13 State Priority and Perturbation Sensitivity
After clustering, annotation, and trajectory analysis, one question still remains: which states actually respond to the perturbation? Not every cluster changes meaningfully between conditions, and some rare populations may drive the phenotype while being numerically small. This mainline is about ranking states by their responsiveness and detecting rare populations that deserve follow-up before everything else.
sclet now provides the three entry points that were promised in the mainline roadmap: RunPerturbationPriority(), RunRareCellDetection(), and RunStatePriorityWorkflow().
The core engine for perturbation priority is the Augur framework. Augur trains a machine-learning model for each cell type to predict experimental condition (e.g., treatment vs control) from molecular measurements. The cross-validated AUC of each cell-type-specific classifier becomes the priority score: a higher AUC means cells of that type are more distinguishable between conditions, and therefore more responsive.
13.1 Perturbation Priority Workflow
13.1.1 One-Step Dispatch
The simplest entry point is RunStatePriorityWorkflow(). It delegates to Augur behind the scenes and records the workflow as a structured analysis mainline record.
library(sclet)
sce <- pbmc
# The object must have condition labels and cluster labels in colData.
sce$condition <- ifelse(seq_len(ncol(sce)) %% 2 == 0, "treated", "control")
sce <- RunStatePriorityWorkflow(
sce,
condition_col = "condition",
group_col = "colLabels",
run_perturbation_priority = TRUE
)13.1.2 Direct Augur Call
If you prefer to work directly with the Augur backend without the workflow shell, use RunPerturbationPriority().
The real Augur run is not executed during book rendering because it requires the Augur package and involves a non-trivial cross-validation loop. The code below shows the intended usage pattern.
library(sclet)
sce <- pbmc
sce$condition <- ifelse(seq_len(ncol(sce)) %% 2 == 0, "treated", "control")
sce <- RunPerturbationPriority(
sce,
condition_col = "condition",
group_col = "colLabels",
name = "my_augur_run"
)
# Inspect the AUC ranking
priority <- get_perturbation_priority(sce)
print(priority$AUC)13.1.3 Inspecting Results
After the analysis, sclet stores the Augur output through two accessor layers. get_perturbation_priority() returns the complete priority record; has_perturbation_priority() checks whether the result is available.
## [1] FALSE# Retrieve the AUC table
auc_table <- get_perturbation_priority(sce, element = "AUC")
head(auc_table)## NULL13.2 Rare Cell Detection
RunRareCellDetection(method = "density") identifies rare and major cell populations using a mutual-connectivity metric computed directly on the kNN graph. No external packages beyond BiocNeighbors (already a sclet dependency) are needed. The algorithm works in three steps on any reduction (typically PCA):
- Build kNN graph and compute each cell’s mutual connectivity (Q = fraction of neighbors that mutually connect back).
- Identify high-Q seeds — cells above
q_thresholdare local density maxima. - Label propagation — unlabeled cells adopt the label of their most frequent labeled neighbor over 5 iterations. Clusters ≤
rare_thresholdcells are flagged as rare.
library(sclet)
sce <- pbmc
# Ensure PCA is in the object (already there from core workflow)
sce <- RunRareCellDetection(
sce,
method = "density",
reduction = "PCA",
dims = 1:10,
k = 20,
q_threshold = 0.25,
rare_threshold = 10,
name = "density_demo"
