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1 Data Summary


2 BridgeSettings

Configuration Settings for the Workflow

species tissue metadata genesets genetype min_umi_per_cell max_mt_percent min_genes_per_cell min_cell scr_th seu_nrmlz_method seu_scale_factor seu_n_hvg seu_n_dim seu_k_param seu_cluster_res harmony tsne spr_n_dim mrk_logfc mrk_min_pct mrk_only_pos mrk_test mrk_top_n adt trajectory traj_var_gene traj_top_n pipe_version
hs skin sample_based none hgnc_symbol 750 15 250 3 0.25 LogNormalize 1e+06 2000 30 20 0.7 sample FALSE 30 0.25 0.5 TRUE wilcox 0 FALSE none 1000 50 1.0.0

3 BridgeQC

3.1 Sample-level Characteristics and Quality Control Metrics

3.1.1 Metadata

sample disease skin_type tissue sample_id
NS-AR001 Control Nonlesion Skin S1
NS-AR003 Control Nonlesion Skin S2
NS-AR004 Control Nonlesion Skin S3
NS-AR005 Control Nonlesion Skin S4
NS-AR006 Control Nonlesion Skin S5
NS-AR007 Control Nonlesion Skin S6
NS-AR008 Control Nonlesion Skin S7
NS-AR009 Control Nonlesion Skin S8
PN-30696 PSO Nonlesion Skin S9
PN-30696V3 PSO Nonlesion Skin S10
PN-31170 PSO Nonlesion Skin S11
PN-31277 PSO Nonlesion Skin S12
PN-369PC PSO Nonlesion Skin S13
PN-5851 PSO Nonlesion Skin S14
PN-7802ED PSO Nonlesion Skin S15
PN-8659ED PSO Nonlesion Skin S16
PN-8940 PSO Nonlesion Skin S17
PN-929 PSO Nonlesion Skin S18
PN-9709PC PSO Nonlesion Skin S19
PP-30696 PSO Lesion Skin S20
PP-30696V3 PSO Lesion Skin S21
PP-31170 PSO Lesion Skin S22
PP-31277 PSO Lesion Skin S23
PP-31499 PSO Lesion Skin S24
PP-369PC PSO Lesion Skin S25
PP-5851 PSO Lesion Skin S26
PP-6215A PSO Lesion Skin S27
PP-6215B PSO Lesion Skin S28
PP-7802ED PSO Lesion Skin S29
PP-8659ED PSO Lesion Skin S30
PP-8940 PSO Lesion Skin S31
PP-929 PSO Lesion Skin S32
PP-9709PC PSO Lesion Skin S33

3.1.2 Cells & Genes (RNA)

sample_id pre_qc_gene pre_qc_cell post_qc_gene post_qc_cell
S1 21,018 1,148 17,470 869
S2 21,473 2,345 18,157 2,032
S3 21,644 1,156 18,085 972
S4 20,585 1,064 17,121 901
S5 20,488 2,438 17,480 2,169
S6 21,940 2,880 18,873 2,650
S7 14,592 208 9,968 65
S8 20,805 2,295 17,635 2,085
S9 20,079 4,024 17,020 3,751
S10 19,855 1,563 16,370 1,207
S11 20,811 1,653 17,631 1,402
S12 21,293 3,522 18,057 3,255
S13 20,349 1,367 17,062 1,096
S14 20,335 3,386 16,909 2,879
S15 22,182 5,010 18,623 3,698
S16 22,409 3,273 19,152 2,471
S17 22,472 5,577 19,376 5,115
S18 19,969 5,216 16,927 4,717
S19 18,322 927 15,109 761
S20 21,067 3,339 17,834 2,788
S21 21,210 2,101 17,531 1,405
S22 22,475 3,746 19,488 3,168
S23 21,398 3,044 18,304 2,747
S24 21,801 2,843 18,757 2,395
S25 21,516 2,105 18,390 1,774
S26 20,472 1,153 16,873 809
S27 22,271 3,440 19,164 3,212
S28 22,627 4,077 19,497 3,808
S29 22,925 5,982 19,526 4,600
S30 22,668 3,177 19,414 2,687
S31 22,288 3,929 19,207 3,390
S32 21,478 5,106 18,435 4,315
S33 20,574 2,994 17,473 2,778

3.1.3 UMI per cell (RNA)

Vales are post-QC.

