R/generics.R, R/preprocessing.R
PearsonResidualVar.RdFind the top features for a given assay based on analytic Pearson residual variance. This function computes the Pearson residual variance for each feature without constructing the entire dense matrix of Pearson residuals to reduce the memory required.
PearsonResidualVar(object, ...)
# Default S3 method
PearsonResidualVar(
object,
assay = NULL,
nfeatures = 20000,
min.counts = 100,
ncell.batch = 100,
theta = 10,
verbose = TRUE,
...
)
# S3 method for class 'Assay'
PearsonResidualVar(
object,
assay = NULL,
nfeatures = 20000,
theta = 10,
min.counts = 100,
weight.mean = 0,
ncell.batch = 100,
verbose = TRUE,
...
)
# S3 method for class 'StdAssay'
PearsonResidualVar(
object,
assay = NULL,
min.counts = 100,
weight.mean = 0,
theta = 10,
ncell.batch = 100,
verbose = TRUE,
...
)
# S3 method for class 'Seurat'
PearsonResidualVar(
object,
assay = NULL,
min.counts = 100,
weight.mean = 0,
theta = 10,
ncell.batch = 100,
verbose = TRUE,
...
)A Seurat object
Arguments passed to other methods
Name of assay to use
Number of top features to set as the variable features
Minimum number of counts for feature to be eligible for variable features
Number of cells to process in each batch. Higher number increases speed but uses more memory.
Theta value for analytic Pearson residual calculation
Display messages
Weighting to apply to the feature mean relative to the
Pearson residual variance for ranking features. weight.mean=0 will
rank features based on the Pearson residual variance only.
Returns a SeuratObject::Seurat() object
Lause, J., Berens, P. & Kobak, D. Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data. Genome Biol 22, 258 (2021). doi:10.1186/s13059-021-02451-7
PearsonResidualVar(object = atac_small[["peaks"]]["counts"])
#> Retaining 323 features with mean greater than zero
#> count mean ResidualVariance
#> chr1-713460-714823 81 0.81 2.1857905
#> chr1-752422-753038 16 0.16 1.8110236
#> chr1-762106-763359 47 0.47 1.7661403
#> chr1-779589-780271 9 0.09 2.2233234
#> chr1-804872-805761 24 0.24 2.3697917
#> chr1-839520-841123 28 0.28 2.5069483
#> chr1-841866-842572 4 0.04 1.9521912
#> chr1-856165-857031 4 0.04 1.9521912
#> chr1-858464-861548 27 0.27 2.8024812
#> chr1-875427-878705 24 0.24 2.9960921
#> chr1-894021-896898 92 0.92 2.8404204
#> chr1-901313-902847 26 0.26 2.0707752
#> chr1-911152-912038 8 0.08 1.7418068
#> chr1-919270-919976 12 0.12 1.8577075
#> chr1-925760-926165 7 0.07 1.7162496
#> chr1-928630-937949 150 1.50 3.5536232
#> chr1-939991-941002 11 0.11 2.1391961
#> chr1-944476-944998 5 0.05 1.7412935
#> chr1-948133-951142 79 0.79 4.0190753
#> chr1-954372-958413 103 1.03 3.6981206
#> chr1-967806-970136 46 0.46 3.2442588
#> chr1-973840-977754 72 0.72 3.2289484
