.153243e-14
4: inhibitory GRIK3 3.130814e-14 6.348075e-14 4.667898e-14 4.686951e-14
5: inhibitory NFIB 1.413734e-01 7.127073e-14 8.140147e-04 5.046699e-14
---
1996: inhibitory AP3M2 8.741122e-04 1.222177e-04 3.274595e-03 5.849801e-02
1997: inhibitory GALNT7 5.033646e-05 2.794727e-06 1.058547e-01 5.321011e-05
1998: inhibitory PSMC4 2.801749e-10 7.015702e-14 1.469305e-07 7.831020e-03
1999: inhibitory PLEKHO1 5.596815e-09 1.960970e-10 1.029898e-04 1.548516e-02
2000: inhibitory RIMBP2 2.230634e-02 2.612701e-05 6.154704e-02 1.679517e-03
K05 K06 K07 K08 K09
1: 2.283793e-08 3.947332e-14 2.328855e-04 6.450310e-14 5.163735e-14
2: 5.604603e-14 3.343626e-14 2.259620e-10 5.872823e-14 5.196091e-14
3: 8.100962e-14 4.716569e-14 9.932720e-07 6.907554e-14 5.915468e-14
4: 4.915364e-14 4.229986e-02 3.983400e-14 2.987459e-10 5.255663e-14
5: 6.988242e-08 5.020048e-14 4.110753e-02 6.730828e-14 5.702409e-14
---
1996: 7.070438e-04 3.291708e-04 2.208931e-03 4.015153e-06 1.242075e-03
1997: 4.723046e-03 8.489098e-03 1.545351e-03 9.567540e-08 3.160690e-04
1998: 2.715698e-13 1.165791e-07 4.583328e-07 1.401585e-10 4.185940e-02
1999: 3.423962e-11 6.956701e-03 5.497471e-02 2.357856e-05 1.629559e-03
2000: 1.644017e-04 4.135851e-03 3.908925e-02 3.585112e-03 5.206685e-03
K10 K11 K12 K13 K14
1: 6.581096e-14 5.848218e-14 5.014993e-14 5.269369e-14 7.084830e-14
2: 5.748249e-14 5.548787e-14 4.617014e-14 4.848846e-14 6.675626e-14
3: 6.544875e-14 6.327432e-14 1.723515e-04 5.991200e-14 7.888176e-14
4: 6.218592e-14 1.420635e-12 7.535486e-02 5.671000e-14 6.399254e-14
5: 2.288153e-08 5.771135e-14 4.995881e-14 1.649013e-11 7.027149e-07
---
1996: 7.209483e-05 9.194262e-05 5.142262e-06 8.810467e-06 3.482595e-05
1997: 3.049385e-03 5.868211e-03 1.995241e-09 1.625130e-04 1.153223e-03
1998: 1.257456e-12 1.710540e-13 1.095095e-10 3.123679e-10 7.798892e-14
1999: 1.064204e-06 6.938298e-07 3.191425e-08 1.844853e-03 2.886933e-07
2000: 3.542726e-03 2.796509e-03 3.573793e-06 4.715719e-02 1.432758e-02
broad_type symbol K01 K02 K03 K04
1: astrocytes TNC 5.508544e-14 5.355202e-14 6.048987e-14 4.995452e-14
2: astrocytes CD44 4.826442e-07 4.937742e-14 5.950754e-14 3.523831e-12
3: astrocytes CABLES1 5.820693e-14 5.887997e-05 4.757135e-08 4.713368e-14
4: astrocytes WIF1 5.403599e-14 6.650400e-02 2.452031e-06 4.419095e-14
5: astrocytes CP 1.080412e-08 3.779148e-14 5.126544e-14 2.749986e-02
---
1996: astrocytes UBXN11 5.337963e-14 5.683441e-14 5.923437e-14 3.196347e-02
1997: astrocytes ATP6AP1L 4.828945e-06 2.902379e-02 5.262668e-03 1.926480e-02
1998: astrocytes PSMG4 2.861397e-07 3.263370e-05 5.375626e-06 2.400370e-03
1999: astrocytes AC010615.4 2.346774e-04 1.821599e-02 2.426731e-04 1.451961e-02
2000: astrocytes ADPRHL2 8.498947e-10 5.635027e-14 6.229237e-14 3.195369e-02
K05 K06 K07 K08 K09