sample_id min 0% 25% 50% 75% 100% max
S1 759 759 6,000 8,183 10,665 54,022 54,022
S2 751 751 8,481 13,656 19,624 54,609 54,609
S3 752 752 4,681 7,584 11,065 207,862 207,862
S4 751 751 4,645 7,713 16,742 261,100 261,100
S5 751 751 6,517 10,442 16,483 188,158 188,158
S6 770 770 7,502 13,544 17,142 82,763 82,763
S7 795 795 3,566 5,498 7,596 41,285 41,285
S8 752 752 5,885 9,198 11,358 47,767 47,767
S9 750 750 4,447 6,168 8,280 28,999 28,999
S10 752 752 9,012 12,346 17,034 62,224 62,224
S11 751 751 2,872 5,335 8,798 75,021 75,021
S12 751 751 2,934 6,930 10,844 72,570 72,570
S13 758 758 3,990 7,296 12,308 54,000 54,000
S14 752 752 5,573 7,361 9,671 56,430 56,430
S15 756 756 2,910 6,076 8,774 48,617 48,617
S16 750 750 4,084 6,993 11,302 119,244 119,244
S17 750 750 4,198 8,481 12,540 51,723 51,723
S18 778 778 6,426 9,036 11,851 51,642 51,642
S19 751 751 6,712 11,750 15,767 61,526 61,526
S20 751 751 3,188 7,261 12,164 94,706 94,706
S21 750 750 3,128 6,951 17,405 84,908 84,908
S22 750 750 4,148 9,386 19,072 93,007 93,007
S23 750 750 5,688 13,683 21,342 90,463 90,463
S24 770 770 5,530 16,064 26,234 91,984 91,984
S25 750 750 7,173 15,594 25,385 105,019 105,019
S26 750 750 8,693 16,253 25,801 126,353 126,353
S27 760 760 4,066 10,548 20,321 112,201 112,201
S28 755 755 4,210 10,302 19,992 120,547 120,547
S29 753 753 5,269 9,740 16,104 57,299 57,299
S30 759 759 3,881 6,788 11,608 78,449 78,449
S31 750 750 2,899 5,770 12,609 112,431 112,431
S32 772 772 8,142 11,714 16,932 68,083 68,083
S33 755 755 3,096 7,483 9,936 38,875 38,875

3.1.4 Gene per cell (RNA)

Vales are post-QC.

sample_id min 0% 25% 50% 75% 100% max
S1 369 369 1,986 2,725 3,243 6,293 6,293
S2 338 338 2,268 2,912 3,604 7,156 7,156
S3 334 334 1,704 2,646 3,362 9,038 9,038
S4 330 330 1,783 2,465 3,360 9,378 9,378
S5 314 314 2,026 2,624 3,442 9,582 9,582
S6 267 267 2,502 3,348 3,874 7,948 7,948
S7 355 355 1,109 1,893 2,479 5,808 5,808
S8 413 413 2,032 2,547 2,971 6,150 6,150
S9 300 300 1,358 1,654 1,996 4,411 4,411
S10 342 342 2,422 2,947 3,475 7,880 7,880
S11 266 266 1,215 1,884 2,602 7,822 7,822
S12 283 283 1,134 1,770 2,312 5,979 5,979
S13 344 344 1,554 2,170 2,780 7,558 7,558
S14 366 366 1,627 1,981 2,424 6,536 6,536
S15 275 275 1,187 1,966 2,434 5,802 5,802
S16 322 322 1,562 2,308 3,096 8,702 8,702
S17 317 317 1,618 2,275 2,797 6,161 6,161
S18 421 421 1,647 2,027 2,433 5,194 5,194
S19 328 328 1,869 2,386 2,790 6,017 6,017
S20 293 293 1,223 2,100 2,734 6,685 6,685
S21 379 379 1,361 2,342 3,571 7,784 7,784
S22 268 268 1,521 2,632 3,566 7,939 7,939
S23 287 287 1,708 2,736 3,442 7,309 7,309
S24 296 296 1,924 3,354 4,130 6,912 6,912
S25 294 294 2,165 3,399 4,260 7,179 7,179
S26 334 334 2,707 3,775 4,692 8,842 8,842
S27 374 374 1,544 2,824 3,879 7,196 7,196
S28 300 300 1,619 2,788 3,838 7,376 7,376
S29 303 303 1,826 2,670 3,369 5,699 5,699
S30 350 350 1,528 2,287 3,123 8,279 8,279
S31 256 256 1,254 1,936 3,012 7,959 7,959
S32 278 278 2,192 2,711 3,346 5,974 5,974
S33 345 345 1,247 1,922 2,333 4,951 4,951

3.1.5 Mitochondrial (%) per cell (RNA)

Vales are post-QC.