)## Found more than one class "package_version" in cache; using the first, from namespace 'SeuratObject'## Also defined by 'alabaster.base'## Found more than one class "package_version" in cache; using the first, from namespace 'SeuratObject'## Also defined by 'alabaster.base'## ℹ Building kNN graph (k=20) on 10 dims## ℹ Found 2374 high-density seeds (Q >= 0.25)##
## 1 10 100 1000 1001 1002 1003 1004 1005 1006 1007 1008
## 1 6 1 1 1 1 1 1 1 1 1 1
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## 1 2 1 1 1 1 1 1 1 1 1 1
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## 3 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 5 4
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 2 1 1 1 1
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## 1 1 1 1 1 1 5 1 1 1 1 1
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## 1 1 1 1 1 2 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 2 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 3 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 2 1 1 1 1 1 1 1
## 1906 1907 1908 1909 191 1910 1911 1912 1913 1914 1915 1916
## 1 1 1 1 1 1 1 1 1 1 1 1
## 1917 1918 1919 192 1920 1921 1922 1923 1924 1925 1926 1927
## 1 1 1 1 1 1 1 1 1 1 1 1
## 1928 1929 193 1930 1931 1932 1933 1934 1935 1936 1937 1938
## 1 1 2 1 1 1 1 1 1 1 1 1
## 1939 194 1940 1941 1942 1943 1944 1945 1946 1947 1948 1949
## 1 1 1 1 1 1 1 1 1 1 1 1
## 195 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 196
## 4 1 1 1 1 1 1 1 1 1 1 1
## 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 197 1970
## 1 1 1 1 1 1 1 1 1 1 1 1
## 1971 1972 1973 1974 1975 1976 1977 1978 1979 198 1980 1981
## 1 1 1 1 1 1 1 1 1 1 1 1
## 1982 1983 1984 1985 1986 1987 1988 1989 199 1990 1991 1992
## 1 1 1 1 1 1 1 1 1 1 1 1
## 1993 1994 1995 1996 1997 1998 1999 2 20 200 2000 2001
## 1 1 1 1 1 1 1 1 5 1 1 1
## 2002 2003 2004 2005 2006 2007 2008 2009 201 2010 2011 2012
## 1 1 1 1 1 1 1 1 1 1 1 1
## 2013 2014 2015 2016 2017 2018 2019 202 2020 2021 2022 2023
## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 3 1 3 1 2 1 3 1
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## 1 1 1 1 1 3 1 1 1 2 1 1
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## 1 1 1 1 4 1 1 1 3 1 1 1
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## 4 1 1 3 1 1 1 1 1 1 1 1
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## 1 1 2 1 1 1 1 1 1 1 2 1
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## 1 1 1 1 3 1 1 1 1 1 1 1
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## 1 3 1 1 1 1 1 1 1 1 1 1
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## 1 1 2 1 1 1 1 1 1 1 1 1
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## 1 2 1 1 1 1 1 1 1 1 1 1
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## 5 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 2 1
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## 1 1 1 1 1 1 1 1 1 1 4 1
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## 1 1 1 1 1 1 1 1 1 2 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 2 1 1 1 1
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## 1 1 1 1 1 1 2 1 1 1 1 1
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## 1 1 1 1 1 5 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 3 1 1 1 1 1 1 1 1 1
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## 1 4 2 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 3 1 1 1 1 1 1 1 1 1 1 3
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 1 1 1 1 1
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## 1 1 1 1 1 1 1 2 1 1 1 1
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## 1 1 1 1 1 1 4 1 1 1 1 1