1: 5.968234e-14 4.923187e-14 1.718578e-01 6.509417e-14 9.124448e-09
2: 6.024823e-14 4.912547e-14 7.937184e-02 6.758393e-14 6.462610e-14
3: 5.167050e-04 1.514491e-01 5.048680e-14 4.390321e-06 6.674808e-14
4: 6.562571e-14 3.256467e-02 4.461540e-14 2.496363e-11 6.560003e-14
5: 5.039962e-14 3.853433e-14 5.988266e-02 5.847123e-14 5.462482e-14
---
1996: 5.930296e-14 5.249242e-14 5.484194e-14 6.450261e-14 6.505828e-14
1997: 4.168829e-03 1.257576e-02 1.132977e-02 1.634542e-03 9.741721e-03
1998: 7.532285e-03 4.823328e-04 5.443867e-05 5.840001e-02 7.565350e-07
1999: 3.774251e-04 2.423429e-03 7.216716e-05 3.720462e-06 1.704744e-03
2000: 6.195603e-14 5.383538e-14 3.620362e-09 6.673996e-14 8.552366e-14
K10 K11 K12 K13 K14
1: 7.412629e-14 6.262882e-14 7.583952e-14 6.640169e-14 1.530919e-04
2: 7.141941e-14 6.491720e-14 5.565260e-14 6.617291e-14 1.095052e-01
3: 3.756261e-09 3.150442e-09 6.114988e-09 2.471356e-06 5.486905e-14
4: 7.839263e-14 3.319385e-12 5.992744e-14 2.627321e-07 4.706317e-14
5: 6.529651e-14 5.739577e-14 4.998159e-14 5.322422e-14 3.296692e-03
---
1996: 7.080094e-14 5.976464e-14 3.635713e-11 6.485558e-14 5.301219e-14
1997: 8.566273e-14 6.827795e-05 9.983806e-04 5.502123e-02 1.927157e-04
1998: 1.628670e-02 2.637286e-07 7.809776e-03 5.049444e-02 2.795895e-02
1999: 8.473280e-14 2.235145e-04 3.060273e-05 3.839901e-02 6.404636e-03
2000: 1.999261e-08 6.588056e-14 5.859846e-14 6.597820e-14 1.548130e-10
broad_type symbol K01 K02 K03
1: endo_stromal ST6GALNAC3 7.172008e-14 7.012454e-03 6.281933e-14
2: endo_stromal MECOM 7.203146e-14 5.680333e-02 6.299274e-14
3: endo_stromal SPARCL1 7.300515e-14 1.056339e-02 6.461209e-14
4: endo_stromal ELOVL7 7.136825e-14 5.803847e-03 6.229239e-14
5: endo_stromal DOCK9 7.182232e-14 4.991011e-03 6.308586e-14
---
1996: endo_stromal NOX4 5.978272e-14 6.474239e-14 1.374485e-12
1997: endo_stromal DPM1 7.257842e-14 4.533263e-04 6.354589e-14
1998: endo_stromal PPARGC1B 3.608014e-05 7.201470e-11 3.878628e-08
1999: endo_stromal PIM3 6.939683e-14 1.377866e-06 6.234442e-14
2000: endo_stromal DFFA 7.150331e-14 1.326031e-06 6.395182e-14
K04 K05 K06 K07 K08
1: 1.498302e-03 5.419028e-14 1.540184e-01 5.963086e-14 3.144429e-14
2: 1.236490e-02 5.492910e-14 5.139181e-02 6.014345e-14 3.331951e-14
3: 1.158405e-01 5.890062e-14 2.707504e-02 6.170423e-14 4.562174e-14
4: 4.569394e-04 5.283272e-14 1.364212e-01 5.894344e-14 2.882201e-14
5: 5.873066e-04 5.430258e-14 8.070333e-02 5.980567e-14 3.240603e-14
---
1996: 6.975139e-14 4.146344e-14 7.086873e-14 4.892767e-14 4.517662e-14
1997: 3.009232e-04 5.931691e-14 2.313132e-05 6.122265e-14 4.459234e-14
1998: 7.360141e-07 7.801095e-02 2.178976e-07 2.027907e-06 8.797911e-03
1999: 2.280931e-02 5.600714e-14 3.117069e-07 5.926342e-14 3.314743e-14
2000: 2.669230e-07 5.687601e-14 7.704663e-06 6.013716e-14 4.168505e-14
K09 K10 K11 K12 K13