sample_id min 0% 25% 50% 75% 100% max
S1 0.00 0.00 4.29 6.19 8.39 14.93 14.93
S2 0.00 0.00 2.41 3.23 4.41 14.85 14.85
S3 0.00 0.00 2.43 3.92 5.60 14.89 14.89
S4 0.00 0.00 0.48 1.44 3.47 14.97 14.97
S5 0.05 0.05 2.13 2.96 4.28 14.62 14.62
S6 0.00 0.00 1.27 3.47 5.07 14.77 14.77
S7 1.23 1.23 3.58 4.70 6.34 13.96 13.96
S8 0.00 0.00 0.55 1.42 2.95 14.95 14.95
S9 0.00 0.00 1.84 2.38 3.17 14.76 14.76
S10 0.00 0.00 4.53 5.96 7.59 14.99 14.99
S11 0.02 0.02 2.05 2.94 4.05 14.93 14.93
S12 0.00 0.00 1.59 2.10 2.85 13.62 13.62
S13 0.03 0.03 0.85 1.53 2.79 14.80 14.80
S14 0.00 0.00 6.42 7.98 9.67 14.96 14.96
S15 0.08 0.08 3.78 5.09 6.90 15.00 15.00
S16 0.23 0.23 4.92 6.61 8.81 14.99 14.99
S17 0.05 0.05 2.94 3.63 4.42 14.80 14.80
S18 0.00 0.00 2.79 3.57 4.57 14.64 14.64
S19 0.00 0.00 2.87 3.62 4.56 14.68 14.68
S20 0.00 0.00 2.18 3.09 4.47 14.94 14.94
S21 0.00 0.00 5.35 7.37 9.89 14.99 14.99
S22 0.00 0.00 1.73 2.81 3.99 14.88 14.88
S23 0.00 0.00 1.43 2.04 2.68 14.90 14.90
S24 0.00 0.00 1.59 2.04 2.71 14.99 14.99
S25 0.00 0.00 2.22 2.99 3.73 14.80 14.80
S26 0.00 0.00 2.24 4.91 7.72 14.97 14.97
S27 0.00 0.00 2.22 2.94 3.75 14.84 14.84
S28 0.00 0.00 2.16 2.86 3.66 14.96 14.96
S29 0.00 0.00 4.60 6.08 7.57 14.99 14.99
S30 0.06 0.06 4.38 5.84 7.70 14.99 14.99
S31 0.02 0.02 2.46 3.37 4.55 14.99 14.99
S32 0.00 0.00 3.53 4.33 5.53 14.99 14.99
S33 0.00 0.00 0.73 1.42 2.03 14.46 14.46


3.2 Distribution Plots for Quality Control Metrics

Thresholds, represented by dashed lines, were implemented to filter the data and only retain cells of high quality.

3.2.1 UMI per cell

3.2.2 Gene per cell

3.2.3 Mitochondrial (%) per cell


3.3 Barcodes contamination

3.3.1 Raw count

Number of barcodes shared between pairs of samples post-QC.

