IanevskiAleksandr
commented
2 years ago Hi,
Can you show the ouput of print(nodes) to see all the node data you have?
Thanks, Aleksandr
Open RENXI-NUS opened 2 years ago
IanevskiAleksandr
commented
2 years ago Hi,
Can you show the ouput of print(nodes) to see all the node data you have?
Thanks, Aleksandr
RENXI-NUS
commented
2 years ago Sure. This is all the node data:
> print(nodes)
cluster ncells Colour ord shortName realname
1 Memory CD8+ T cells_0 5929.974269 #5f75ae 2 Memory CD8+ T Memory CD8+ T cells
2 Memory CD8+ T cells_12 68.165898 #cab2d6 2 Memory CD8+ T Memory CD8+ T cells
3 Memory CD8+ T cells_9 107.735041 #b15928 2 Memory CD8+ T Memory CD8+ T cells
4 Memory CD8+ T cells_10 135.501122 #ffff99 2 Memory CD8+ T Memory CD8+ T cells
5 Memory CD8+ T cells_5 1264.185179 #eccf5a 2 Memory CD8+ T Memory CD8+ T cells
6 Memory CD8+ T cells_11 1.000000 #6a3d9a 2 Memory CD8+ T Memory CD8+ T cells
7 Naive CD8+ T cells_11 58.671935 #6a3d9a 2 Naive CD8+ T Naive CD8+ T cells
8 Naive CD8+ T cells_2 1.000000 #64a841 2 Naive CD8+ T Naive CD8+ T cells
9 Naive CD8+ T cells_12 39.056222 #cab2d6 2 Naive CD8+ T Naive CD8+ T cells
10 Naive CD8+ T cells_8 1.000000 #7ba39d 2 Naive CD8+ T Naive CD8+ T cells
11 Naive CD8+ T cells_3 1.000000 #e5486e 2 Naive CD8+ T Naive CD8+ T cells
12 Naive CD8+ T cells_0 5000.859816 #5f75ae 2 Naive CD8+ T Naive CD8+ T cells
13 Naive CD8+ T cells_6 1.000000 #b5aa0f 2 Naive CD8+ T Naive CD8+ T cells
14 Naive CD8+ T cells_10 153.365503 #ffff99 2 Naive CD8+ T Naive CD8+ T cells
15 Naive CD8+ T cells_9 1.000000 #b15928 2 Naive CD8+ T Naive CD8+ T cells
16 Naive CD8+ T cells_5 1429.376909 #eccf5a 2 Naive CD8+ T Naive CD8+ T cells
17 <U+03B3>d-T cells_4 1.000000 #de8e06 2 <U+03B3>d-T <U+03B3>d-T cells
18 <U+03B3>d-T cells_9 1.000000 #b15928 2 <U+03B3>d-T <U+03B3>d-T cells
19 <U+03B3>d-T cells_0 4304.082581 #5f75ae 2 <U+03B3>d-T <U+03B3>d-T cells
20 <U+03B3>d-T cells_10 76.297035 #ffff99 2 <U+03B3>d-T <U+03B3>d-T cells
21 <U+03B3>d-T cells_5 789.043994 #eccf5a 2 <U+03B3>d-T <U+03B3>d-T cells
22 <U+03B3>d-T cells_11 27.200183 #6a3d9a 2 <U+03B3>d-T <U+03B3>d-T cells
23 Effector CD8+ T cells_0 4165.662905 #5f75ae 2 Effector CD8+ T Effector CD8+ T cells
24 Effector CD8+ T cells_5 992.117888 #eccf5a 2 Effector CD8+ T Effector CD8+ T cells
25 Effector CD8+ T cells_2 1.000000 #64a841 2 Effector CD8+ T Effector CD8+ T cells
26 Effector CD8+ T cells_11 22.453698 #6a3d9a 2 Effector CD8+ T Effector CD8+ T cells
27 Effector CD8+ T cells_10 102.811108 #ffff99 2 Effector CD8+ T Effector CD8+ T cells
28 CD8+ NKT-like cells_10 185.969145 #ffff99 2 CD8+ NKT CD8+ NKT-like cells
29 CD8+ NKT-like cells_0 1930.771376 #5f75ae 2 CD8+ NKT CD8+ NKT-like cells
30 CD8+ NKT-like cells_12 36.488631 #cab2d6 2 CD8+ NKT CD8+ NKT-like cells
31 CD8+ NKT-like cells_4 2196.150886 #de8e06 2 CD8+ NKT CD8+ NKT-like cells