1: 4.070986e-03 7.764734e-14 1.575869e-02 6.081887e-02 7.224379e-14
2: 3.891529e-03 7.805406e-14 1.164949e-02 5.016632e-02 7.239223e-14
3: 8.166619e-02 7.954355e-14 1.154343e-02 1.597070e-04 7.379952e-14
4: 1.002880e-03 7.678902e-14 1.164382e-02 2.856780e-02 7.164039e-14
5: 3.295122e-03 7.759341e-14 1.502902e-02 8.839820e-02 7.230092e-14
---
1996: 5.349982e-14 6.543058e-14 6.873331e-14 6.025480e-14 6.051628e-14
1997: 5.276834e-03 7.940677e-14 4.601825e-05 3.466727e-02 7.274670e-14
1998: 1.010242e-09 2.105622e-03 8.401897e-12 1.770163e-09 5.485598e-03
1999: 2.637981e-03 7.546770e-14 1.568118e-09 5.667143e-08 6.966712e-14
2000: 7.066721e-04 7.830004e-14 1.346238e-05 4.005797e-02 7.240697e-14
K14 K15 K16 K17 K18
1: 6.127805e-14 2.284951e-02 3.181706e-02 2.408074e-02 6.163245e-14
2: 6.152060e-14 6.260855e-02 2.273696e-02 2.504531e-02 6.328875e-14
3: 6.588025e-14 2.023795e-02 1.629141e-03 7.611883e-03 6.594707e-14
4: 5.991571e-14 1.159444e-02 8.649754e-02 2.305277e-02 6.077842e-14
5: 6.150957e-14 1.481647e-02 5.201353e-02 1.196794e-02 6.217186e-14
---
1996: 5.380636e-14 8.047601e-14 1.965383e-04 7.252267e-14 7.393960e-02
1997: 6.623165e-14 1.676482e-02 1.289766e-05 1.160637e-04 6.484637e-14
1998: 9.533727e-10 6.903673e-06 7.443941e-06 6.511035e-06 6.605045e-06
1999: 6.294554e-14 2.294094e-03 4.690200e-02 2.059725e-05 6.151744e-14
2000: 6.431186e-14 4.748313e-04 3.435668e-04 2.183126e-03 6.432454e-14
broad_type symbol K01 K02 K03 K04
1: microglia PRKY 6.770564e-14 2.503590e-05 5.318287e-14 8.432268e-12
2: microglia SERPINE1 3.279561e-04 5.538078e-14 3.039992e-07 5.671505e-03
3: microglia TMEM163 5.566815e-14 5.521313e-14 5.073022e-14 6.514299e-14
4: microglia P2RY12 2.028914e-12 1.539024e-01 4.951982e-14 2.482062e-04
5: microglia CX3CR1 5.511223e-14 1.305579e-01 4.749542e-14 8.788986e-05
---
1996: microglia UCK2 6.263724e-09 5.694415e-04 5.960537e-13 1.383746e-04
1997: microglia SPDYE1 5.642756e-14 5.520548e-03 5.403421e-05 1.160097e-05
1998: microglia HPS5 3.522207e-05 8.088349e-07 3.114857e-02 6.126449e-07
1999: microglia MEF2C 3.241175e-03 4.122203e-02 2.679070e-03 2.940959e-02
2000: microglia NHLH1 5.264484e-14 3.144937e-14 3.893406e-14 4.712589e-14
K05 K06 K07 K08 K09
1: 6.900231e-03 4.930286e-03 5.900456e-14 6.029417e-14 6.959494e-14
2: 5.823211e-14 7.216537e-02 6.057506e-14 5.697103e-14 6.911213e-14
3: 5.757283e-14 4.590347e-14 5.922927e-14 1.535616e-01 6.320724e-14
4: 6.169949e-14 5.040362e-14 6.216577e-14 3.801733e-08 6.861033e-14
5: 6.120999e-14 4.666223e-14 6.106205e-14 5.156635e-09 6.607159e-14
---
1996: 6.327394e-14 9.562713e-11 6.271645e-14 3.100203e-02 3.764879e-02
1997: 5.279486e-13 4.826186e-14 1.361846e-13 1.327453e-02 6.737341e-14
1998: 6.374449e-14 1.013532e-02 6.439315e-14 3.106419e-02 7.126954e-14
1999: 3.366089e-04 3.674704e-02 2.947039e-02 4.782318e-04 6.994018e-02