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30 S31 S32 S33
S1 869 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0
S2 0 2032 3 2 1 0 0 0 0 2 0 1 0 2 1 3 1 0 0 0 1 0 0 0 1 0 0 0 1 1 1 0 0
S3 0 3 972 3 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 1
S4 0 2 3 901 1 0 0 0 0 0 0 1 0 0 2 1 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0
S5 0 1 0 1 2169 3 0 2 0 0 0 0 0 5 2 0 0 0 0 0 0 0 0 0 0 0 0 0 4 3 0 0 0
S6 0 0 0 0 3 2650 0 2 0 0 0 0 1 2 3 0 0 0 0 1 0 1 0 0 0 1 0 1 1 2 0 0 0
S7 0 0 0 0 0 0 65 1 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
S8 0 0 1 0 2 2 1 2085 0 1 0 0 0 2 0 1 0 2 0 0 3 0 0 0 2 0 0 0 3 2 0 0 0
S9 0 0 0 0 0 0 0 0 3751 0 1 18 6 0 0 0 30 22 2 16 0 17 14 13 6 0 20 20 1 1 16 25 20
S10 0 2 0 0 0 0 0 1 0 1207 0 1 0 3 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 2 0 0 0
S11 0 0 0 0 0 0 0 0 1 0 1402 6 0 0 0 1 4 11 2 6 0 30 8 3 4 0 4 6 0 1 4 7 3
S12 0 1 0 1 0 0 0 0 18 1 6 3255 6 0 1 0 17 29 2 18 0 9 13 9 4 0 15 12 0 0 15 13 17
S13 0 0 0 0 0 1 0 0 6 0 0 6 1096 0 0 0 8 11 1 5 1 5 3 3 15 0 0 4 0 0 4 8 4
S14 0 2 1 0 5 2 1 2 0 3 0 0 0 2879 1 2 0 0 0 2 2 0 1 0 0 0 0 1 6 4 0 0 1
S15 3 1 1 2 2 3 0 0 0 0 0 1 0 1 3698 2 0 0 0 0 1 1 0 0 1 0 0 1 3 3 0 0 0
S16 0 3 0 1 0 0 1 1 0 1 1 0 0 2 2 2471 0 0 0 0 0 1 0 0 0 0 0 0 1 4 0 0 0
S17 0 1 0 0 0 0 0 0 30 1 4 17 8 0 0 0 5115 35 8 18 0 28 24 10 12 0 18 32 0 1 21 36 19
S18 0 0 0 0 0 0 0 2 22 0 11 29 11 0 0 0 35 4717 4 16 0 17 24 21 10 0 22 25 0 1 25 23 15
S19 0 0 0 0 0 0 0 0 2 0 2 2 1 0 0 0 8 4 761 7 0 1 9 5 3 0 2 3 0 0 1 3 14
S20 0 0 0 0 0 1 0 0 16 0 6 18 5 2 0 0 18 16 7 2788 0 13 8 7 2 0 15 13 0 0 13 12 9
S21 0 1 0 0 0 0 0 3 0 0 0 0 1 2 1 0 0 0 0 0 1405 0 0 0 0 1 0 0 1 0 0 1 0
S22 0 0 0 0 0 1 0 0 17 0 30 9 5 0 1 1 28 17 1 13 0 3168 18 17 5 0 15 14 0 0 14 18 8
S23 0 0 0 0 0 0 0 0 14 0 8 13 3 1 0 0 24 24 9 8 0 18 2747 9 5 0 10 17 0 1 11 14 8
S24 0 0 0 0 0 0 0 0 13 0 3 9 3 0 0 0 10 21 5 7 0 17 9 2395 4 0 9 11 0 0 10 10 6
S25 0 1 0 0 0 0 0 2 6 0 4 4 15 0 1 0 12 10 3 2 0 5 5 4 1774 0 4 12 0 0 9 15 2
S26 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 809 0 0 1 1 0 0 0
S27 0 0 0 0 0 0 0 0 20 0 4 15 0 0 0 0 18 22 2 15 0 15 10 9 4 0 3212 12 1 0 15 23 13
S28 0 0 0 0 0 1 0 0 20 0 6 12 4 1 1 0 32 25 3 13 0 14 17 11 12 0 12 3808 1 0 23 25 16
S29 2 1 2 1 4 1 0 3 1 1 0 0 0 6 3 1 0 0 0 0 1 0 0 0 0 1 1 1 4600 3 0 0 0
S30 1 1 0 0 3 2 0 2 1 2 1 0 0 4 3 4 1 1 0 0 0 0 1 0 0 1 0 0 3 2687 1 0 0
S31 0 1 0 0 0 0 0 0 16 0 4 15 4 0 0 0 21 25 1 13 0 14 11 10 9 0 15 23 0 1 3390 17 11
S32 0 0 0 0 0 0 0 0 25 0 7 13 8 0 0 0 36 23 3 12 1 18 14 10 15 0 23 25 0 0 17 4315 17
S33 0 0 1 0 0 0 0 0 20 0 3 17 4 1 0 0 19 15 14 9 0 8 8 6 2 0 13 16 0 0 11 17 2778

3.3.2 Jaccard Index

Fraction (%) of barcodes shared between pairs of samples post-QC.