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## 1 1 1 1 1 5 1 1 1 1 1 1
## 796 797 798 799 8 80 800 801 802 803 804 805
## 1 1 1 1 6 1 1 1 1 1 1 1
## 806 807 808 809 81 810 811 812 813 814 815 816
## 1 1 1 1 1 1 1 1 1 1 1 1
## 817 818 819 82 820 821 822 823 824 825 826 827
## 1 1 1 2 1 1 1 1 1 1 1 1
## 828 829 83 830 831 832 833 834 835 836 837 838
## 1 1 4 1 1 1 1 1 1 1 1 1
## 839 84 840 841 842 843 844 845 846 847 848 849
## 1 4 1 1 1 1 1 1 1 1 1 1
## 85 850 851 852 853 854 855 856 857 858 859 86
## 1 1 1 1 1 1 1 1 1 1 1 1
## 860 861 862 863 864 865 866 867 868 869 87 870
## 1 1 1 1 1 1 1 1 1 1 4 1
## 871 872 873 874 875 876 877 878 879 88 880 881
## 1 1 1 1 1 1 1 1 1 1 1 1
## 882 883 884 885 886 887 888 889 89 890 891 892
## 1 1 1 1 1 1 1 1 3 1 1 1
## 893 894 895 896 897 898 899 9 90 900 901 902
## 1 1 1 1 1 1 1 2 3 1 1 1
## 903 904 905 906 907 908 909 91 910 911 912 913
## 1 1 1 1 1 1 1 4 1 1 1 1
## 914 915 916 917 918 919 92 920 921 922 923 924
## 1 1 1 1 1 1 7 1 1 1 1 1
## 925 926 927 928 929 93 930 931 932 933 934 935
## 1 1 1 1 1 1 1 1 1 1 1 1
## 936 937 938 939 94 940 941 942 943 944 945 946
## 1 1 1 1 1 1 1 1 1 1 1 1
## 947 948 949 95 950 951 952 953 954 955 956 957
## 1 1 1 1 1 1 1 1 1 1 1 1
## 958 959 96 960 961 962 963 964 965 966 967 968
## 1 1 2 1 1 1 1 1 1 1 1 1
## 969 97 970 971 972 973 974 975 976 977 978 979
## 1 1 1 1 1 1 1 1 1 1 1 1
## 98 980 981 982 983 984 985 986 987 988 989 99
## 3 1 1 1 1 1 1 1 1 1 1 7
## 990 991 992 993 994 995 996 997 998 999
## 1 1 1 1 1 1 1 1 1 1## [1] "1" "100" "1000" "1001" "1002" "1003" "1004"
## [8] "1005" "1006" "1007" "1008" "1009" "1010" "1011"
## [15] "1012" "1013" "1014" "1015" "1016" "1017" "1018"
## [22] "1019" "1020" "1021" "1022" "1023" "1024" "1025"
## [29] "1026" "1027" "1028" "1029" "103" "1030" "1031"
## [36] "1032" "1033" "1034" "1035" "1036" "1037" "1038"
## [43] "1039" "104" "1040" "1041" "1042" "1043" "1044"
## [50] "1045" "1046" "1047" "1048" "1049" "105" "1050"
## [57] "1051" "1052" "1053" "1054" "1055" "1056" "1057"
## [64] "1058" "1059" "106" "1060" "1061" "1062" "1063"
## [71] "1064" "1065" "1066" "1067" "1068" "1069" "1070"
## [78] "1071" "1072" "1073" "1074" "1075" "1076" "1077"
## [85] "1078" "1079" "108" "1080" "1081" "1082" "1083"
## [92] "1084" "1085" "1086" "1087" "1088" "1089" "109"
## [99] "1090" "1091" "1092" "1093" "1094" "1095" "1096"
## [106] "1097" "1098" "1099" "11" "1100" "1101" "1102"
## [113] "1103" "1104" "1105" "1106" "1107" "1108" "1109"
## [120] "111" "1110" "1111" "1112" "1113" "1114" "1115"
## [127] "1116" "1117" "1118" "1119" "112" "1120" "1121"
## [134] "1122" "1123" "1124" "1125" "1126" "1127" "1128"
## [141] "1129" "1130" "1131" "1132" "1133" "1134" "1135"
## [148] "1136" "1137" "1138" "1139" "1140" "1141" "1142"
## [155] "1143" "1144" "1145" "1146" "1147" "1148" "1149"
## [162] "1150" "1151" "1152" "1153" "1154" "1155" "1156"
## [169] "1157" "1158" "1159" "116" "1160" "1161" "1162"
## [176] "1163" "1164" "1165" "1166" "1167" "1168" "1169"
## [183] "117" "1170" "1171" "1172" "1173" "1174" "1175"
## [190] "1176" "1177" "1178" "1179" "118" "1180" "1181"
## [197] "1182" "1183" "1184" "1185" "1186" "1187" "1188"
## [204] "1189" "119" "1190" "1191" "1192" "1193" "1194"
## [211] "1195" "1196" "1197" "1198" "1199" "1200" "1201"
## [218] "1202" "1203" "1204" "1205" "1206" "1207" "1208"
## [225] "1209" "1210" "1211" "1212" "1213" "1214" "1215"
## [232] "1216" "1217" "1218" "1219" "122" "1220" "1221"
## [239] "1222" "1223" "1224" "1225" "1226" "1227" "1228"
## [246] "1229" "123" "1230" "1231" "1232" "1233" "1234"