2000: 3.896336e-14 2.888198e-03 3.913413e-14 3.775779e-14 5.113412e-14
K10 K11 K12
1: 7.501088e-02 6.424984e-14 2.950255e-08
2: 7.063803e-14 6.239985e-14 1.996000e-13
3: 6.511028e-14 6.034444e-14 2.682775e-09
4: 9.049040e-07 6.477058e-14 6.606174e-08
5: 1.800022e-09 6.302235e-14 6.856641e-13
---
1996: 5.812981e-07 6.640436e-14 3.369117e-06
1997: 7.005570e-14 6.578345e-14 6.813124e-14
1998: 2.254832e-03 6.756021e-14 3.280228e-04
1999: 1.086983e-02 6.844830e-02 2.942337e-02
2000: 4.319230e-14 4.615849e-14 6.071050e-14
broad_type symbol K01 K02 K03 K04
1: immune THEMIS 1.033382e-06 1.308585e-01 1.575729e-12 8.768470e-03
2: immune CAMK4 2.996375e-12 9.535780e-02 4.159182e-14 7.775349e-02
3: immune MZB1 3.249409e-14 1.479838e-14 3.429147e-14 2.980185e-14
4: immune AOAH 1.324841e-07 1.351354e-01 4.565851e-14 1.174073e-04
5: immune PRKCH 1.600238e-06 1.274343e-01 4.366975e-12 6.585007e-04
---
1996: immune AC005833.1 3.432674e-14 2.340261e-14 3.533076e-14 3.208345e-14
1997: immune PBK 2.189431e-18 1.763067e-18 2.204274e-18 2.070107e-18
1998: immune ZNF266 5.631173e-02 1.617284e-03 4.686776e-14 3.946949e-14
1999: immune LHFPL5 4.771474e-14 1.552121e-03 1.347289e-05 4.004168e-14
2000: immune OGG1 6.451526e-02 8.146560e-11 4.247637e-14 3.959779e-14
K05 K06 K07 K08
1: 1.000951e-09 4.450650e-14 2.820396e-14 4.637007e-12
2: 2.224153e-10 4.318051e-14 2.484648e-14 4.259512e-14
3: 3.353328e-14 4.097989e-14 9.349851e-02 3.674409e-14
4: 2.842325e-04 4.818934e-07 3.326580e-14 2.180263e-05
5: 2.288542e-07 4.479990e-14 2.895130e-14 4.430732e-14
---
1996: 3.360024e-02 3.564273e-14 3.605409e-14 4.100123e-14
1997: 2.277688e-18 2.265090e-18 1.725560e-18 2.237138e-18
1998: 2.102843e-11 4.506053e-14 3.240238e-14 4.728729e-14
1999: 1.498920e-09 4.343182e-14 8.886839e-03 7.191751e-13
2000: 3.961926e-14 4.392731e-14 3.245002e-14 8.102254e-06devtools::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 2021-09-24
- Packages -------------------------------------------------------------------
! package * version date lib
abind 1.4-5 2016-07-21 [2]
assertthat * 0.2.1 2019-03-21 [2]
Biobase * 2.50.0 2020-10-27 [1]
BiocGenerics * 0.36.1 2021-04-16 [1]
BiocManager 1.30.16 2021-06-15 [1]
BiocParallel * 1.24.1 2020-11-06 [1]
BiocStyle * 2.18.1 2020-11-24 [1]
bitops 1.0-7 2021-04-24 [2]
bslib 0.3.0 2021-09-02 [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]
circlize * 0.4.13 2021-06-09 [1]
cli 3.0.1 2021-07-17 [1]
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 2.0-2 2021-06-24 [1]
ComplexHeatmap * 2.6.2 2020-11-12 [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]
deldir 0.2-10 2021-02-16 [2]
desc 1.3.0 2021-03-05 [2]
devtools 2.4.2 2021-06-07 [1]
digest 0.6.27 2020-10-24 [2]
dplyr 1.0.7 2021-06-18 [2]
ellipsis 0.3.2 2021-04-29 [2]