#> chr1-994056-995654 62 0.62 2.6663022
#> chr1-998895-1000200 44 0.44 3.2358063
#> chr1-1002063-1006231 76 0.76 3.1089806
#> chr1-1014697-1015912 20 0.20 2.2913495
#> chr1-1034158-1035389 7 0.07 1.7747198
#> chr1-1051006-1053102 170 1.70 2.9358377
#> chr1-1057192-1058404 32 0.32 2.5968992
#> chr1-1071616-1073471 26 0.26 3.2600499
#> chr1-1079247-1080264 10 0.10 2.4514011
#> chr1-1092026-1094240 54 0.54 3.0611375
#> chr1-1108888-1109641 7 0.07 2.1241798
#> chr1-1135873-1137356 68 0.68 3.3289271
#> chr1-1140204-1144858 53 0.53 4.1016682
#> chr1-1147592-1153647 58 0.58 2.9065902
#> chr1-1154588-1155301 6 0.06 1.9284294
#> chr1-1166366-1168282 132 1.32 3.7599368
#> chr1-1185856-1186893 20 0.20 2.9411765
#> chr1-1207999-1210168 98 0.98 4.2386782
#> chr1-1226995-1227705 12 0.12 1.6930171
#> chr1-1240091-1245762 185 1.85 4.5561707
#> chr1-1259506-1261414 105 1.05 2.8191404
#> chr1-1283373-1285555 67 0.67 2.5753612
#> chr1-1288121-1291291 23 0.23 2.1582250
#> chr1-1293753-1295053 4 0.04 1.9521912
#> chr1-1306174-1308201 70 0.70 3.7303850
#> chr1-1309645-1311492 110 1.10 1.9901720
#> chr1-1333514-1336003 123 1.23 2.3000963
#> chr1-1337323-1337799 4 0.04 1.9521912
#> chr1-1341794-1343522 128 1.28 3.4682813
#> chr1-1361935-1362825 6 0.06 1.9284294
#> chr1-1369325-1371497 19 0.19 2.7691349
#> chr1-1397565-1398360 10 0.10 2.0792079
#> chr1-1406028-1408272 88 0.88 3.5726350
#> chr1-1440010-1441302 17 0.17 1.9729308
#> chr1-1446312-1448163 97 0.97 2.2781783
#> chr1-1475360-1476487 6 0.06 1.5970842
#> chr1-1509089-1511050 91 0.91 3.3406467
#> chr1-1532974-1533319 3 0.03 1.3418232
#> chr1-1534779-1536172 28 0.28 2.2290161
#> chr1-1542207-1543000 7 0.07 1.7747198
#> chr1-1549446-1552535 189 1.89 2.8648413
#> chr1-1553343-1553743 2 0.02 0.9780439
#> chr1-1562519-1567986 196 1.96 4.8388347
#> chr1-1589986-1591117 62 0.62 2.5144280
#> chr1-1597084-1597513 7 0.07 1.7162496
#> chr1-1608771-1610748 32 0.32 3.0889521
#> chr1-1617619-1618183 6 0.06 1.9284294
#> chr1-1623610-1625141 96 0.96 2.8433725
#> chr1-1655226-1656410 92 0.92 2.2630992
#> chr1-1660021-1660414 5 0.05 1.8044741
#> chr1-1677619-1678941 9 0.09 1.7828433
#> chr1-1690269-1690749 8 0.08 1.6337208
#> chr1-1695549-1696821 30 0.30 2.6346214
#> chr1-1706795-1707660 12 0.12 1.8577075
#> chr1-1708510-1715065 201 2.01 2.9749520
#> chr1-1727875-1728288 10 0.10 2.4514011
#> chr1-1729436-1729707 4 0.04 1.9521912
#> chr1-1772973-1773995 7 0.07 1.7747198
#> chr1-1780695-1781014 4 0.04 0.9561753
#> chr1-1788464-1789189 10 0.10 1.8811881
#> chr1-1789961-1790535 6 0.06 1.9284294
#> chr1-1797303-1797631 3 0.03 1.3418232
#> chr1-1800682-1801583 21 0.21 2.0796605
#> chr1-1804025-1804468 4 0.04 1.4541833
#> chr1-1812400-1813494 7 0.07 2.1241798
#> chr1-1814487-1815655 4 0.04 1.9521912