32 CD8+ NKT-like cells_5 1995.301472 #eccf5a 2 CD8+ NKT CD8+ NKT-like cells
33 Cancer cells_0 1.000000 #5f75ae 2 Cancer Cancer cells
34 Cancer cells_6 28.799347 #b5aa0f 2 Cancer Cancer cells
35 Cancer cells_11 4.369094 #6a3d9a 2 Cancer Cancer cells
36 Cancer cells_3 2103.388839 #e5486e 2 Cancer Cancer cells
37 Cancer cells_9 33.814999 #b15928 2 Cancer Cancer cells
38 Cancer cells_8 241.768124 #7ba39d 2 Cancer Cancer cells
39 Cancer cells_2 1.000000 #64a841 2 Cancer Cancer cells
40 Cancer cells_4 1.000000 #de8e06 2 Cancer Cancer cells
41 Cancer cells_5 1.000000 #eccf5a 2 Cancer Cancer cells
42 Mast cells_0 1.000000 #5f75ae 2 Mast Mast cells
43 Mast cells_2 1.000000 #64a841 2 Mast Mast cells
44 Mast cells_0 1.000000 #5f75ae 2 Mast Mast cells
45 Mast cells_9 115.985219 #b15928 2 Mast Mast cells
46 Mast cells_6 1.000000 #b5aa0f 2 Mast Mast cells
47 Mast cells_5 1.000000 #eccf5a 2 Mast Mast cells
48 Mast cells_1 2189.034192 #92bbb8 2 Mast Mast cells
49 Mast cells_7 801.513102 #e4b680 2 Mast Mast cells
50 Mast cells_1 2189.034192 #92bbb8 2 Mast Mast cells
51 Mast cells_9 115.985219 #b15928 2 Mast Mast cells
52 Mast cells_8 1.000000 #7ba39d 2 Mast Mast cells
53 Mast cells_4 1.000000 #de8e06 2 Mast Mast cells
54 Mast cells_4 1.000000 #de8e06 2 Mast Mast cells
55 Mast cells_8 1.000000 #7ba39d 2 Mast Mast cells
56 Mast cells_6 1.000000 #b5aa0f 2 Mast Mast cells
57 Mast cells_7 801.513102 #e4b680 2 Mast Mast cells
58 Mast cells_2 1.000000 #64a841 2 Mast Mast cells
59 Monocytes_0 1.000000 #5f75ae 2 Monocytes Monocytes
60 Monocytes_4 1.000000 #de8e06 2 Monocytes Monocytes
61 Monocytes_6 1.000000 #b5aa0f 2 Monocytes Monocytes
62 Monocytes_3 233.497361 #e5486e 2 Monocytes Monocytes
63 Monocytes_1 2850.473189 #92bbb8 2 Monocytes Monocytes
64 Monocytes_8 1.000000 #7ba39d 2 Monocytes Monocytes
65 Monocytes_5 1.000000 #eccf5a 2 Monocytes Monocytes
66 Pre-B cells_9 273.405072 #b15928 2 Pre-B Pre-B cells
67 Pre-B cells_0 1.000000 #5f75ae 2 Pre-B Pre-B cells
68 Pre-B cells_8 1.000000 #7ba39d 2 Pre-B Pre-B cells
69 Pre-B cells_3 1.000000 #e5486e 2 Pre-B Pre-B cells
70 Pre-B cells_1 2136.511173 #92bbb8 2 Pre-B Pre-B cells
71 Pre-B cells_7 493.365862 #e4b680 2 Pre-B Pre-B cells
72 Pre-B cells_4 2.334262 #de8e06 2 Pre-B Pre-B cells
73 Pre-B cells_6 1.000000 #b5aa0f 2 Pre-B Pre-B cells
74 Pre-B cells_5 1.000000 #eccf5a 2 Pre-B Pre-B cells
75 Kupffer cells_7 616.170813 #e4b680 2 Kupffer Kupffer cells
76 Kupffer cells_1 12313.277806 #92bbb8 2 Kupffer Kupffer cells
77 Macrophages_1 10078.778436 #92bbb8 2 MF Macrophages
78 Macrophages_7 717.097822 #e4b680 2 MF Macrophages
79 Non-classical monocytes_7 535.182624 #e4b680 2 N_Monocytes Non-classical monocytes
80 Non-classical monocytes_1 9456.779044 #92bbb8 2 N_Monocytes Non-classical monocytes
81 Non-classical monocytes_12 6.087715 #cab2d6 2 N_Monocytes Non-classical monocytes