evaluate 0.14 2019-05-28 [2]
fansi 0.5.0 2021-05-25 [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 1.1-5 2021-05-28 [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]
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]
ggplot.multistats * 1.0.0 2019-10-28 [1]
ggplot2 * 3.3.5 2021-06-25 [1]
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]
gtable 0.3.0 2019-03-25 [2]
here 1.0.1 2020-12-13 [2]
hexbin 1.28.2 2021-01-08 [2]
highr 0.9 2021-04-16 [2]
htmltools 0.5.2 2021-08-25 [2]
htmlwidgets 1.5.4 2021-09-08 [2]
httpuv 1.6.3 2021-09-09 [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 0.1.4 2021-04-26 [2]
jsonlite 1.7.2 2020-12-09 [2]
KernSmooth 2.23-20 2021-05-03 [2]
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magick 2.7.2 2021-05-02 [2]
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mime 0.11 2021-06-23 [1]
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pillar 1.6.2 2021-07-29 [1]
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pkgload 1.2.2 2021-09-11 [2]
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plyr 1.8.6 2020-03-03 [2]
png 0.1-7 2013-12-03 [2]
polyclip 1.10-0 2019-03-14 [2]
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processx 3.5.2 2021-04-30 [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 2.5.1 2021-08-19 [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 1.0.7 2021-07-07 [1]
RcppAnnoy 0.0.19 2021-07-30 [1]
RCurl 1.98-1.4 2021-08-17 [1]
registry 0.5-1 2019-03-05 [1]
remotes 2.4.0 2021-06-02 [1]
reshape2 1.4.4 2020-04-09 [2]
reticulate * 1.21 2021-09-14 [2]
rjson 0.2.20 2018-06-08 [1]
rlang 0.4.11 2021-04-30 [2]
rmarkdown 2.11 2021-09-14 [1]
ROCR 1.0-11 2020-05-02 [2]
rpart 4.1-15 2019-04-12 [2]
rprojroot 2.0.2 2020-11-15 [2]
Rtsne 0.15 2018-11-10 [2]
S4Vectors * 0.28.1 2020-12-09 [1]
sass 0.4.0 2021-05-12 [2]
scales * 1.1.1 2020-05-11 [2]
scattermore 0.7 2020-11-24 [2]
sctransform 0.3.2 2020-12-16 [2]
seriation * 1.3.0 2021-06-30 [1]
sessioninfo 1.1.1 2018-11-05 [1]
Seurat * 4.0.4 2021-08-20 [2]
SeuratObject * 4.0.2 2021-06-09 [2]
shape 1.4.6 2021-05-19 [1]
shiny 1.6.0 2021-01-25 [2]
SingleCellExperiment * 1.12.0 2020-10-27 [1]
spatstat.core 2.3-0 2021-07-16 [2]
spatstat.data 2.1-0 2021-03-21 [2]
spatstat.geom 2.2-2 2021-07-12 [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 3.0.4 2021-07-01 [2]
tibble 3.1.4 2021-08-25 [1]
tidyr 1.1.3 2021-03-03 [2]
tidyselect 1.1.1 2021-04-30 [2]
TSP 1.1-10 2020-04-17 [1]
usethis 2.0.1 2021-02-10 [1]
utf8 1.2.2 2021-07-24 [1]
uwot 0.1.10 2020-12-15 [2]
vctrs 0.3.8 2021-04-29 [2]
viridis * 0.6.1 2021-05-11 [1]
viridisLite * 0.4.0 2021-04-13 [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 0.26 2021-09-14 [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_1.21
[3] fgsea_1.16.0 BiocParallel_1.24.1
[5] ggplot.multistats_1.0.0 seriation_1.3.0
