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The Survival Scatter plot shows the clinical status (i.e. dead or alive) for all individuals in the patient cohort, based on the same data that underlies the corresponding Kaplan-Meier plots. Patients that are alive at last time for follow-up are shown in blue and patients who have died during the study are shown in red.
The x-axis shows the expression levels (FPKM) of the investigated gene in the tumor tissue at the time of diagnosis. The y-axis shows the follow-up time after diagnosis (years). Both axes are complimented with kernel density curves demonstrating the data density over the axes. The top density plot shows the expression levels (FPKM) distribution among dead (red) and alive patients (blue). The right density plot shows the data density of the survived years of dead patients with high and low expression levels respectively, stratified using the cutoff indicated by the vertical dashed line through the Survival Scatter plot. This cutoff is automatically defined based on the FPKM cutoff that minimizes the p-score. The cutoff can be changed by dragging the vertical line or by entering a cutoff value in the square labeled "Current cut-off".
Under the Survival Scatter plot the p-score landscape (black curve; left axis) is shown together with dead median separation (red curve; right axis). Dead median separation is the difference in median mRNA expression between patients who have died with high and low expression, respectively. It is calculated as follows: median FPKM expression of dead patients with high expression - median FPKM expression of dead patients with low expression. This is intended to aid the user in visually exploring custom cutoffs and the associated p-scores and dead median separation.
Individual patient data is displayed and can be filtered by clicking on one or more of the category buttons on the top of the page. Categories describing expression level and patient information include: high, low, alive, dead, female, male and tumor stages. The scale of the x-axis can be toggled between linear and log-scale by clicking on the "x log" button. Mouse-over function shows TCGA ID, patient information and mRNA expression (FPKM) for each patient.
& Survival analysisi
Kaplan-Meier plots summarize results from analysis of correlation between mRNA expression level and patient survival. Patients were divided based on level of expression into one of the two groups "low" (under cut off) or "high" (over cut off). X-axis shows time for survival (years) and y-axis shows the probability of survival, where 1.0 corresponds to 100 percent.
The Survival Scatter plot shows the clinical status (i.e. dead or alive) for all individuals in the patient cohort, based on the same data that underlies the corresponding Kaplan-Meier plots. Patients that are alive at last time for follow-up are shown in blue and patients who have died during the study are shown in red.
The x-axis shows the expression levels (FPKM) of the investigated gene in the tumor tissue at the time of diagnosis. The y-axis shows the follow-up time after diagnosis (years). Both axes are complimented with kernel density curves demonstrating the data density over the axes. The top density plot shows the expression levels (FPKM) distribution among dead (red) and alive patients (blue). The right density plot shows the data density of the survived years of dead patients with high and low expression levels respectively, stratified using the cutoff indicated by the vertical dashed line through the Survival Scatter plot. This cutoff is automatically defined based on the FPKM cutoff that minimizes the p-score. The cutoff can be changed by dragging the vertical line or by entering a cutoff value in the square labeled "Current cut-off".
Under the Survival Scatter plot the p-score landscape (black curve; left axis) is shown together with dead median separation (red curve; right axis). Dead median separation is the difference in median mRNA expression between patients who have died with high and low expression, respectively. It is calculated as follows: median FPKM expression of dead patients with high expression - median FPKM expression of dead patients with low expression. This is intended to aid the user in visually exploring custom cutoffs and the associated p-scores and dead median separation.
Individual patient data is displayed and can be filtered by clicking on one or more of the category buttons on the top of the page. Categories describing expression level and patient information include: high, low, alive, dead, female, male and tumor stages. The scale of the x-axis can be toggled between linear and log-scale by clicking on the "x log" button. Mouse-over function shows TCGA ID, patient information and mRNA expression (FPKM) for each patient.
& Survival analysisi
Kaplan-Meier plots summarize results from analysis of correlation between mRNA expression level and patient survival. Patients were divided based on level of expression into one of the two groups "low" (under cut off) or "high" (over cut off). X-axis shows time for survival (years) and y-axis shows the probability of survival, where 1.0 corresponds to 100 percent.
Survival analysis data not available.