S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27 S28 S29 S30 S31 S32 S33
S1 100.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.00 0.07 0.06 0.00 0.00 0.00
S2 0.00 100.00 0.20 0.14 0.05 0.00 0e+00 0.00 0.00 0.12 0.00 0.04 0.00 0.08 0.03 0.13 0.03 0.00 0.00 0.00 0.06 0.00 0.00 0.00 0.05 0e+00 0.00 0.00 0.03 0.04 0.04 0.00 0.00
S3 0.00 0.20 100.00 0.32 0.00 0.00 0e+00 0.07 0.00 0.00 0.00 0.00 0.00 0.05 0.04 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.00 0.07 0.00 0.00 0.00 0.05
S4 0.00 0.14 0.32 100.00 0.07 0.00 0e+00 0.00 0.00 0.00 0.00 0.05 0.00 0.00 0.09 0.06 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.00 0.04 0.00 0.00 0.00 0.00
S5 0.00 0.05 0.00 0.07 100.00 0.12 0e+00 0.09 0.00 0.00 0.00 0.00 0.00 0.20 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.00 0.12 0.12 0.00 0.00 0.00
S6 0.00 0.00 0.00 0.00 0.12 100.00 0e+00 0.08 0.00 0.00 0.00 0.00 0.05 0.07 0.09 0.00 0.00 0.00 0.00 0.04 0.00 0.03 0.00 0.00 0.00 6e-02 0.00 0.03 0.03 0.07 0.00 0.00 0.00
S7 0.00 0.00 0.00 0.00 0.00 0.00 1e+02 0.09 0.00 0.00 0.00 0.00 0.00 0.07 0.00 0.08 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
S8 0.00 0.00 0.07 0.00 0.09 0.08 9e-02 100.00 0.00 0.06 0.00 0.00 0.00 0.08 0.00 0.04 0.00 0.06 0.00 0.00 0.17 0.00 0.00 0.00 0.10 0e+00 0.00 0.00 0.09 0.08 0.00 0.00 0.00
S9 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 100.00 0.00 0.04 0.51 0.25 0.00 0.00 0.00 0.68 0.52 0.09 0.49 0.00 0.49 0.43 0.42 0.22 0e+00 0.57 0.53 0.02 0.03 0.45 0.62 0.61
S10 0.00 0.12 0.00 0.00 0.00 0.00 0e+00 0.06 0.00 100.00 0.00 0.04 0.00 0.15 0.00 0.05 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.00 0.03 0.10 0.00 0.00 0.00
S11 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.04 0.00 100.00 0.26 0.00 0.00 0.00 0.05 0.12 0.36 0.18 0.29 0.00 1.31 0.39 0.16 0.25 0e+00 0.17 0.23 0.00 0.05 0.17 0.24 0.14
S12 0.00 0.04 0.00 0.05 0.00 0.00 0e+00 0.00 0.51 0.04 0.26 100.00 0.28 0.00 0.03 0.00 0.41 0.73 0.10 0.60 0.00 0.28 0.43 0.32 0.16 0e+00 0.46 0.34 0.00 0.00 0.45 0.34 0.56
S13 0.00 0.00 0.00 0.00 0.00 0.05 0e+00 0.00 0.25 0.00 0.00 0.28 100.00 0.00 0.00 0.00 0.26 0.38 0.11 0.26 0.08 0.23 0.16 0.17 1.05 0e+00 0.00 0.16 0.00 0.00 0.18 0.30 0.21
S14 0.00 0.08 0.05 0.00 0.20 0.07 7e-02 0.08 0.00 0.15 0.00 0.00 0.00 100.00 0.03 0.07 0.00 0.00 0.00 0.07 0.09 0.00 0.04 0.00 0.00 0e+00 0.00 0.03 0.16 0.14 0.00 0.00 0.04
S15 0.13 0.03 0.04 0.09 0.07 0.09 0e+00 0.00 0.00 0.00 0.00 0.03 0.00 0.03 100.00 0.06 0.00 0.00 0.00 0.00 0.04 0.03 0.00 0.00 0.04 0e+00 0.00 0.03 0.07 0.09 0.00 0.00 0.00
S16 0.00 0.13 0.00 0.06 0.00 0.00 8e-02 0.04 0.00 0.05 0.05 0.00 0.00 0.07 0.06 100.00 0.00 0.00 0.00 0.00 0.00 0.04 0.00 0.00 0.00 0e+00 0.00 0.00 0.03 0.16 0.00 0.00 0.00
S17 0.00 0.03 0.00 0.00 0.00 0.00 0e+00 0.00 0.68 0.03 0.12 0.41 0.26 0.00 0.00 0.00 100.00 0.71 0.27 0.46 0.00 0.68 0.61 0.27 0.35 0e+00 0.43 0.72 0.00 0.03 0.49 0.76 0.48