[7] ComplexHeatmap_2.6.2 SeuratObject_4.0.2
[9] Seurat_4.0.4 future_1.22.1
[11] Matrix_1.3-4 SingleCellExperiment_1.12.0
[13] SummarizedExperiment_1.20.0 Biobase_2.50.0
[15] GenomicRanges_1.42.0 GenomeInfoDb_1.26.7
[17] IRanges_2.24.1 S4Vectors_0.28.1
[19] BiocGenerics_0.36.1 MatrixGenerics_1.2.1
[21] matrixStats_0.60.1 purrr_0.3.4
[23] forcats_0.5.1 ggplot2_3.3.5
[25] scales_1.1.1 viridis_0.6.1
[27] viridisLite_0.4.0 assertthat_0.2.1
[29] stringr_1.4.0 data.table_1.14.0
[31] magrittr_2.0.1 circlize_0.4.13
[33] RColorBrewer_1.1-2 BiocStyle_2.18.1
[35] colorout_1.2-2 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] utf8_1.2.2 tidyselect_1.1.1 htmlwidgets_1.5.4
[4] TSP_1.1-10 Rtsne_0.15 devtools_2.4.2
[7] munsell_0.5.0 codetools_0.2-18 ica_1.0-2
[10] miniUI_0.1.1.1 withr_2.4.2 colorspace_2.0-2
[13] highr_0.9 knitr_1.34 ROCR_1.0-11
[16] tensor_1.5 listenv_0.8.0 git2r_0.28.0
[19] GenomeInfoDbData_1.2.4 polyclip_1.10-0 rprojroot_2.0.2
[22] parallelly_1.28.1 vctrs_0.3.8 generics_0.1.0
[25] xfun_0.26 R6_2.5.1 clue_0.3-59
[28] bitops_1.0-7 spatstat.utils_2.2-0 cachem_1.0.6
[31] DelayedArray_0.16.3 promises_1.2.0.1 gtable_0.3.0
[34] Cairo_1.5-12.2 globals_0.14.0 processx_3.5.2
[37] goftest_1.2-2 rlang_0.4.11 GlobalOptions_0.1.2
[40] splines_4.0.5 lazyeval_0.2.2 hexbin_1.28.2
[43] spatstat.geom_2.2-2 BiocManager_1.30.16 yaml_2.2.1
[46] reshape2_1.4.4 abind_1.4-5 httpuv_1.6.3
[49] usethis_2.0.1 tools_4.0.5 ellipsis_0.3.2
[52] spatstat.core_2.3-0 jquerylib_0.1.4 sessioninfo_1.1.1
[55] ggridges_0.5.3 Rcpp_1.0.7 plyr_1.8.6
[58] zlibbioc_1.36.0 RCurl_1.98-1.4 prettyunits_1.1.1
[61] ps_1.6.0 rpart_4.1-15 deldir_0.2-10
[64] pbapply_1.4-3 GetoptLong_1.0.5 cowplot_1.1.1
[67] zoo_1.8-9 ggrepel_0.9.1 cluster_2.1.2
[70] fs_1.5.0 here_1.0.1 magick_2.7.2
[73] scattermore_0.7 lmtest_0.9-38 RANN_2.6.1
[76] fitdistrplus_1.1-5 pkgload_1.2.2 patchwork_1.1.1
[79] mime_0.11 evaluate_0.14 xtable_1.8-4
[82] gridExtra_2.3 shape_1.4.6 testthat_3.0.4
[85] compiler_4.0.5 tibble_3.1.4 KernSmooth_2.23-20
[88] crayon_1.4.1 htmltools_0.5.2 mgcv_1.8-36
[91] later_1.3.0 tidyr_1.1.3 DBI_1.1.1
[94] MASS_7.3-54 rappdirs_0.3.3 cli_3.0.1
[97] igraph_1.2.6 pkgconfig_2.0.3 registry_0.5-1
[100] plotly_4.9.4.1 spatstat.sparse_2.0-0 foreach_1.5.1
[103] bslib_0.3.0 XVector_0.30.0 callr_3.7.0
[106] digest_0.6.27 sctransform_0.3.2 RcppAnnoy_0.0.19
[109] spatstat.data_2.1-0 rmarkdown_2.11 leiden_0.3.8
[112] fastmatch_1.1-3 uwot_0.1.10 shiny_1.6.0
[115] rjson_0.2.20 lifecycle_1.0.0 nlme_3.1-153
[118] jsonlite_1.7.2 desc_1.3.0 fansi_0.5.0
[121] pillar_1.6.2 lattice_0.20-44 fastmap_1.1.0
[124] httr_1.4.2 pkgbuild_1.2.0 survival_3.2-13
[127] remotes_2.4.0 glue_1.4.2 png_0.1-7
[130] iterators_1.0.13 stringi_1.7.4 sass_0.4.0
[133] memoise_2.0.0 dplyr_1.0.7 irlba_2.3.3
[136] future.apply_1.8.1