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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
113
Tumor
2.1
395
Tumor
2.0
145
Tumor
1.6
937
Tumor
1.5
1015
Tumor
1.4
191
Tumor
1.4
627
Tumor
1.2
467
Tumor
1.2
557
Tumor
1.2
375
Tumor
1.1
487
Tumor
1.0
823
Tumor
1.0
135
Tumor
0.9
353
Tumor
0.9
327
Tumor
0.9
755
Tumor
0.8
451
Tumor
0.8
443
Tumor
0.8
112
Tumor
0.8
124
Normal
0.7
867
Tumor
0.7
187
Tumor
0.7
524
Normal
0.7
851
Tumor
0.7
217
Tumor
0.7
563
Tumor
0.7
537
Tumor
0.7
431
Tumor
0.6
195
Tumor
0.6
267
Tumor
0.6
223
Tumor
0.6
1028
Normal
0.6
423
Tumor
0.6
421
Tumor
0.6
525
Tumor
0.6
778
Normal
0.6
526
Normal
0.5
665
Tumor
0.5
741
Tumor
0.5
721
Tumor
0.5
137
Tumor
0.5
332
Normal
0.5
745
Tumor
0.5
218
Normal
0.5
538
Normal
0.4
392
Normal
0.4
125
Tumor
0.4
383
Tumor
0.4
468
Normal
0.4
857
Tumor
0.4
477
Tumor
0.4
925
Tumor
0.4
954
Normal
0.3
861
Tumor
0.3
427
Tumor
0.3
953
Tumor
0.3
384
Normal
0.3
498
Normal
0.3
744
Normal
0.3
636
Normal
0.3
344
Normal
0.3
368
Normal
0.3
981
Tumor
0.3
465
Tumor
0.3
696
Normal
0.3
558
Normal
0.3
1043
Tumor
0.2
114
Normal
0.2
224
Normal
0.2
376
Normal
0.2
452
Normal
0.2
141
Tumor
0.2
554
Normal
0.2
488
Normal
0.2
1045
Tumor
0.2
434
Normal
0.2
361
Tumor
0.2
873
Tumor
0.2
262
Normal
0.2
686
Normal
0.2
365
Tumor
0.2
492
Normal
0.2
286
Normal
0.2
352
Normal
0.2
724
Normal
0.1
642
Normal
0.1
672
Normal
0.1
911
Tumor
0.1
444
Normal
0.1
142
Normal
0.1
695
Tumor
0.1
567
Tumor
0.0
426
Normal
0.0
396
Normal
0.0
394
Normal
0.0
574
Normal
0.0
448
Normal
0.0
536
Normal
0.0
433
Tumor
0.0
354
Normal
0.0
445
Tumor
0.0
1014
Normal
0.0
685
Tumor
0.0
617
Tumor
0.0
388
Normal
0.0
858
Normal
0.0
232
Normal
-0.1
268
Normal
-0.1
432
Normal
-0.1
662
Normal
-0.1
342
Normal
-0.1
185
Tumor
-0.1
723
Tumor
-0.1
922
Normal
-0.1
615
Tumor
-0.1
186
Normal
-0.1
128
Normal
-0.1
952
Normal
-0.1
214
Normal
-0.1
221
Tumor
-0.1
915
Tumor
-0.1
414
Normal
-0.1
698
Normal
-0.1
126
Normal
-0.1
196
Normal
-0.1
1044
Normal
-0.1
478
Normal
-0.1
111
Normal
-0.1
968
Normal
-0.1
1016
Normal
-0.1
386
Normal
-0.1
146
Normal
-0.1
573
Tumor
-0.2
228
Normal
-0.2
568
Normal
-0.2
366
Normal
-0.2
883
Tumor
-0.2
213
Tumor
-0.2
172
Normal
-0.2
528
Normal
-0.2
466
Normal
-0.2
222
Normal
-0.2
742
Normal
-0.2
572
Normal
-0.2
298
Normal
-0.2
818
Normal
-0.2
161
Tumor
-0.2
756
Normal
-0.2
852
Normal
-0.2
436
Normal
-0.2
358
Normal
-0.2
456
Normal
-0.2
188
Normal
-0.2
816
Normal
-0.2
814
