We use cookies to enhance the usability of our website. If you continue, we'll assume that you are happy to receive all cookies. More information. Don't show this again.
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
744
Normal
2.1
298
Normal
1.9
487
Tumor
1.7
728
Normal
1.7
342
Normal
1.6
465
Tumor
1.6
818
Normal
1.6
648
Normal
1.5
482
Normal
1.5
981
Tumor
1.4
196
Normal
1.4
392
Normal
1.3
462
Normal
1.3
746
Normal
1.3
488
Normal
1.3
445
Tumor
1.2
745
Tumor
1.2
313
Tumor
1.2
866
Normal
1.2
355
Tumor
1.2
523
Tumor
1.2
356
Normal
1.1
964
Normal
1.1
261
Tumor
1.1
146
Normal
1.1
982
Normal
1.1
882
Normal
1.0
227
Tumor
1.0
642
Normal
1.0
148
Normal
1.0
922
Normal
1.0
358
Normal
1.0
353
Tumor
1.0
448
Normal
0.9
1032
Normal
0.9
647
Tumor
0.9
354
Normal
0.9
142
Normal
0.9
862
Normal
0.9
132
Normal
0.9
423
Tumor
0.9
727
Tumor
0.8
376
Normal
0.8
664
Normal
0.8
714
Normal
0.8
564
Normal
0.8
756
Normal
0.8
755
Tumor
0.8
1026
Normal
0.8
968
Normal
0.8
742
Normal
0.8
111
Normal
0.8
145
Tumor
0.7
452
Normal
0.7
357
Tumor
0.7
1027
Tumor
0.7
456
Normal
0.7
883
Tumor
0.7
498
Normal
0.7
172
Normal
0.7
466
Normal
0.7
222
Normal
0.6
428
Normal
0.6
813
Tumor
0.6
1016
Normal
0.6
984
Normal
0.6
914
Normal
0.6
267
Tumor
0.6
314
Normal
0.6
262
Normal
0.6
884
Normal
0.6
1044
Normal
0.6
696
Normal
0.6
977
Tumor
0.6
1014
Normal
0.6
214
Normal
0.6
572
Normal
0.5
954
Normal
0.5
484
Normal
0.5
468
Normal
0.5
424
Normal
0.5
444
Normal
0.5
232
Normal
0.5
162
Normal
0.5
858
Normal
0.5
1042
Normal
0.5
1043
Tumor
0.5
524
Normal
0.5
672
Normal
0.5
966
Normal
0.5
666
Normal
0.5
384
Normal
0.5
546
Normal
0.5
958
Normal
0.5
716
Normal
0.5
386
Normal
0.4
913
Tumor
0.4
558
Normal
0.4
141
Tumor
0.4
494
Normal
0.4
278
Normal
0.4
446
Normal
0.4
272
Normal
0.4
228
Normal
0.4
944
Normal
0.4
686
Normal
0.4
114
Normal
0.4
126
Normal
0.4
814
Normal
0.4
161
Tumor
0.3
481
Tumor
0.3
912
Normal
0.3
937
Tumor
0.3
513
Tumor
0.3
368
Normal
0.3
957
Tumor
0.3
224
Normal
0.3
192
Normal
0.3
286
Normal
0.3
926
Normal
0.3
191
Tumor
0.3
195
Tumor
0.3
777
Tumor
0.3
534
Normal
0.3
364
Normal
0.3
297
Tumor
0.3
785
Tumor
0.3
861
Tumor
0.3
124
Normal
0.2
878
Normal
0.2
786
Normal
0.2
1022
Normal
0.2
554
Normal
0.2
365
Tumor
0.2
268
Normal
0.2
698
Normal
0.2
953
Tumor
0.2
443
Tumor
0.2
571
Tumor
0.2
538
Normal
0.2
361
Tumor
0.2
478
Normal
0.2
223
Tumor
0.2
695
Tumor
0.2
362
Normal
0.1
1041
Tumor
0.1
187
Tumor
0.1
852
Normal
0.1
778
Normal
0.1
125
Tumor
0.1
352
Normal
0.1
284
Normal
0.1
528
Normal
0.1
414
Normal
0.0
366
Normal
0.0
328
Normal
0.0
536
Normal
0.0
416
Normal
0.0
492
Normal
0.0
514
Normal
0.0
518
Normal
0.0
516
Normal
0.0
447
Tumor
-0.1