#> chr1-1817581-1818125 4 0.04 1.4541833
#> chr1-1819732-1824104 149 1.49 3.3701877
#> chr1-1837423-1839193 13 0.13 1.7700661
#> chr1-1839727-1841458 148 1.48 3.1148961
#> chr1-1849693-1853920 159 1.59 3.0181625
#> chr1-1875345-1875801 4 0.04 1.9521912
#> chr1-1891426-1891854 3 0.03 1.3418232
#> chr1-1927576-1928068 9 0.09 2.2233234
#> chr1-1975839-1976906 17 0.17 1.7415698
#> chr1-1980856-1982929 108 1.08 3.2445775
#> chr1-2023023-2023435 4 0.04 1.9521912
#> chr1-2043788-2044372 8 0.08 1.9898227
#> chr1-2046611-2047074 2 0.02 0.9780439
#> chr1-2058137-2059185 11 0.11 1.7795162
#> chr1-2063672-2065744 168 1.68 3.8200635
#> chr1-2068827-2069139 2 0.02 0.9780439
#> chr1-2071091-2071791 18 0.18 2.2244052
#> chr1-2074156-2074747 5 0.05 1.7412935
#> chr1-2077596-2078445 4 0.04 1.9521912
#> chr1-2079917-2080950 24 0.24 2.0442708
#> chr1-2082091-2083429 44 0.44 2.5827238
#> chr1-2105657-2106319 8 0.08 1.9047619
#> chr1-2120455-2122065 65 0.65 2.9866378
#> chr1-2125466-2127403 144 1.44 3.4878511
#> chr1-2130011-2131484 85 0.85 3.4345351
#> chr1-2135022-2137621 103 1.03 1.8564550
#> chr1-2143708-2144981 48 0.48 2.5238550
#> chr1-2155475-2156839 16 0.16 2.1873589
#> chr1-2157847-2188813 866 8.66 3.5757410
#> chr1-2189545-2192208 22 0.22 2.0974915
#> chr1-2206598-2208283 10 0.10 1.8811881
#> chr1-2221250-2223390 84 0.84 3.0908452
#> chr1-2227715-2234197 197 1.97 4.9056673
#> chr1-2236104-2237259 9 0.09 1.5702016
#> chr1-2241757-2247855 90 0.90 2.3955148
#> chr1-2312793-2314371 26 0.26 2.6602599
#> chr1-2322313-2323985 168 1.68 3.0463144
#> chr1-2343197-2348396 190 1.90 3.8296271
#> chr1-2398568-2399841 6 0.06 1.6783303
#> chr1-2425108-2425944 2 0.02 0.9780439
#> chr1-2426847-2429351 19 0.19 2.8394722
#> chr1-2430822-2432046 12 0.12 1.9822325
#> chr1-2454600-2456271 35 0.35 2.7812284
#> chr1-2456987-2458884 115 1.15 2.9622086
#> chr1-2460345-2462489 23 0.23 2.6323961
#> chr1-2471903-2481288 354 3.54 3.3904255
#> chr1-2486054-2489237 143 1.43 2.4503668
#> chr1-2489999-2490171 3 0.03 1.3418232
#> chr1-2507261-2510518 86 0.86 3.0198295
#> chr1-2513019-2513577 3 0.03 1.3418232
#> chr1-2515241-2519350 220 2.20 2.8241431
#> chr1-2573495-2575472 103 1.03 3.7929213
#> chr1-2585232-2586236 6 0.06 1.6783303
#> chr1-2703118-2703609 4 0.04 1.9521912
#> chr1-2756472-2757468 18 0.18 2.2244052
#> chr1-2843088-2844374 8 0.08 1.9047619
#> chr1-2949388-2950228 4 0.04 1.9521912
#> chr1-3232972-3233779 6 0.06 1.9284294
#> chr1-3369629-3371833 22 0.22 2.8091087
#> chr1-3407512-3408483 12 0.12 2.6954013
#> chr1-3446985-3448712 37 0.37 3.3214701
#> chr1-3481736-3482215 7 0.07 1.7747198
#> chr1-3513943-3514649 14 0.14 1.8343195
#> chr1-3527180-3529385 14 0.14 2.3482893
#> chr1-3535177-3536355 38 0.38 1.9663320