82 Myeloid Dendritic cells_7 1497.933147 #e4b680 2 mDCs Myeloid Dendritic cells
83 Myeloid Dendritic cells_12 108.686473 #cab2d6 2 mDCs Myeloid Dendritic cells
84 Myeloid Dendritic cells_1 7620.180904 #92bbb8 2 mDCs Myeloid Dendritic cells
85 Myeloid Dendritic cells_2 1.000000 #64a841 2 mDCs Myeloid Dendritic cells
86 Myeloid Dendritic cells_9 162.289399 #b15928 2 mDCs Myeloid Dendritic cells
87 Myeloid Dendritic cells_11 1.000000 #6a3d9a 2 mDCs Myeloid Dendritic cells
88 Granulocytes_7 618.507170 #e4b680 2 Gs Granulocytes
89 Granulocytes_1 5798.071007 #92bbb8 2 Gs Granulocytes
90 Granulocytes_9 1.000000 #b15928 2 Gs Granulocytes
91 Granulocytes_12 1.203136 #cab2d6 2 Gs Granulocytes
92 Granulocytes_3 1.000000 #e5486e 2 Gs Granulocytes
93 Neutrophils_8 1.000000 #7ba39d 2 Neutrophils Neutrophils
94 Neutrophils_1 4882.408766 #92bbb8 2 Neutrophils Neutrophils
95 Neutrophils_3 736.620560 #e5486e 2 Neutrophils Neutrophils
96 Neutrophils_4 1.000000 #de8e06 2 Neutrophils Neutrophils
97 Neutrophils_6 1.000000 #b5aa0f 2 Neutrophils Neutrophils
98 Neutrophils_7 235.076039 #e4b680 2 Neutrophils Neutrophils
99 Endothelial cell_10 201.558556 #ffff99 2 Endothelial cell Endothelial cell
100 Endothelial cell_10 201.558556 #ffff99 2 Endothelial Endothelial cell
101 Endothelial cell_11 179.498811 #6a3d9a 2 Endothelial cell Endothelial cell
102 Endothelial cell_11 179.498811 #6a3d9a 2 Endothelial Endothelial cell
103 Endothelial cell_12 22.225843 #cab2d6 2 Endothelial cell Endothelial cell
104 Endothelial cell_12 22.225843 #cab2d6 2 Endothelial Endothelial cell
105 Endothelial cell_2 10796.720396 #64a841 2 Endothelial cell Endothelial cell
106 Endothelial cell_2 10796.720396 #64a841 2 Endothelial Endothelial cell
107 Endothelial_11 56.153587 #6a3d9a 2 ECs Endothelial
108 Endothelial_2 9153.015708 #64a841 2 ECs Endothelial
109 Endothelial_10 224.401644 #ffff99 2 ECs Endothelial
110 HSC/MPP cells_10 227.608255 #ffff99 2 HSC/MPP HSC/MPP cells
111 HSC/MPP cells_3 1.000000 #e5486e 2 HSC/MPP HSC/MPP cells
112 HSC/MPP cells_11 159.728225 #6a3d9a 2 HSC/MPP HSC/MPP cells
113 HSC/MPP cells_2 3920.796905 #64a841 2 HSC/MPP HSC/MPP cells
114 Hepatic stellate cells_11 2424.171345 #6a3d9a 2 HSCs Hepatic stellate cells
115 Hepatic stellate cells_10 4.164938 #ffff99 2 HSCs Hepatic stellate cells
116 Hepatic stellate cells_6 1.000000 #b5aa0f 2 HSCs Hepatic stellate cells
117 Hepatic stellate cells_2 2457.543702 #64a841 2 HSCs Hepatic stellate cells
118 Hepatic stellate cells_12 33.251052 #cab2d6 2 HSCs Hepatic stellate cells
119 Hepatic stellate cells_3 194.450838 #e5486e 2 HSCs Hepatic stellate cells
120 Hepatocytes_6 1682.545120 #b5aa0f 2 Hepatocytes Hepatocytes
121 Hepatocytes_3 23653.016087 #e5486e 2 Hepatocytes Hepatocytes
122 Hepatocytes_8 1398.015667 #7ba39d 2 Hepatocytes Hepatocytes
123 Memory B cells_4 1.000000 #de8e06 2 Memory B Memory B cells