LIVER HEPATOCELLULAR CARCINOMA - Protein relative expression (CPTAC)
Number of samples
330
Samples
Sample ID
Sample type
nRPX
571
Tumor
2.9
357
Tumor
2.9
953
Tumor
2.6
627
Tumor
2.5
361
Tumor
2.5
423
Tumor
2.5
697
Tumor
2.4
713
Tumor
2.3
465
Tumor
2.3
411
Tumor
1.8
128
Normal
1.7
923
Tumor
1.7
393
Tumor
1.6
513
Tumor
1.4
722
Normal
1.4
491
Tumor
1.2
914
Normal
1.1
313
Tumor
1.1
426
Normal
1.1
616
Normal
1.0
148
Normal
1.0
227
Tumor
0.9
298
Normal
0.9
278
Normal
0.9
981
Tumor
0.8
648
Normal
0.8
344
Normal
0.8
138
Normal
0.8
628
Normal
0.8
472
Normal
0.7
944
Normal
0.7
114
Normal
0.7
258
Normal
0.7
355
Tumor
0.7
328
Normal
0.7
137
Tumor
0.7
746
Normal
0.7
1014
Normal
0.7
924
Normal
0.7
132
Normal
0.6
615
Tumor
0.6
642
Normal
0.6
695
Tumor
0.6
568
Normal
0.6
824
Normal
0.6
698
Normal
0.6
388
Normal
0.6
868
Normal
0.5
1028
Normal
0.5
136
Normal
0.5
456
Normal
0.5
546
Normal
0.5
214
Normal
0.5
755
Tumor
0.5
366
Normal
0.5
1022
Normal
0.5
1032
Normal
0.5
564
Normal
0.5
362
Normal
0.4
428
Normal
0.4
867
Tumor
0.4
462
Normal
0.4
534
Normal
0.4
487
Tumor
0.4
474
Normal
0.4
1045
Tumor
0.4
365
Tumor
0.4
172
Normal
0.3
466
Normal
0.3
364
Normal
0.3
816
Normal
0.3
786
Normal
0.3
464
Normal
0.3
228
Normal
0.3
618
Normal
0.3
954
Normal
0.3
968
Normal
0.3
232
Normal
0.2
728
Normal
0.2
257
Tumor
0.2
915
Tumor
0.2
268
Normal
0.2
356
Normal
0.2
436
Normal
0.2
572
Normal
0.1
358
Normal
0.1
864
Normal
0.1
448
Normal
0.1
468
Normal
0.1
714
Normal
0.1
396
Normal
0.1
481
Tumor
0.1
222
Normal
0.1
445
Tumor
0.1
882
Normal
0.1
518
Normal
0.1
422
Normal
0.0
484
Normal
0.0
412
Normal
0.0
444
Normal
0.0
982
Normal
0.0
647
Tumor
0.0
482
Normal
0.0
1046
Normal
0.0
352
Normal
0.0
1042
Normal
0.0
314
Normal
0.0
1044
Normal
-0.1
533
Tumor
-0.1
363
Tumor
-0.1
424
Normal
-0.1
866
Normal
-0.1
716
Normal
-0.1
976
Normal
-0.1
721
Tumor
-0.1
686
Normal
-0.1
911
Tumor
-0.1
141
Tumor
-0.1
196
Normal
-0.1
574
Normal
-0.1
473
Tumor
-0.1
874
Normal
-0.2
912
Normal
-0.2
818
Normal
-0.2
162
Normal
-0.2
557
Tumor
-0.2
967
Tumor
-0.2
1027
Tumor
-0.2
142
Normal
-0.2
353
Tumor
-0.2
414
Normal
-0.2
312
Normal
-0.2
666
Normal
-0.2
558
Normal
-0.3
272
Normal
-0.3
492
Normal
-0.3
342
Normal
-0.3
664
Normal
-0.3
376
Normal
-0.3
354
Normal
-0.3
922
Normal
-0.3
538
Normal
-0.3
416
Normal
-0.3
126
Normal
-0.3
984
Normal
-0.3
212
Normal
-0.3
332
Normal
-0.3
218
Normal
-0.3
916
Normal
-0.3
498
Normal
-0.3
862
Normal
-0.4
636
Normal
-0.4
386
Normal
-0.4
434
Normal
-0.4
956
Normal
-0.4
878
Normal
-0.4
756
Normal
-0.4
483
Tumor
-0.4
488
Normal
-0.4
964
Normal
-0.4
858
Normal
-0.4
432
Normal
-0.4
111
Normal
-0.4
526
Normal
-0.4
188
Normal
-0.5
528
Normal
-0.5
1013
Tumor
-0.5
852
Normal
-0.5
446
Normal
-0.5
368
Normal
-0.5
494
Normal
-0.5
327
Tumor
-0.5
525
Tumor
-0.5
926
Normal
-0.5
286
Normal
-0.5
394
Normal
-0.5
778
Normal
-0.5
738
Normal
-0.5
478
Normal
-0.6
554
Normal
-0.6
861
Tumor
-0.6
952
Normal
-0.6
884
Normal
-0.6
873
Tumor
-0.6
192
Normal
-0.6
161
Tumor
-0.6
277
Tumor
-0.6
514
Normal
-0.6
186
Normal
-0.6
1016
Normal
-0.7
1043
Tumor
-0.7
957
Tumor
-0.7
146
Normal
-0.7
723
Tumor
-0.7
221
Tumor
-0.7
696
Normal
-0.7
685
Tumor