#> chr1-3537510-3538045 6 0.06 1.2657389
#> chr1-3540009-3542500 162 1.62 2.6146367
#> chr1-3546738-3547139 2 0.02 0.9780439
#> chr1-3565942-3569718 77 0.77 3.8520415
#> chr1-3585229-3585878 12 0.12 2.2766830
#> chr1-3593401-3595956 19 0.19 1.9312019
#> chr1-3612122-3612609 4 0.04 1.9521912
#> chr1-3640902-3641383 5 0.05 1.7412935
#> chr1-3662633-3664352 50 0.50 4.0999877
#> chr1-3688192-3690359 63 0.63 3.4250974
#> chr1-3692008-3692971 4 0.04 1.9521912
#> chr1-3703815-3704555 3 0.03 1.3418232
#> chr1-3710108-3710711 8 0.08 1.9047619
#> chr1-3712392-3713775 56 0.56 2.3106061
#> chr1-3759680-3759895 2 0.02 0.9780439
#> chr1-3773000-3774956 90 0.90 2.4770642
#> chr1-3799784-3800744 8 0.08 2.0719890
#> chr1-3806419-3808097 31 0.31 3.2463571
#> chr1-3815928-3820356 308 3.08 3.2177084
#> chr1-3827263-3827968 5 0.05 1.7412935
#> chr1-3838659-3839297 10 0.10 2.1668107
#> chr1-4066997-4068144 4 0.04 1.9521912
#> chr1-4712641-4713007 3 0.03 1.3418232
#> chr1-5448721-5449698 17 0.17 2.4356527
#> chr1-5541924-5542287 2 0.02 0.9780439
#> chr1-5726874-5727812 7 0.07 1.7162496
#> chr1-6051145-6055407 212 2.12 2.8182847
#> chr1-6061422-6063389 10 0.10 2.1668107
#> chr1-6065317-6066074 6 0.06 1.9284294
#> chr1-6072846-6073562 4 0.04 1.4541833
#> chr1-6074646-6075340 10 0.10 2.1668107
#> chr1-6085254-6089147 156 1.56 3.4627150
#> chr1-6094452-6094929 4 0.04 1.9521912
#> chr1-6112490-6113074 3 0.03 0.9670987
#> chr1-6115973-6117096 17 0.17 2.3174032
#> chr1-6118667-6119050 8 0.08 1.6567460
#> chr1-6158309-6158535 2 0.02 0.9780439
#> chr1-6159426-6161621 11 0.11 1.7795162
#> chr1-6187544-6188439 23 0.23 1.9427090
#> chr1-6208425-6209293 23 0.23 2.6323961
#> chr1-6258846-6260407 85 0.85 2.5403414
#> chr1-6264890-6266821 28 0.28 3.3451279
#> chr1-6268667-6270086 22 0.22 2.3854321
#> chr1-6295272-6296706 69 0.69 3.9028770
#> chr1-6304964-6307369 38 0.38 2.5079012
#> chr1-6319594-6322140 42 0.42 2.1104104
#> chr1-6403422-6403936 7 0.07 1.7747198
#> chr1-6407925-6409601 26 0.26 2.5955915
#> chr1-6418151-6420435 50 0.50 4.1416584
#> chr1-6425029-6425683 6 0.06 1.9284294
#> chr1-6452328-6454679 160 1.60 3.2170187
#> chr1-6461699-6462218 8 0.08 1.9047619
#> chr1-6464664-6465176 9 0.09 1.7828433
#> chr1-6474354-6474772 6 0.06 1.2657389
#> chr1-6483424-6485428 20 0.20 2.6835064
#> chr1-6497838-6498680 10 0.10 2.1668107
#> chr1-6500054-6501132 16 0.16 2.6794849
#> chr1-6507013-6510383 32 0.32 3.0813953
#> chr1-6514584-6515741 4 0.04 1.9521912
#> chr1-6519517-6521256 34 0.34 3.1983161
#> chr1-6523645-6526848 27 0.27 2.6582278
#> chr1-6535328-6536188 12 0.12 1.8577075
#> chr1-6545462-6547152 29 0.29 2.9478403
#> chr1-6549536-6551487 22 0.22 3.0343720
#> chr1-6557001-6558057 31 0.31 2.9715868
#> chr1-6613890-6615140 73 0.73 2.3964304