124 Memory B cells_7 263.827108 #e4b680 2 Memory B Memory B cells
125 Memory B cells_8 188.009481 #7ba39d 2 Memory B Memory B cells
126 Memory B cells_9 786.106144 #b15928 2 Memory B Memory B cells
127 Memory B cells_12 41.586705 #cab2d6 2 Memory B Memory B cells
128 Memory B cells_3 2569.625694 #e5486e 2 Memory B Memory B cells
129 Natural killer cells_6 1.000000 #b5aa0f 2 NK Natural killer cells
130 Natural killer cells_5 1830.932576 #eccf5a 2 NK Natural killer cells
131 Natural killer cells_8 1.000000 #7ba39d 2 NK Natural killer cells
132 Natural killer cells_12 39.871433 #cab2d6 2 NK Natural killer cells
133 Natural killer cells_4 3745.213922 #de8e06 2 NK Natural killer cells
134 Natural killer cells_10 49.623020 #ffff99 2 NK Natural killer cells
135 cluster 5 916.000000 #f1f1ef 1 cluster 5 cluster 5
136 cluster 0 4552.000000 #f1f1ef 1 cluster 0 cluster 0
137 cluster 1 3691.000000 #f1f1ef 1 cluster 1 cluster 1
138 cluster 7 341.000000 #f1f1ef 1 cluster 7 cluster 7
139 cluster 4 1933.000000 #f1f1ef 1 cluster 4 cluster 4
140 cluster 10 239.000000 #f1f1ef 1 cluster 10 cluster 10
141 cluster 3 2474.000000 #f1f1ef 1 cluster 3 cluster 3
142 cluster 9 241.000000 #f1f1ef 1 cluster 9 cluster 9
143 cluster 12 42.000000 #f1f1ef 1 cluster 12 cluster 12
144 cluster 2 3366.000000 #f1f1ef 1 cluster 2 cluster 2
145 cluster 8 283.000000 #f1f1ef 1 cluster 8 cluster 8
146 cluster 6 632.000000 #f1f1ef 1 cluster 6 cluster 6
147 cluster 11 175.000000 #f1f1ef 1 cluster 11 cluster 11And this is my edge data:
> print(edges)
from to
1 cluster 0 Memory CD8+ T cells_0
2 cluster 0 Naive CD8+ T cells_0
3 cluster 0 <U+03B3>d-T cells_0
4 cluster 0 Effector CD8+ T cells_0
5 cluster 0 CD8+ NKT-like cells_0
6 cluster 0 Cancer cells_0
7 cluster 0 Mast cells_0
8 cluster 0 Mast cells_0
9 cluster 0 Monocytes_0
10 cluster 0 Pre-B cells_0
11 cluster 1 Kupffer cells_1
12 cluster 1 Macrophages_1
13 cluster 1 Non-classical monocytes_1
14 cluster 1 Myeloid Dendritic cells_1
15 cluster 1 Granulocytes_1
16 cluster 1 Neutrophils_1
17 cluster 1 Monocytes_1
18 cluster 1 Mast cells_1
19 cluster 1 Mast cells_1
20 cluster 1 Pre-B cells_1
21 cluster 2 Endothelial cell_2
22 cluster 2 Endothelial_2
23 cluster 2 HSC/MPP cells_2
24 cluster 2 Hepatic stellate cells_2
25 cluster 2 Naive CD8+ T cells_2
26 cluster 2 Cancer cells_2
27 cluster 2 Myeloid Dendritic cells_2
28 cluster 2 Mast cells_2
29 cluster 2 Mast cells_2
30 cluster 2 Effector CD8+ T cells_2
31 cluster 3 Hepatocytes_3
32 cluster 3 Memory B cells_3
33 cluster 3 Cancer cells_3
34 cluster 3 Neutrophils_3
35 cluster 3 Monocytes_3
36 cluster 3 Hepatic stellate cells_3
37 cluster 3 HSC/MPP cells_3
38 cluster 3 Pre-B cells_3
39 cluster 3 Naive CD8+ T cells_3
40 cluster 3 Granulocytes_3
41 cluster 4 Natural killer cells_4
42 cluster 4 CD8+ NKT-like cells_4
43 cluster 4 Pre-B cells_4