S18 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.06 0.52 0.00 0.36 0.73 0.38 0.00 0.00 0.00 0.71 100.00 0.15 0.43 0.00 0.43 0.64 0.59 0.31 0e+00 0.55 0.59 0.00 0.03 0.62 0.51 0.40
S19 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.09 0.00 0.18 0.10 0.11 0.00 0.00 0.00 0.27 0.15 100.00 0.39 0.00 0.05 0.51 0.32 0.24 0e+00 0.10 0.13 0.00 0.00 0.05 0.12 0.79
S20 0.00 0.00 0.00 0.00 0.00 0.04 0e+00 0.00 0.49 0.00 0.29 0.60 0.26 0.07 0.00 0.00 0.46 0.43 0.39 100.00 0.00 0.44 0.29 0.27 0.09 0e+00 0.50 0.39 0.00 0.00 0.42 0.34 0.32
S21 0.00 0.06 0.00 0.00 0.00 0.00 0e+00 0.17 0.00 0.00 0.00 0.00 0.08 0.09 0.04 0.00 0.00 0.00 0.00 0.00 100.00 0.00 0.00 0.00 0.00 9e-02 0.00 0.00 0.03 0.00 0.00 0.03 0.00
S22 0.00 0.00 0.00 0.00 0.00 0.03 0e+00 0.00 0.49 0.00 1.31 0.28 0.23 0.00 0.03 0.04 0.68 0.43 0.05 0.44 0.00 100.00 0.61 0.61 0.20 0e+00 0.47 0.40 0.00 0.00 0.43 0.48 0.27
S23 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.43 0.00 0.39 0.43 0.16 0.04 0.00 0.00 0.61 0.64 0.51 0.29 0.00 0.61 100.00 0.35 0.22 0e+00 0.34 0.52 0.00 0.04 0.36 0.40 0.29
S24 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.42 0.00 0.16 0.32 0.17 0.00 0.00 0.00 0.27 0.59 0.32 0.27 0.00 0.61 0.35 100.00 0.19 0e+00 0.32 0.35 0.00 0.00 0.35 0.30 0.23
S25 0.00 0.05 0.00 0.00 0.00 0.00 0e+00 0.10 0.22 0.00 0.25 0.16 1.05 0.00 0.04 0.00 0.35 0.31 0.24 0.09 0.00 0.20 0.22 0.19 100.00 0e+00 0.16 0.43 0.00 0.00 0.35 0.49 0.09
S26 0.00 0.00 0.00 0.00 0.00 0.06 0e+00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.09 0.00 0.00 0.00 0.00 1e+02 0.00 0.00 0.04 0.06 0.00 0.00 0.00
S27 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.57 0.00 0.17 0.46 0.00 0.00 0.00 0.00 0.43 0.55 0.10 0.50 0.00 0.47 0.34 0.32 0.16 0e+00 100.00 0.34 0.03 0.00 0.45 0.61 0.43
S28 0.00 0.00 0.00 0.00 0.00 0.03 0e+00 0.00 0.53 0.00 0.23 0.34 0.16 0.03 0.03 0.00 0.72 0.59 0.13 0.39 0.00 0.40 0.52 0.35 0.43 0e+00 0.34 100.00 0.02 0.00 0.64 0.62 0.49
S29 0.07 0.03 0.07 0.04 0.12 0.03 0e+00 0.09 0.02 0.03 0.00 0.00 0.00 0.16 0.07 0.03 0.00 0.00 0.00 0.00 0.03 0.00 0.00 0.00 0.00 4e-02 0.03 0.02 100.00 0.08 0.00 0.00 0.00
S30 0.06 0.04 0.00 0.00 0.12 0.07 0e+00 0.08 0.03 0.10 0.05 0.00 0.00 0.14 0.09 0.16 0.03 0.03 0.00 0.00 0.00 0.00 0.04 0.00 0.00 6e-02 0.00 0.00 0.08 100.00 0.03 0.00 0.00
S31 0.00 0.04 0.00 0.00 0.00 0.00 0e+00 0.00 0.45 0.00 0.17 0.45 0.18 0.00 0.00 0.00 0.49 0.62 0.05 0.42 0.00 0.43 0.36 0.35 0.35 0e+00 0.45 0.64 0.00 0.03 100.00 0.44 0.36
S32 0.00 0.00 0.00 0.00 0.00 0.00 0e+00 0.00 0.62 0.00 0.24 0.34 0.30 0.00 0.00 0.00 0.76 0.51 0.12 0.34 0.03 0.48 0.40 0.30 0.49 0e+00 0.61 0.62 0.00 0.00 0.44 100.00 0.48
S33 0.00 0.00 0.05 0.00 0.00 0.00 0e+00 0.00 0.61 0.00 0.14 0.56 0.21 0.04 0.00 0.00 0.48 0.40 0.79 0.32 0.00 0.27 0.29 0.23 0.09 0e+00 0.43 0.49 0.00 0.00 0.36 0.48 100.00