-0.7
461
Tumor
-0.7
421
Tumor
-0.7
452
Normal
-0.7
662
Normal
-0.7
384
Normal
-0.7
978
Normal
-0.7
918
Normal
-0.7
451
Tumor
-0.8
224
Normal
-0.8
1026
Normal
-0.8
958
Normal
-0.8
672
Normal
-0.8
284
Normal
-0.8
195
Tumor
-0.8
823
Tumor
-0.9
563
Tumor
-0.9
523
Tumor
-0.9
536
Normal
-0.9
211
Tumor
-0.9
443
Tumor
-0.9
635
Tumor
-0.9
938
Normal
-1.0
567
Tumor
-1.0
742
Normal
-1.0
343
Tumor
-1.0
415
Tumor
-1.0
262
Normal
-1.0
127
Tumor
-1.0
1041
Tumor
-1.0
341
Tumor
-1.1
217
Tumor
-1.1
524
Normal
-1.1
311
Tumor
-1.1
427
Tumor
-1.1
392
Normal
-1.1
375
Tumor
-1.2
966
Normal
-1.2
223
Tumor
-1.2
493
Tumor
-1.2
413
Tumor
-1.2
516
Normal
-1.2
963
Tumor
-1.2
351
Tumor
-1.2
145
Tumor
-1.3
112
Tumor
-1.3
425
Tumor
-1.3
857
Tumor
-1.3
617
Tumor
-1.3
187
Tumor
-1.3
383
Tumor
-1.3
641
Tumor
-1.4
447
Tumor
-1.4
267
Tumor
-1.4
863
Tumor
-1.4
124
Normal
-1.4
213
Tumor
-1.4
125
Tumor
-1.4
943
Tumor
-1.4
535
Tumor
-1.4
431
Tumor
-1.4
573
Tumor
-1.4
135
Tumor
-1.4
123
Tumor
-1.4
191
Tumor
-1.4
391
Tumor
-1.5
744
Normal
-1.5
331
Tumor
-1.5
917
Tumor
-1.5
185
Tumor
-1.5
497
Tumor
-1.5
231
Tumor
-1.5
261
Tumor
-1.5
463
Tumor
-1.5
297
Tumor
-1.5
285
Tumor
-1.5
715
Tumor
-1.6
745
Tumor
-1.6
387
Tumor
-1.6
433
Tumor
-1.6
467
Tumor
-1.7
283
Tumor
-1.7
977
Tumor
-1.7
455
Tumor
-1.7
671
Tumor
-1.7
553
Tumor
-1.7
131
Tumor
-1.7
777
Tumor
-1.7
113
Tumor
-1.8
517
Tumor
-1.8
367
Tumor
-1.8
951
Tumor
-1.8
955
Tumor
-1.8
663
Tumor
-1.9
814
Normal
-1.9
271
Tumor
-1.9
147
Tumor
-1.9
395
Tumor
-1.9
877
Tumor
-1.9
537
Tumor
-2.0
785
Tumor
-2.0
921
Tumor
-2.0
527
Tumor
-2.0
171
Tumor
-2.0
515
Tumor
-2.0
545
Tumor
-2.0
865
Tumor
-2.0
471
Tumor
-2.0
743
Tumor
-2.1
881
Tumor
-2.1
477
Tumor
-2.1
975
Tumor
-2.1
913
Tumor
-2.1
1021
Tumor
-2.2
1031
Tumor
-2.2
1015
Tumor
-2.2
1025
Tumor
-2.2
925
Tumor
-2.2
817
Tumor
-2.2
815
Tumor
-2.2
435
Tumor
-2.2
813
Tumor
-2.2
937
Tumor
-2.2
665
Tumor
-2.3
851
Tumor
-2.3
883
Tumor
-2.3
385
Tumor
-2.3
741
Tumor
-2.4
965
Tumor
-2.4
983
Tumor
-2.5
661
Tumor
-2.5
727
Tumor
-2.6
737
Tumor
-2.6
724
Normal
-3.4
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LIVER CANCER - Protein expressioni
A mouse-over function shows sample information and annotation data. Click on an image to view it in a full screen mode. Samples can be filtered based on level of antibody staining by selecting one or several of the following categories: high, medium, low and not detected. The assay and annotation is described here.
Note that samples used for immunohistochemistry by the Human Protein Atlas do not correspond to samples in the TCGA dataset.
Antibody stainingi
Antibody staining in the annotated cell types in the current human tissue is reported as not detected, low, medium, or high, based on conventional immunohistochemistry profiling in selected tissues. This score is based on the combination of the staining intensity and fraction of stained cells.
Each image is clickable and will lead to virtual microscopy that enables deeper exploration of all samples and also displays staining intensity scores, fraction scores and subcellular localization as well as patient and tissue information for each sample.