44 cluster 4 Mast cells_4
45 cluster 4 Mast cells_4
46 cluster 4 Cancer cells_4
47 cluster 4 Memory B cells_4
48 cluster 4 Monocytes_4
49 cluster 4 <U+03B3>d-T cells_4
50 cluster 4 Neutrophils_4
51 cluster 5 CD8+ NKT-like cells_5
52 cluster 5 Natural killer cells_5
53 cluster 5 Naive CD8+ T cells_5
54 cluster 5 Memory CD8+ T cells_5
55 cluster 5 Effector CD8+ T cells_5
56 cluster 5 <U+03B3>d-T cells_5
57 cluster 5 Cancer cells_5
58 cluster 5 Pre-B cells_5
59 cluster 5 Monocytes_5
60 cluster 5 Mast cells_5
61 cluster 6 Hepatocytes_6
62 cluster 6 Cancer cells_6
63 cluster 6 Naive CD8+ T cells_6
64 cluster 6 Neutrophils_6
65 cluster 6 Monocytes_6
66 cluster 6 Mast cells_6
67 cluster 6 Mast cells_6
68 cluster 6 Natural killer cells_6
69 cluster 6 Pre-B cells_6
70 cluster 6 Hepatic stellate cells_6
71 cluster 7 Myeloid Dendritic cells_7
72 cluster 7 Mast cells_7
73 cluster 7 Mast cells_7
74 cluster 7 Macrophages_7
75 cluster 7 Granulocytes_7
76 cluster 7 Kupffer cells_7
77 cluster 7 Non-classical monocytes_7
78 cluster 7 Pre-B cells_7
79 cluster 7 Memory B cells_7
80 cluster 7 Neutrophils_7
81 cluster 8 Hepatocytes_8
82 cluster 8 Cancer cells_8
83 cluster 8 Memory B cells_8
84 cluster 8 Neutrophils_8
85 cluster 8 Monocytes_8
86 cluster 8 Naive CD8+ T cells_8
87 cluster 8 Natural killer cells_8
88 cluster 8 Mast cells_8
89 cluster 8 Mast cells_8
90 cluster 8 Pre-B cells_8
91 cluster 9 Memory B cells_9
92 cluster 9 Pre-B cells_9
93 cluster 9 Myeloid Dendritic cells_9
94 cluster 9 Mast cells_9
95 cluster 9 Mast cells_9
96 cluster 9 Memory CD8+ T cells_9
97 cluster 9 Cancer cells_9
98 cluster 9 Naive CD8+ T cells_9
99 cluster 9 Granulocytes_9
100 cluster 9 <U+03B3>d-T cells_9
101 cluster 10 HSC/MPP cells_10
102 cluster 10 Endothelial_10
103 cluster 10 Endothelial cell_10
104 cluster 10 CD8+ NKT-like cells_10
105 cluster 10 Naive CD8+ T cells_10
106 cluster 10 Memory CD8+ T cells_10
107 cluster 10 Effector CD8+ T cells_10
108 cluster 10 <U+03B3>d-T cells_10
109 cluster 10 Natural killer cells_10
110 cluster 10 Hepatic stellate cells_10
111 cluster 11 Hepatic stellate cells_11
112 cluster 11 Endothelial cell_11
113 cluster 11 HSC/MPP cells_11
114 cluster 11 Naive CD8+ T cells_11
115 cluster 11 Endothelial_11
116 cluster 11 <U+03B3>d-T cells_11
117 cluster 11 Effector CD8+ T cells_11
118 cluster 11 Cancer cells_11
119 cluster 11 Myeloid Dendritic cells_11
120 cluster 11 Memory CD8+ T cells_11
121 cluster 12 Myeloid Dendritic cells_12
122 cluster 12 Memory CD8+ T cells_12
123 cluster 12 Memory B cells_12
124 cluster 12 Natural killer cells_12
125 cluster 12 Naive CD8+ T cells_12
126 cluster 12 CD8+ NKT-like cells_12
127 cluster 12 Hepatic stellate cells_12
128 cluster 12 Endothelial cell_12
129 cluster 12 Non-classical monocytes_12
130 cluster 12 Granulocytes_12
smk5g5
commented
2 years ago +1 to this error!