## [253] "1235" "1236" "1237" "1238" "1239" "124" "1240"
## [260] "1241" "1242" "1243" "1244" "1245" "1246" "1247"
## [267] "1248" "1249" "125" "1250" "1251" "1252" "1253"
## [274] "1254" "1255" "1256" "1257" "1258" "1259" "1260"
## [281] "1261" "1262" "1263" "1264" "1265" "1266" "1267"
## [288] "1268" "1269" "127" "1270" "1271" "1272" "1273"
## [295] "1274" "1275" "1276" "1277" "1278" "1279" "128"
## [302] "1280" "1281" "1282" "1283" "1284" "1285" "1286"
## [309] "1287" "1288" "1289" "1290" "1291" "1292" "1293"
## [316] "1294" "1295" "1296" "1297" "1298" "1299" "1300"
## [323] "1301" "1302" "1303" "1304" "1305" "1306" "1307"
## [330] "1308" "1309" "131" "1310" "1311" "1312" "1313"
## [337] "1314" "1315" "1316" "1317" "1318" "1319" "1320"
## [344] "1321" "1322" "1323" "1324" "1325" "1326" "1327"
## [351] "1328" "1329" "133" "1330" "1331" "1332" "1333"
## [358] "1334" "1335" "1336" "1337" "1338" "1339" "134"
## [365] "1340" "1341" "1342" "1343" "1344" "1345" "1346"
## [372] "1347" "1348" "1349" "135" "1350" "1351" "1352"
## [379] "1353" "1354" "1355" "1356" "1357" "1358" "1359"
## [386] "136" "1360" "1361" "1362" "1363" "1364" "1365"
## [393] "1366" "1367" "1368" "1369" "137" "1370" "1371"
## [400] "1372" "1373" "1374" "1375" "1376" "1377" "1378"
## [407] "1379" "1380" "1381" "1382" "1383" "1384" "1385"
## [414] "1386" "1387" "1388" "1389" "139" "1390" "1391"
## [421] "1392" "1393" "1394" "1395" "1396" "1397" "1398"
## [428] "1399" "1400" "1401" "1402" "1403" "1404" "1405"
## [435] "1406" "1407" "1408" "1409" "1410" "1411" "1412"
## [442] "1413" "1414" "1415" "1416" "1417" "1418" "1419"
## [449] "1420" "1421" "1422" "1423" "1424" "1425" "1426"
## [456] "1427" "1428" "1429" "143" "1430" "1431" "1432"
## [463] "1433" "1434" "1435" "1436" "1437" "1438" "1439"
## [470] "1440" "1441" "1442" "1443" "1444" "1445" "1446"
## [477] "1447" "1448" "1449" "145" "1450" "1451" "1452"
## [484] "1453" "1454" "1455" "1456" "1457" "1458" "1459"
## [491] "146" "1460" "1461" "1462" "1463" "1464" "1465"
## [498] "1466" "1467" "1468" "1469" "147" "1470" "1471"
## [505] "1472" "1473" "1474" "1475" "1476" "1477" "1478"
## [512] "1479" "148" "1480" "1481" "1482" "1483" "1484"
## [519] "1485" "1486" "1487" "1488" "1489" "149" "1490"
## [526] "1491" "1492" "1493" "1494" "1495" "1496" "1497"
## [533] "1498" "1499" "1500" "1501" "1502" "1503" "1504"
## [540] "1505" "1506" "1507" "1508" "1509" "151" "1510"
## [547] "1511" "1512" "1513" "1514" "1515" "1516" "1517"
## [554] "1518" "1519" "152" "1520" "1521" "1522" "1523"
## [561] "1524" "1525" "1526" "1527" "1528" "1529" "1530"
## [568] "1531" "1532" "1533" "1534" "1535" "1536" "1537"
## [575] "1538" "1539" "154" "1540" "1541" "1542" "1543"
## [582] "1544" "1545" "1546" "1547" "1548" "1549" "155"
## [589] "1550" "1551" "1552" "1553" "1554" "1555" "1556"
## [596] "1557" "1558" "1559" "1560" "1561" "1562" "1563"
## [603] "1564" "1565" "1566" "1567" "1568" "1569" "1570"
## [610] "1571" "1572" "1573" "1574" "1575" "1576" "1577"
## [617] "1578" "1579" "158" "1580" "1581" "1582" "1583"
## [624] "1584" "1585" "1586" "1587" "1588" "1589" "159"
## [631] "1590" "1591" "1592" "1593" "1594" "1595" "1596"
## [638] "1597" "1598" "1599" "16" "160" "1600" "1601"
## [645] "1602" "1603" "1604" "1605" "1606" "1607" "1608"
## [652] "1609" "161" "1610" "1611" "1612" "1613" "1614"
## [659] "1615" "1616" "1617" "1618" "1619" "162" "1620"
## [666] "1621" "1622" "1623" "1624" "1625" "1626" "1627"
## [673] "1628" "1629" "163" "1630" "1631" "1632" "1633"
## [680] "1634" "1635" "1636" "1637" "1638" "1639" "164"
## [687] "1640" "1641" "1642" "1643" "1644" "1645" "1646"