3.4 Doublet Cell Detection using Scrublet Scoring System

Observed scores are used for doublet classification. Dashed line indicates the threshold used to identify doublets.

3.4.1 Observed scores

3.4.2 Simulated scores


3.5 Impact of Quality Control on Cell, Gene, and UMI Abundances

3.5.1 Number of cells and genes per sample

diamonds and diamonds refer to before and after QC, respectively.

3.5.2 Average number of UMIs/cell and genes/cell per sample

The error bars represent the standard deviation of the number of UMIs and genes across cells per sample.


3.6 Key QC Metrics of Merged Samples

min 0% 25% 50% 75% 100% max
UMI per cell 750 750 4,608 8,679 14,068 261,100 261,100
Gene per cell 256 256 1,583 2,316 3,140 9,582 9,582
Mitochondrial (%) per cell 0.00 0.00 2.18 3.44 5.32 15.00 15.00

3.7 Visualization of Merged scRNA-Seq Object in 2D Space

Note: Labels may have been removed if they overlap excessively.

3.7.1 Signacx SPRING Projection

3.7.2 Seurat UMAP Projection

3.7.3 Seurat UMAP Projection (no-batch correction)


3.8 Visualizing Cell QC Metrics Using Dimensionality Reduction

Note: QC metrics based on kernel density estimation.

3.8.1 UMI per cell - SPRING Projection

3.8.2 Gene per cell - SPRING Projection

3.8.3 Mitochondrial (%) per cell - SPRING Projection

3.8.4 UMI per cell - UMAP Projection

3.8.5 Gene per cell - UMAP Projection

3.8.6 Mitochondrial (%) per cell - UMAP Projection


4 BridgeCluster

Note: Labels may have been removed if they overlap excessively.

4.1 Visualizing Cell Populations with Dimensionality Reduction

4.1.1 Signacx SPRING Projection

4.1.2 Seurat UMAP Projection


4.2 Cell Cluster Composition

Values at the top of each bar indicate the percentage of cells

4.2.1 Seurat

4.2.2 Signacx


4.3 Statistical Dispersion Analysis of Cell Composition in Clusters across sample

This measurement is a proxy to batch effect artifacts. Values adjacent to each point indicate the number of cells.

4.3.1 Seurat

4.3.2 Signacx


5 BridgeAnnotation

5.1 Visualizing Distinct Cell Type Populations with Dimensionality Reduction

Note: Labels may have been removed if they overlap excessively.

5.1.1 Signacx SPRING Projection

5.1.2 Signacx UMAP Projection


5.2 Cell Type Population Composition

Values at the top of each bar indicate the percentage of cells

5.2.1 Signacx


6 References

Publication: no referrence

Data Availability: no referrence


7 Session Information

This is the output of sessionInfo() on the computing system on which this document was compiled