I am also getting this error!
PottsC
commented
2 years ago I am having this error as well! Just +1-ing this
mnagy1716
commented
2 years ago Also having this error, would be grateful to use this feature!
katkoad
commented
2 years ago Also having this error and have not found a fix yet
smk5g5
commented
2 years ago I think just using
mygraph <- graph_from_data_frame(unique(edges), vertices=unique(nodes))
will solve the problem but I am not sure if it would give the right answer. i.e. it will help generate the plot but not sure if that plot would be right.
gmcregis
commented
2 years ago I think just using
mygraph <- graph_from_data_frame(unique(edges), vertices=unique(nodes))will solve the problem but I am not sure if it would give the right answer. i.e. it will help generate the plot but not sure if that plot would be right.
this didn't work for me, if anyone has any other ideas would be greatly appreciated
IanevskiAleksandr
commented
2 years ago @smk5g5 @RENXI-NUS @gmcregis @katkoad
I tried from two different PCs, but cannot replicate the error. Could you please share sessionInfo(); output?
It would be also very helpful if you can share save.image(file = "test.RData") file.
Thanks, Aleksandr
gmcregis
commented
2 years ago mygraph1 <- graph_from_data_frame(unique(edges1), vertices=unique(nodes1)) Error in graph_from_data_frame(unique(edges1), vertices = unique(nodes1)) : Duplicate vertex names mygraph1 <- graph_from_data_frame(edges1, vertices=nodes1) Error in graph_from_data_frame(edges1, vertices = nodes1) : Duplicate vertex names sessionInfo() R version 4.0.1 (2020-06-06) Platform: x86_64-apple-darwin17.0 (64-bit) Running under: OS X 12.3.1
Matrix products: default LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] data.tree_1.0.0 igraph_1.3.0 ggraph_2.0.5
[4] HGNChelper_0.8.1 scales_1.2.0 survival_3.3-1
[7] progress_1.2.2 preprocessCore_1.50.0 SeuratData_0.2.1
[10] SeuratDisk_0.0.0.9019 Scissor_2.0.0 Matrix_1.4-1
[13] SeuratObject_4.0.4 Seurat_4.1.0 knitr_1.38
[16] janitor_2.1.0 forcats_0.5.1 stringr_1.4.0
[19] dplyr_1.0.9 purrr_0.3.4 readr_2.1.2
[22] tidyr_1.2.0 tibble_3.1.7 ggplot2_3.3.6
[25] tidyverse_1.3.1
loaded via a namespace (and not attached):
[1] readxl_1.4.0 backports_1.4.1 plyr_1.8.7
[4] lazyeval_0.2.2 splines_4.0.1 listenv_0.8.0
[7] scattermore_0.8 digest_0.6.29 htmltools_0.5.2
[10] viridis_0.6.2 fansi_1.0.3 magrittr_2.0.3
[13] memoise_2.0.1 tensor_1.5 cluster_2.1.3
[16] ROCR_1.0-11 limma_3.44.3 tzdb_0.3.0
[19] openxlsx_4.2.5 graphlayouts_0.8.0 globals_0.14.0
[22] modelr_0.1.8 matrixStats_0.62.0 spatstat.sparse_2.1-0
[25] prettyunits_1.1.1 colorspace_2.0-3 rappdirs_0.3.3
[28] blob_1.2.3 rvest_1.0.2 ggrepel_0.9.1
[31] haven_2.4.3 xfun_0.30 crayon_1.5.1
[34] jsonlite_1.8.0 spatstat.data_2.1-4 zoo_1.8-9
[37] glue_1.6.2 polyclip_1.10-0 gtable_0.3.0