## [694] "1647" "1648" "1649" "165" "1650" "1651" "1652"
## [701] "1653" "1654" "1655" "1656" "1657" "1658" "1659"
## [708] "166" "1660" "1661" "1662" "1663" "1664" "1665"
## [715] "1666" "1667" "1668" "1669" "167" "1670" "1671"
## [722] "1672" "1673" "1674" "1675" "1676" "1677" "1678"
## [729] "1679" "168" "1680" "1681" "1682" "1683" "1684"
## [736] "1685" "1686" "1687" "1688" "1689" "169" "1690"
## [743] "1691" "1692" "1693" "1694" "1695" "1696" "1697"
## [750] "1698" "1699" "1700" "1701" "1702" "1703" "1704"
## [757] "1705" "1706" "1707" "1708" "1709" "171" "1710"
## [764] "1711" "1712" "1713" "1714" "1715" "1716" "1717"
## [771] "1718" "1719" "172" "1720" "1721" "1722" "1723"
## [778] "1724" "1725" "1726" "1727" "1728" "1729" "173"
## [785] "1730" "1731" "1732" "1733" "1734" "1735" "1736"
## [792] "1737" "1738" "1739" "1740" "1741" "1742" "1743"
## [799] "1744" "1745" "1746" "1747" "1748" "1749" "1750"
## [806] "1751" "1752" "1753" "1754" "1755" "1756" "1757"
## [813] "1758" "1759" "1760" "1761" "1762" "1763" "1764"
## [820] "1765" "1766" "1767" "1768" "1769" "177" "1770"
## [827] "1771" "1772" "1773" "1774" "1775" "1776" "1777"
## [834] "1778" "1779" "1780" "1781" "1782" "1783" "1784"
## [841] "1785" "1786" "1787" "1788" "1789" "179" "1790"
## [848] "1791" "1792" "1793" "1794" "1795" "1796" "1797"
## [855] "1798" "1799" "180" "1800" "1801" "1802" "1803"
## [862] "1804" "1805" "1806" "1807" "1808" "1809" "181"
## [869] "1810" "1811" "1812" "1813" "1814" "1815" "1816"
## [876] "1817" "1818" "1819" "182" "1820" "1821" "1822"
## [883] "1823" "1824" "1825" "1826" "1827" "1828" "1829"
## [890] "183" "1830" "1831" "1832" "1833" "1834" "1835"
## [897] "1836" "1837" "1838" "1839" "184" "1840" "1841"
## [904] "1842" "1843" "1844" "1845" "1846" "1847" "1848"
## [911] "1849" "185" "1850" "1851" "1852" "1853" "1854"
## [918] "1855" "1856" "1857" "1858" "1859" "186" "1860"
## [925] "1861" "1862" "1863" "1864" "1865" "1866" "1867"
## [932] "1868" "1869" "187" "1870" "1871" "1872" "1873"
## [939] "1874" "1875" "1876" "1877" "1878" "1879" "188"
## [946] "1880" "1881" "1882" "1883" "1884" "1885" "1886"
## [953] "1887" "1888" "1889" "189" "1890" "1891" "1892"
## [960] "1893" "1894" "1895" "1896" "1897" "1898" "1899"
## [967] "190" "1900" "1901" "1902" "1903" "1904" "1905"
## [974] "1906" "1907" "1908" "1909" "191" "1910" "1911"
## [981] "1912" "1913" "1914" "1915" "1916" "1917" "1918"
## [988] "1919" "192" "1920" "1921" "1922" "1923" "1924"
## [995] "1925" "1926" "1927" "1928" "1929" "1930" "1931"
## [1002] "1932" "1933" "1934" "1935" "1936" "1937" "1938"
## [1009] "1939" "194" "1940" "1941" "1942" "1943" "1944"
## [1016] "1945" "1946" "1947" "1948" "1949" "1950" "1951"
## [1023] "1952" "1953" "1954" "1955" "1956" "1957" "1958"
## [1030] "1959" "196" "1960" "1961" "1962" "1963" "1964"
## [1037] "1965" "1966" "1967" "1968" "1969" "197" "1970"
## [1044] "1971" "1972" "1973" "1974" "1975" "1976" "1977"
## [1051] "1978" "1979" "198" "1980" "1981" "1982" "1983"
## [1058] "1984" "1985" "1986" "1987" "1988" "1989" "199"
## [1065] "1990" "1991" "1992" "1993" "1994" "1995" "1996"
## [1072] "1997" "1998" "1999" "2" "200" "2000" "2001"
## [1079] "2002" "2003" "2004" "2005" "2006" "2007" "2008"
## [1086] "2009" "201" "2010" "2011" "2012" "2013" "2014"
## [1093] "2015" "2016" "2017" "2018" "2019" "202" "2020"
## [1100] "2021" "2022" "2023" "2024" "2025" "2026" "2027"
## [1107] "2028" "2029" "203" "2030" "2031" "2032" "2033"
## [1114] "2034" "2035" "2036" "2037" "2038" "2039" "204"
## [1121] "2040" "2041" "2042" "2043" "2044" "2045" "2046"