#> chr1-6639159-6642773 130 1.30 2.2532335
#> chr1-6651141-6652061 4 0.04 1.9521912
#> chr1-6659264-6664388 200 2.00 2.6036539
#> chr1-6672613-6675785 191 1.91 4.5460156
#> chr1-6684553-6686243 74 0.74 3.1863707
#> chr1-6706469-6707017 6 0.06 1.9284294
#> chr1-6761132-6762608 73 0.73 3.1070122
#> chr1-6779996-6780494 8 0.08 1.9047619
#> chr1-6787479-6787943 4 0.04 1.9521912
#> chr1-6801917-6804384 28 0.28 2.8543635
#> chr1-6843960-6846894 328 3.28 3.0159180
#> chr1-6949969-6950349 5 0.05 1.7412935
#> chr1-7022276-7023784 10 0.10 1.8811881
#> chr1-7727502-7728223 8 0.08 1.9047619
#> chr1-7729458-7730117 12 0.12 2.6954013
#> chr1-7740033-7741328 34 0.34 3.8240983
#> chr1-7763862-7766072 84 0.84 2.9151292
#> chr1-7788851-7789256 7 0.07 1.7747198
#> chr1-7812830-7814063 7 0.07 1.7747198
#> chr1-7830534-7832331 101 1.01 2.0412586
#> chr1-7841489-7844891 133 1.33 3.7662521
#> chr1-7846855-7847243 3 0.03 1.3418232
#> chr1-7962633-7963232 13 0.13 2.5439683
#> chr1-7975875-7976274 4 0.04 1.9521912
#> chr1-7989680-7991862 28 0.28 3.5206284
#> chr1-8000672-8003534 36 0.36 1.7975118
#> chr1-8008972-8009703 16 0.16 2.6794849
#> chr1-8013637-8014963 86 0.86 2.8699302
#> chr1-8020317-8022548 176 1.76 3.0218192
#> chr1-8035301-8035725 10 0.10 1.8811881
#> chr1-8042128-8042915 9 0.09 1.7828433
#> chr1-8075007-8075497 6 0.06 1.9284294
#> chr1-8085460-8087248 81 0.81 3.2821690
#> chr1-8156770-8157834 6 0.06 1.9284294
#> chr1-8164523-8165144 9 0.09 1.7828433
#> chr1-8166762-8167329 4 0.04 1.9521912
#> chr1-8186838-8187845 25 0.25 2.1365854
#> chr1-8212306-8213910 54 0.54 4.9938102
#> chr1-8227330-8227690 9 0.09 1.4724227
#> chr1-8229422-8230556 9 0.09 1.9793924
#> chr1-8242128-8243255 34 0.34 3.1983161
#> chr1-8277105-8277928 8 0.08 1.9047619
#> chr1-8278622-8279253 10 0.10 2.1668107
#> chr1-8284654-8285560 22 0.22 3.0343720
#> chr1-8374335-8374807 5 0.05 1.8044741
#> chr1-8377792-8378947 21 0.21 2.2662189
#> chr1-8408802-8409630 14 0.14 1.6934348
#> chr1-8442858-8443649 6 0.06 1.9284294
#> chr1-8448058-8448562 8 0.08 1.9047619
#> chr1-8455220-8456159 14 0.14 1.8343195
#> chr1-8456996-8458096 6 0.06 1.9284294
#> chr1-8467741-8468104 6 0.06 1.9284294
#> chr1-8469105-8469816 8 0.08 2.0719890
#> chr1-8482480-8485295 83 0.83 3.9650459
#> chr1-8487258-8488478 28 0.28 2.2290161
#> chr1-8498906-8499422 4 0.04 1.9521912
#> chr1-8523212-8523742 8 0.08 1.9898227
#> chr1-8555950-8557971 15 0.15 2.5451560
#> chr1-8570017-8570771 12 0.12 2.6954013
#> chr1-8580547-8580902 3 0.03 1.3418232
#> chr1-8584964-8586531 57 0.57 1.8010257
#> chr1-8621060-8621547 3 0.03 1.3418232
#> chr1-8685625-8685837 5 0.05 1.2225503
#> chr1-8689375-8690307 9 0.09 2.4198725
#> chr1-8723942-8724565 7 0.07 1.7747198
#> chr1-8760958-8762003 26 0.26 2.8954866