[40] leiden_0.3.9 future.apply_1.8.1 BiocGenerics_0.36.1
[43] abind_1.4-5 DBI_1.1.2 spatstat.random_2.2-0
[46] miniUI_0.1.1.1 Rcpp_1.0.8.3 viridisLite_0.4.0
[49] xtable_1.8-4 reticulate_1.24 spatstat.core_2.4-2
[52] bit_4.0.4 stats4_4.0.1 DT_0.22
[55] htmlwidgets_1.5.4 httr_1.4.3 RColorBrewer_1.1-3
[58] ellipsis_0.3.2 ica_1.0-2 farver_2.1.0
[61] pkgconfig_2.0.3 uwot_0.1.11 deldir_1.0-6
[64] dbplyr_2.1.1 utf8_1.2.2 here_1.0.1
[67] labeling_0.4.2 tidyselect_1.1.2 rlang_1.0.2
[70] reshape2_1.4.4 later_1.3.0 AnnotationDbi_1.52.0
[73] munsell_0.5.0 cellranger_1.1.0 tools_4.0.1
[76] cachem_1.0.6 cli_3.3.0 generics_0.1.2
[79] RSQLite_2.2.14 broom_0.7.12 ggridges_0.5.3
[82] evaluate_0.15 fastmap_1.1.0 goftest_1.2-3
[85] yaml_2.3.5 bit64_4.0.5 fs_1.5.2
[88] tidygraph_1.2.0 fitdistrplus_1.1-8 zip_2.2.0
[91] RANN_2.6.1 nlme_3.1-157 pbapply_1.5-0
[94] future_1.24.0 mime_0.12 xml2_1.3.3
[97] hdf5r_1.3.5 compiler_4.0.1 rstudioapi_0.13
[100] plotly_4.10.0 png_0.1-7 spatstat.utils_2.3-0
[103] reprex_2.0.1 tweenr_1.0.2 stringi_1.7.6
[106] lattice_0.20-45 vctrs_0.4.1 pillar_1.7.0
[109] lifecycle_1.0.1 spatstat.geom_2.4-0 lmtest_0.9-40
[112] RcppAnnoy_0.0.19 data.table_1.14.2 cowplot_1.1.1
[115] irlba_2.3.5 httpuv_1.6.5 patchwork_1.1.1
[118] R6_2.5.1 promises_1.2.0.1 KernSmooth_2.23-20
[121] gridExtra_2.3 IRanges_2.24.1 parallelly_1.30.0
[124] codetools_0.2-18 MASS_7.3-56 assertthat_0.2.1
[127] rprojroot_2.0.3 withr_2.5.0 sctransform_0.3.3
[130] S4Vectors_0.28.1 mgcv_1.8-40 parallel_4.0.1
[133] hms_1.1.1 rpart_4.1.16 grid_4.0.1
[136] rmarkdown_2.13 snakecase_0.11.0 Rtsne_0.15
[139] ggforce_0.3.3 Biobase_2.50.0 shiny_1.7.1
[142] lubridate_1.8.0
IanevskiAleksandr
commented
2 years ago Do you get this error with an example data?
kythol
commented
2 years ago Hi, I'm having the same issue. It is not the case with example data. In my case I see that there are duplicates in the nodes$cluster column (246 total rows vs 231 unique rows). I was using the Lung gene set
Since I knew my issue was with only two short names (Immune system / Immune and Endothelial cells / Endothelial), I ran this loop to pick the shortest string and it worked
for( i in unique(nodes$realname)){ a<-subset(nodes, realname == i) if( length(unique(a$shortName)) > 1){ nodes[nodes["realname"] == i,"shortName"]<-min(char(unique(a$shortName))) } } nodes<-nodes[!duplicated(nodes),]
Hope it helps and thanks a lot for the package, it is wonderful. Lisa
elisaudayani
commented
1 year ago Hi Lisa, thank you so much for sharing the loop codes! Now the code works for me as well. I found the same duplicates issue in the nodes$cluster, I used the Brain gene set. -Juli
Hi,
Thanks for the useful software. May I ask how to solve the "duplicate vertex names" error when visualizing a bubble plot by ScType please?