## [1128] "2047" "2048" "2049" "205" "2050" "2051" "2052"
## [1135] "2053" "2054" "2055" "2056" "2057" "2058" "2059"
## [1142] "206" "2060" "2061" "2062" "2063" "2064" "2065"
## [1149] "2066" "2067" "2068" "2069" "2070" "2071" "2072"
## [1156] "2073" "2074" "2075" "2076" "2077" "2078" "2079"
## [1163] "2080" "2081" "2082" "2083" "2084" "2085" "2086"
## [1170] "2087" "2088" "2089" "209" "2090" "2091" "2092"
## [1177] "2093" "2094" "2095" "2096" "2097" "2098" "2099"
## [1184] "2100" "2101" "2102" "2103" "2104" "2105" "2106"
## [1191] "2107" "2108" "2109" "211" "2110" "2111" "2112"
## [1198] "2113" "2114" "2115" "2116" "2117" "2118" "2119"
## [1205] "212" "2120" "2121" "2122" "2123" "2124" "2125"
## [1212] "2126" "2127" "2128" "2129" "213" "2130" "2131"
## [1219] "2132" "2133" "2134" "2135" "2136" "2137" "2138"
## [1226] "2139" "214" "2140" "2141" "2142" "2143" "2144"
## [1233] "2145" "2146" "2147" "2148" "2149" "215" "2150"
## [1240] "2151" "2152" "2153" "2154" "2155" "2156" "2157"
## [1247] "2158" "2159" "216" "2160" "2161" "2162" "2163"
## [1254] "2164" "2165" "2166" "2167" "2168" "2169" "217"
## [1261] "2170" "2171" "2172" "2173" "2174" "2175" "2176"
## [1268] "2177" "2178" "2179" "218" "2180" "2181" "2182"
## [1275] "2183" "2184" "2185" "2186" "2187" "2188" "2189"
## [1282] "219" "2190" "2191" "2192" "2193" "2194" "2195"
## [1289] "2196" "2197" "2198" "2199" "220" "2200" "2201"
## [1296] "2202" "2203" "2204" "2205" "2206" "2207" "2208"
## [1303] "2209" "2210" "2211" "2212" "2213" "2214" "2215"
## [1310] "2216" "2217" "2218" "2219" "2220" "2221" "2222"
## [1317] "2223" "2224" "2225" "2226" "2227" "2228" "2229"
## [1324] "223" "2230" "2231" "2232" "2233" "2234" "2235"
## [1331] "2236" "2237" "2238" "2239" "224" "2240" "2241"
## [1338] "2242" "2243" "2244" "2245" "2246" "2247" "2248"
## [1345] "2249" "225" "2250" "2251" "2252" "2253" "2254"
## [1352] "2255" "2256" "2257" "2258" "2259" "226" "2260"
## [1359] "2261" "2262" "2263" "2264" "2265" "2266" "2267"
## [1366] "2268" "2269" "227" "2270" "2271" "2272" "2273"
## [1373] "2274" "2275" "2276" "2277" "2278" "2279" "228"
## [1380] "2280" "2281" "2282" "2283" "2284" "2285" "2286"
## [1387] "2287" "2288" "2289" "229" "2290" "2291" "2292"
## [1394] "2293" "2294" "2295" "2296" "2297" "2298" "2299"
## [1401] "2300" "2301" "2302" "2303" "2304" "2305" "2306"
## [1408] "2307" "2308" "2309" "231" "2310" "2311" "2312"
## [1415] "2313" "2314" "2315" "2316" "2317" "2318" "2319"
## [1422] "232" "2320" "2321" "2322" "2323" "2324" "2325"
## [1429] "2326" "2327" "2328" "2329" "233" "2330" "2331"
## [1436] "2332" "2333" "2334" "2335" "2336" "2337" "2338"
## [1443] "2339" "234" "2340" "2341" "2342" "2343" "2344"
## [1450] "2345" "2346" "2347" "2348" "2349" "235" "2350"
## [1457] "2351" "2352" "2353" "2354" "2355" "2356" "2357"
## [1464] "2358" "2359" "236" "2360" "2361" "2362" "2363"
## [1471] "2364" "2365" "2366" "2367" "2368" "2369" "237"
## [1478] "2370" "2371" "2372" "2373" "2374" "238" "239"
## [1485] "240" "241" "242" "243" "244" "245" "246"
## [1492] "247" "249" "250" "252" "254" "255" "256"
## [1499] "257" "258" "259" "260" "261" "262" "264"
## [1506] "265" "266" "267" "268" "269" "270" "271"
## [1513] "272" "274" "275" "276" "278" "279" "280"
## [1520] "281" "282" "283" "284" "285" "286" "287"
## [1527] "288" "289" "290" "291" "292" "293" "294"
## [1534] "295" "296" "298" "299" "3" "30" "300"
## [1541] "302" "303" "304" "305" "306" "307" "308"
## [1548] "309" "310" "311" "312" "313" "314" "315"
## [1555] "316" "317" "318" "319" "320" "321" "322"