136
Normal
-0.1
915
Tumor
-0.1
978
Normal
-0.2
135
Tumor
-0.2
938
Normal
-0.2
983
Tumor
-0.2
212
Normal
-0.2
967
Tumor
-0.2
477
Tumor
-0.2
472
Normal
-0.2
636
Normal
-0.2
868
Normal
-0.3
436
Normal
-0.3
341
Tumor
-0.3
663
Tumor
-0.3
461
Tumor
-0.3
963
Tumor
-0.3
1015
Tumor
-0.3
112
Tumor
-0.4
277
Tumor
-0.4
491
Tumor
-0.4
422
Normal
-0.4
824
Normal
-0.4
916
Normal
-0.4
1046
Normal
-0.4
545
Tumor
-0.4
952
Normal
-0.4
434
Normal
-0.4
455
Tumor
-0.4
865
Tumor
-0.5
877
Tumor
-0.5
535
Tumor
-0.5
881
Tumor
-0.5
188
Normal
-0.5
497
Tumor
-0.6
332
Normal
-0.6
1028
Normal
-0.6
113
Tumor
-0.6
415
Tumor
-0.6
851
Tumor
-0.6
956
Normal
-0.7
363
Tumor
-0.7
383
Tumor
-0.7
976
Normal
-0.7
344
Normal
-0.7
517
Tumor
-0.7
537
Tumor
-0.7
943
Tumor
-0.7
618
Normal
-0.7
258
Normal
-0.7
421
Tumor
-0.8
385
Tumor
-0.8
1025
Tumor
-0.8
138
Normal
-0.8
1013
Tumor
-0.8
467
Tumor
-0.8
213
Tumor
-0.8
563
Tumor
-0.8
955
Tumor
-0.8
697
Tumor
-0.8
367
Tumor
-0.9
312
Normal
-0.9
426
Normal
-0.9
391
Tumor
-0.9
131
Tumor
-0.9
1045
Tumor
-0.9
526
Normal
-0.9
327
Tumor
-0.9
257
Tumor
-0.9
553
Tumor
-0.9
1031
Tumor
-0.9
665
Tumor
-0.9
533
Tumor
-0.9
388
Normal
-1.0
743
Tumor
-1.0
331
Tumor
-1.0
641
Tumor
-1.0
857
Tumor
-1.0
483
Tumor
-1.0
343
Tumor
-1.0
137
Tumor
-1.0
186
Normal
-1.0
662
Normal
-1.0
147
Tumor
-1.0
464
Normal
-1.1
393
Tumor
-1.1
474
Normal
-1.2
218
Normal
-1.2
433
Tumor
-1.2
427
Tumor
-1.2
715
Tumor
-1.2
283
Tumor
-1.2
394
Normal
-1.2
375
Tumor
-1.2
413
Tumor
-1.2
412
Normal
-1.2
671
Tumor
-1.2
351
Tumor
-1.2
285
Tumor
-1.3
211
Tumor
-1.3
217
Tumor
-1.3
713
Tumor
-1.3
527
Tumor
-1.3
311
Tumor
-1.3
817
Tumor
-1.3
723
Tumor
-1.3
965
Tumor
-1.3
975
Tumor
-1.3
396
Normal
-1.3
741
Tumor
-1.3
432
Normal
-1.3
271
Tumor
-1.3
493
Tumor
-1.4
616
Normal
-1.4
451
Tumor
-1.4
738
Normal
-1.4
463
Tumor
-1.4
615
Tumor
-1.4
722
Normal
-1.4
221
Tumor
-1.4
411
Tumor
-1.4
128
Normal
-1.4
127
Tumor
-1.5
661
Tumor
-1.5
171
Tumor
-1.5
635
Tumor
-1.5
863
Tumor
-1.5
525
Tumor
-1.5
737
Tumor
-1.6
185
Tumor
-1.6
874
Normal
-1.6
574
Normal
-1.6
471
Tumor
-1.6
628
Normal
-1.6
925
Tumor
-1.7
864
Normal
-1.7
911
Tumor
-1.7
816
Normal
-1.7
473
Tumor
-1.7
721
Tumor
-1.7
617
Tumor
-1.7
387
Tumor
-1.7
123
Tumor
-1.7
395
Tumor
-1.7
568
Normal
-1.7
685
Tumor
-1.7
515
Tumor
-1.7
231
Tumor
-1.7
873
Tumor
-1.8
431
Tumor
-1.8
425
Tumor
-1.8
921
Tumor
-1.8
815
Tumor
-1.8
924
Normal
-1.9
867
Tumor
-1.9
435
Tumor
-1.9
557
Tumor
-1.9
823
Tumor
-1.9
627
Tumor
-2.0
724
Normal
-2.0
1021
Tumor
-2.0
567
Tumor
-2.0
951
Tumor
-2.1
923
Tumor
-2.1
918
Normal
-2.1
917
Tumor
-2.3
573
Tumor
-2.4
Show allShow less
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.