#> chr1-8762907-8763964 32 0.32 1.9307171
#> chr1-8772445-8773223 6 0.06 1.2657389
#> chr1-8786544-8786946 3 0.03 1.3418232
#> chr1-8876634-8878709 88 0.88 2.8049799
#> chr1-8918082-8920107 13 0.13 2.2402247
#> chr1-8931013-8932013 6 0.06 1.9284294
#> chr1-8933459-8934461 20 0.20 1.7647059
#> chr1-8935313-8940649 224 2.24 3.8218367
#> chr1-8951785-8952241 3 0.03 0.9670987
#> chr1-8959709-8960452 10 0.10 2.1668107
#> chr1-8978053-8978591 7 0.07 1.7747198
#> chr1-8986755-8987690 4 0.04 1.9521912
#> chr1-9006466-9007566 4 0.04 1.9521912
#> chr1-9030034-9031614 14 0.14 2.1028899
#> chr1-9046821-9047245 2 0.02 0.9780439
#> chr1-9047790-9048521 15 0.15 1.7569787
#> chr1-9064752-9065614 11 0.11 1.7795162
#> chr1-9070978-9072039 8 0.08 1.7418068
#> chr1-9129476-9130126 9 0.09 1.7828433
#> chr1-9134957-9135502 8 0.08 1.9047619
#> chr1-9143106-9143741 4 0.04 1.9521912
#> chr1-9153374-9153983 4 0.04 1.9521912
#> chr1-9161610-9161990 4 0.04 1.9521912
#> chr1-9170725-9171256 8 0.08 1.9047619
#> chr1-9181580-9182573 6 0.06 1.9284294
#> chr1-9188154-9190941 116 1.16 2.8403093
#> chr1-9191514-9192075 4 0.04 1.9521912
#> chr1-9202229-9203756 14 0.14 2.3482893
#> chr1-9222989-9224547 20 0.20 2.5490196
#> chr1-9239865-9240117 3 0.03 1.3418232
#> chr1-9241288-9242647 14 0.14 2.8622471
#> chr1-9256287-9256980 7 0.07 1.7747198
#> chr1-9293115-9295644 123 1.23 3.5453091
#> chr1-9299648-9300348 12 0.12 2.0223979
#> chr1-9327071-9327557 3 0.03 1.3418232
#> chr1-9335457-9336176 15 0.15 1.7569787
#> chr1-9349019-9350779 26 0.26 2.8954866
#> chr1-9352328-9354391 44 0.44 3.2793452
PearsonResidualVar(object = atac_small[["peaks"]])
#> Retaining 323 features with mean greater than zero
#> Warning: Requested more features than are available. Returning 43 variable features
#> ChromatinAssay data with 323 features for 100 cells
#> Variable features: 43
#> Genome: hg19
#> Annotation present: TRUE
#> Motifs present: TRUE
#> Fragment files: 0
PearsonResidualVar(object = atac_small[["peaks"]])
#> Retaining 323 features with mean greater than zero
#> Warning: Requested more features than are available. Returning 43 variable features
#> ChromatinAssay data with 323 features for 100 cells
#> Variable features: 43
#> Genome: hg19
#> Annotation present: TRUE
#> Motifs present: TRUE
#> Fragment files: 0
PearsonResidualVar(atac_small)
#> Retaining 323 features with mean greater than zero
#> Warning: Requested more features than are available. Returning 43 variable features
#> An object of class Seurat
#> 1323 features across 100 samples within 3 assays
#> Active assay: peaks (323 features, 43 variable features)
#> 2 layers present: counts, data
#> 2 other assays present: bins, RNA
#> 2 dimensional reductions calculated: lsi, umap