## [1562] "323" "324" "325" "326" "327" "328" "329"
## [1569] "330" "331" "332" "333" "334" "335" "336"
## [1576] "337" "338" "339" "340" "341" "342" "343"
## [1583] "344" "345" "346" "347" "348" "349" "350"
## [1590] "351" "352" "353" "354" "355" "356" "358"
## [1597] "359" "360" "361" "362" "363" "364" "365"
## [1604] "366" "367" "368" "369" "370" "371" "372"
## [1611] "373" "374" "375" "376" "377" "378" "379"
## [1618] "38" "380" "381" "382" "383" "384" "385"
## [1625] "386" "387" "388" "389" "390" "391" "392"
## [1632] "393" "394" "395" "396" "397" "398" "399"
## [1639] "400" "401" "402" "403" "404" "405" "406"
## [1646] "407" "408" "410" "411" "412" "413" "415"
## [1653] "416" "417" "418" "419" "42" "420" "422"
## [1660] "423" "424" "425" "426" "427" "428" "429"
## [1667] "43" "430" "431" "432" "433" "434" "435"
## [1674] "436" "437" "438" "439" "44" "440" "441"
## [1681] "442" "443" "444" "445" "446" "447" "448"
## [1688] "449" "450" "451" "452" "453" "454" "455"
## [1695] "456" "457" "458" "459" "460" "461" "462"
## [1702] "463" "464" "465" "466" "467" "468" "469"
## [1709] "470" "472" "473" "474" "475" "476" "478"
## [1716] "479" "48" "480" "481" "482" "483" "484"
## [1723] "485" "486" "487" "488" "489" "490" "491"
## [1730] "492" "493" "494" "495" "496" "497" "498"
## [1737] "499" "50" "500" "501" "502" "503" "504"
## [1744] "505" "506" "507" "508" "509" "510" "511"
## [1751] "512" "513" "514" "515" "516" "517" "518"
## [1758] "519" "52" "520" "521" "522" "523" "524"
## [1765] "525" "526" "527" "528" "529" "530" "531"
## [1772] "532" "533" "534" "535" "536" "537" "538"
## [1779] "539" "54" "540" "541" "542" "543" "544"
## [1786] "545" "546" "547" "548" "549" "550" "551"
## [1793] "552" "553" "554" "555" "556" "557" "558"
## [1800] "559" "560" "561" "562" "563" "564" "565"
## [1807] "566" "567" "568" "569" "570" "571" "572"
## [1814] "573" "574" "575" "576" "577" "578" "579"
## [1821] "580" "581" "582" "583" "584" "585" "586"
## [1828] "587" "588" "589" "59" "590" "591" "592"
## [1835] "593" "594" "595" "596" "597" "598" "599"
## [1842] "60" "600" "601" "602" "603" "604" "605"
## [1849] "606" "607" "608" "609" "610" "611" "612"
## [1856] "613" "614" "615" "616" "617" "618" "619"
## [1863] "620" "621" "622" "623" "624" "625" "626"
## [1870] "627" "628" "629" "63" "630" "631" "632"
## [1877] "633" "634" "635" "636" "637" "638" "639"
## [1884] "640" "641" "642" "643" "644" "645" "646"
## [1891] "647" "648" "649" "650" "651" "652" "653"
## [1898] "654" "655" "656" "657" "658" "659" "660"
## [1905] "661" "662" "663" "664" "665" "666" "667"
## [1912] "668" "669" "67" "670" "671" "672" "673"
## [1919] "674" "675" "676" "677" "678" "679" "68"
## [1926] "680" "681" "682" "683" "684" "685" "686"
## [1933] "687" "688" "689" "690" "691" "692" "693"
## [1940] "694" "695" "696" "697" "698" "699" "700"
## [1947] "701" "702" "703" "704" "705" "706" "707"
## [1954] "708" "709" "71" "710" "711" "712" "713"
## [1961] "714" "715" "716" "717" "718" "719" "720"
## [1968] "721" "722" "723" "724" "725" "726" "727"
## [1975] "728" "729" "730" "731" "732" "733" "734"
## [1982] "735" "736" "737" "738" "739" "740" "741"
## [1989] "742" "743" "744" "745" "746" "747" "748"
## [1996] "749" "75" "750" "751" "752" "753" "754"
## [2003] "755" "756" "757" "758" "759" "76" "760"
## [2010] "761" "762" "763" "764" "765" "766" "767"
## [2017] "768" "769" "770" "771" "772" "773" "774"
## [2024] "775" "776" "777" "778" "779" "780" "781"
## [2031] "782" "783" "784" "785" "786" "787" "788"
## [2038] "789" "790" "791" "792" "793" "794" "795"