## R version 4.3.2 (2023-10-31)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.6 LTS
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
## 
## Random number generation:
##  RNG:     L'Ecuyer-CMRG 
##  Normal:  Inversion 
##  Sample:  Rejection 
##  
## locale:
## [1] C
## 
## time zone: Etc/UTC
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats4    grid      stats     graphics  grDevices
## [6] utils     datasets  methods   base     
## 
## other attached packages:
##  [1] edgeR_4.0.2                 limma_3.58.1               
##  [3] slingshot_2.10.0            TrajectoryUtils_1.10.0     
##  [5] SingleCellExperiment_1.24.0 SummarizedExperiment_1.32.0
##  [7] Biobase_2.62.0              GenomicRanges_1.54.1       
##  [9] GenomeInfoDb_1.38.1         IRanges_2.36.0             
## [11] S4Vectors_0.40.2            BiocGenerics_0.48.1        
## [13] MatrixGenerics_1.14.0       matrixStats_1.1.0          
## [15] princurve_2.1.6             Nebulosa_1.12.0            
## [17] patchwork_1.1.3             data.table_1.14.10         
## [19] ComplexHeatmap_2.18.0       visNetwork_2.1.2           
## [21] plotly_4.10.3               data.tree_1.1.0            
## [23] DT_0.30                     readxl_1.4.3               
## [25] gtools_3.9.5                gplots_3.1.3               
## [27] gridtext_0.1.5              igraph_1.5.1               
## [29] sargent_1.0.1               SignacX_2.2.5              
## [31] harmony_1.2.0               Rcpp_1.0.11                
## [33] kableExtra_1.3.4            purrr_1.0.2                
## [35] reticulate_1.34.0           RColorBrewer_1.1-3         
## [37] cowplot_1.1.1               gridExtra_2.3              
## [39] pheatmap_1.0.12             ggrepel_0.9.4              
## [41] ggplot2_3.4.4               Seurat_5.0.1               
## [43] SeuratObject_5.0.1          sp_2.1-2                   
## [45] dplyr_1.1.4                 optparse_1.7.3             
## 
## loaded via a namespace (and not attached):
##   [1] spatstat.sparse_3.0-3   bitops_1.0-7           
##   [3] httr_1.4.7              webshot_0.5.5          
##   [5] doParallel_1.0.17       tools_4.3.2            
##   [7] sctransform_0.4.1       utf8_1.2.4             
##   [9] R6_2.5.1                mgcv_1.9-0             
##  [11] lazyeval_0.2.2          uwot_0.1.16            
##  [13] ggdist_3.3.1            GetoptLong_1.0.5       
##  [15] withr_2.5.2             progressr_0.14.0       
##  [17] cli_3.6.1               spatstat.explore_3.2-5 
##  [19] fastDummies_1.7.3       labeling_0.4.3         
##  [21] sass_0.4.8              mvtnorm_1.2-4          
##  [23] spatstat.data_3.0-3     proxy_0.4-27           
##  [25] ggridges_0.5.4          pbapply_1.7-2          
##  [27] commonmark_1.9.0        systemfonts_1.0.5      
##  [29] R.utils_2.12.3          svglite_2.1.2          
##  [31] parallelly_1.36.0       rstudioapi_0.15.0      
##  [33] generics_0.1.3          shape_1.4.6            
##  [35] crosstalk_1.2.1         ica_1.0-3              
##  [37] spatstat.random_3.2-2   distributional_0.3.2   
##  [39] Matrix_1.6-4            fansi_1.0.6            
##  [41] DescTools_0.99.52       abind_1.4-5            
##  [43] R.methodsS3_1.8.2       lifecycle_1.0.4        
##  [45] yaml_2.3.7              SparseArray_1.2.2      
##  [47] Rtsne_0.17              promises_1.2.1         
##  [49] crayon_1.5.2            miniUI_0.1.1.1         
##  [51] lattice_0.22-5          pillar_1.9.0           
##  [53] knitr_1.45              rjson_0.2.21           
##  [55] boot_1.3-28.1           gld_2.6.6              
##  [57] future.apply_1.11.0     codetools_0.2-19       
##  [59] leiden_0.4.3.1          glue_1.6.2             
##  [61] vctrs_0.6.5             png_0.1-8              
##  [63] spam_2.10-0             neuralnet_1.44.2       
##  [65] cellranger_1.1.0        gtable_0.3.4           
##  [67] cachem_1.0.8            ks_1.14.1              
##  [69] xfun_0.41               S4Arrays_1.2.0         
##  [71] mime_0.12               pracma_2.4.4           
##  [73] survival_3.5-7          pbmcapply_1.5.1        
##  [75] iterators_1.0.14        statmod_1.5.0          
##  [77] ellipsis_0.3.2          fitdistrplus_1.1-11    
##  [79] ROCR_1.0-11             nlme_3.1-164           
##  [81] RcppAnnoy_0.0.21        bslib_0.6.1            
##  [83] irlba_2.3.5.1           KernSmooth_2.23-22     
##  [85] colorspace_2.1-0        Exact_3.2              
##  [87] tidyselect_1.2.0        compiler_4.3.2         
##  [89] rvest_1.0.3             expm_0.999-8           
##  [91] xml2_1.3.6              DelayedArray_0.28.0    
##  [93] scales_1.3.0            caTools_1.18.2         
##  [95] lmtest_0.9-40           stringr_1.5.1          
##  [97] digest_0.6.33           goftest_1.2-3          
##  [99] spatstat.utils_3.0-4    rmarkdown_2.25         
## [101] RhpcBLASctl_0.23-42     XVector_0.42.0         
## [103] htmltools_0.5.7         pkgconfig_2.0.3        
## [105] highr_0.10              fastmap_1.1.1          
## [107] rlang_1.1.2             GlobalOptions_0.1.2    
## [109] htmlwidgets_1.6.4       shiny_1.8.0            
## [111] jquerylib_0.1.4         farver_2.1.1           
## [113] zoo_1.8-12              jsonlite_1.8.8         
## [115] mclust_6.0.1            R.oo_1.25.0            
## [117] RCurl_1.98-1.13         magrittr_2.0.3         
## [119] GenomeInfoDbData_1.2.11 dotCall64_1.1-1        
## [121] munsell_0.5.0           stringi_1.8.2          
## [123] rootSolve_1.8.2.4       zlibbioc_1.48.0        
## [125] MASS_7.3-60             plyr_1.8.9             
## [127] parallel_4.3.2          listenv_0.9.0          
## [129] lmom_3.0                deldir_2.0-2           
## [131] splines_4.3.2           tensor_1.5             
## [133] circlize_0.4.15         locfit_1.5-9.8         
## [135] spatstat.geom_3.2-7     markdown_1.12          
## [137] RcppHNSW_0.5.0          reshape2_1.4.4         
## [139] evaluate_0.23           foreach_1.5.2          
## [141] httpuv_1.6.13           RANN_2.6.1             
## [143] tidyr_1.3.0             getopt_1.20.4          
## [145] polyclip_1.10-6         future_1.33.0          
## [147] clue_0.3-65             scattermore_1.2        
## [149] xtable_1.8-4            e1071_1.7-14           
## [151] RSpectra_0.16-1         later_1.3.2            
## [153] viridisLite_0.4.2       class_7.3-22           
## [155] tibble_3.2.1            cluster_2.1.6          
## [157] globals_0.16.2