## [2045] "796" "797" "798" "799" "80" "800" "801"
## [2052] "802" "803" "804" "805" "806" "807" "808"
## [2059] "809" "81" "810" "811" "812" "813" "814"
## [2066] "815" "816" "817" "818" "819" "820" "821"
## [2073] "822" "823" "824" "825" "826" "827" "828"
## [2080] "829" "830" "831" "832" "833" "834" "835"
## [2087] "836" "837" "838" "839" "840" "841" "842"
## [2094] "843" "844" "845" "846" "847" "848" "849"
## [2101] "85" "850" "851" "852" "853" "854" "855"
## [2108] "856" "857" "858" "859" "86" "860" "861"
## [2115] "862" "863" "864" "865" "866" "867" "868"
## [2122] "869" "870" "871" "872" "873" "874" "875"
## [2129] "876" "877" "878" "879" "88" "880" "881"
## [2136] "882" "883" "884" "885" "886" "887" "888"
## [2143] "889" "890" "891" "892" "893" "894" "895"
## [2150] "896" "897" "898" "899" "900" "901" "902"
## [2157] "903" "904" "905" "906" "907" "908" "909"
## [2164] "910" "911" "912" "913" "914" "915" "916"
## [2171] "917" "918" "919" "920" "921" "922" "923"
## [2178] "924" "925" "926" "927" "928" "929" "93"
## [2185] "930" "931" "932" "933" "934" "935" "936"
## [2192] "937" "938" "939" "94" "940" "941" "942"
## [2199] "943" "944" "945" "946" "947" "948" "949"
## [2206] "95" "950" "951" "952" "953" "954" "955"
## [2213] "956" "957" "958" "959" "960" "961" "962"
## [2220] "963" "964" "965" "966" "967" "968" "969"
## [2227] "97" "970" "971" "972" "973" "974" "975"
## [2234] "976" "977" "978" "979" "980" "981" "982"
## [2241] "983" "984" "985" "986" "987" "988" "989"
## [2248] "990" "991" "992" "993" "994" "995" "996"
## [2255] "997" "998" "999" "101" "107" "110" "114"
## [2262] "121" "126" "129" "132" "138" "14" "142"
## [2269] "15" "174" "176" "178" "19" "193" "207"
## [2276] "21" "210" "221" "222" "230" "251" "263"
## [2283] "29" "297" "34" "357" "36" "37" "39"
## [2290] "40" "409" "41" "471" "5" "56" "57"
## [2297] "6" "62" "64" "65" "70" "74" "77"
## [2304] "82" "9" "96" "102" "115" "12" "140"
## [2311] "144" "150" "157" "18" "23" "248" "25"
## [2318] "253" "26" "273" "28" "301" "31" "32"
## [2325] "421" "49" "51" "69" "72" "73" "89"
## [2332] "90" "98" "141" "153" "156" "170" "195"
## [2339] "208" "27" "277" "35" "4" "414" "45"
## [2346] "53" "61" "7" "78" "83" "84" "87"
## [2353] "91" "120" "130" "17" "175" "20" "22"
## [2360] "33" "47" "477" "55" "58" "66" "79"
## [2367] "10" "13" "46" "8" "113" "92" "99"## [1] 237413.3 What Fits Nearby
This is not a standalone mainline; it sits naturally between the three most closely related chapters.
- Before this chapter: cluster or annotate cells through the core workflow and reference mapping mainlines so that
group_colpoints to a meaningful cell-type variable. - Alongside this chapter: the Milo appendix chapter remains the standard route for neighbourhood-level abundance shifts, which can be thought of as a statistical companion to the ML-based priority ranking.
- After this chapter: spatial context and communication analysis can be used to validate whether the top-ranked states are also the ones that are spatially reorganized or highly communicative in the relevant condition.
13.4 Current Recommendation
For now the most practical route through this mainline is:
- Build a stable clustering and annotation baseline with the core workflow.
- Use
RunMilo()when the immediate question is abundance shift across conditions. - Use
RunPerturbationPriority()(orRunStatePriorityWorkflow()) when the question is which cell types are most molecularly responsive, regardless of abundance. - Keep
RunRareCellDetection()on the roadmap; when a backend is integrated, the object contract is already ready.