Normal
-0.2
446
Normal
-0.2
464
Normal
-0.2
571
Tumor
-0.2
447
Tumor
-0.2
231
Tumor
-0.2
824
Normal
-0.2
546
Normal
-0.2
424
Normal
-0.2
1046
Normal
-0.2
564
Normal
-0.2
713
Tumor
-0.3
722
Normal
-0.3
422
Normal
-0.3
738
Normal
-0.3
618
Normal
-0.3
966
Normal
-0.3
984
Normal
-0.3
553
Tumor
-0.3
284
Normal
-0.3
868
Normal
-0.3
518
Normal
-0.3
258
Normal
-0.3
148
Normal
-0.3
192
Normal
-0.3
817
Tumor
-0.3
866
Normal
-0.3
666
Normal
-0.3
138
Normal
-0.3
461
Tumor
-0.3
343
Tumor
-0.3
285
Tumor
-0.3
944
Normal
-0.3
483
Tumor
-0.3
362
Normal
-0.3
491
Tumor
-0.3
132
Normal
-0.3
425
Tumor
-0.3
1041
Tumor
-0.3
746
Normal
-0.3
387
Tumor
-0.3
311
Tumor
-0.3
878
Normal
-0.3
278
Normal
-0.3
978
Normal
-0.3
716
Normal
-0.4
123
Tumor
-0.4
786
Normal
-0.4
714
Normal
-0.4
314
Normal
-0.4
415
Tumor
-0.4
162
Normal
-0.4
616
Normal
-0.4
534
Normal
-0.4
914
Normal
-0.4
664
Normal
-0.4
982
Normal
-0.4
882
Normal
-0.4
912
Normal
-0.4
297
Tumor
-0.4
963
Tumor
-0.4
874
Normal
-0.4
648
Normal
-0.4
514
Normal
-0.4
628
Normal
-0.4
364
Normal
-0.4
462
Normal
-0.4
957
Tumor
-0.5
428
Normal
-0.5
975
Tumor
-0.5
312
Normal
-0.5
1026
Normal
-0.5
884
Normal
-0.5
482
Normal
-0.5
391
Tumor
-0.5
494
Normal
-0.5
924
Normal
-0.5
926
Normal
-0.5
272
Normal
-0.5
955
Tumor
-0.5
916
Normal
-0.5
864
Normal
-0.5
328
Normal
-0.5
913
Tumor
-0.5
728
Normal
-0.5
1021
Tumor
-0.5
1022
Normal
-0.5
484
Normal
-0.5
471
Tumor
-0.5
938
Normal
-0.5
416
Normal
-0.5
257
Tumor
-0.5
956
Normal
-0.6
917
Tumor
-0.6
493
Tumor
-0.6
412
Normal
-0.6
923
Tumor
-0.6
356
Normal
-0.6
136
Normal
-0.6
212
Normal
-0.6
641
Tumor
-0.6
517
Tumor
-0.6
976
Normal
-0.6
964
Normal
-0.6
393
Tumor
-0.6
147
Tumor
-0.6
862
Normal
-0.6
663
Tumor
-0.6
918
Normal
-0.6
455
Tumor
-0.6
127
Tumor
-0.6
277
Tumor
-0.7
785
Tumor
-0.7
943
Tumor
-0.7
813
Tumor
-0.7
697
Tumor
-0.7
535
Tumor
-0.7
533
Tumor
-0.7
341
Tumor
-0.7
227
Tumor
-0.7
261
Tumor
-0.7
313
Tumor
-0.7
355
Tumor
-0.7
715
Tumor
-0.7
497
Tumor
-0.7
367
Tumor
-0.7
661
Tumor
-0.7
472
Normal
-0.7
967
Tumor
-0.7
385
Tumor
-0.7
435
Tumor
-0.7
1031
Tumor
-0.7
474
Normal
-0.8
977
Tumor
-0.8
1032
Normal
-0.8
413
Tumor
-0.8
271
Tumor
-0.8
516
Normal
-0.8
951
Tumor
-0.8
1013
Tumor
-0.8
865
Tumor
-0.9
815
Tumor
-0.9
881
Tumor
-0.9
958
Normal
-0.9
863
Tumor
-0.9
411
Tumor
-1.0
515
Tumor
-1.0
211
Tumor
-1.0
1025
Tumor
-1.0
463
Tumor
-1.0
513
Tumor
-1.0
523
Tumor
-1.1
357
Tumor
-1.1
1042
Normal
-1.1
481
Tumor
-1.1
635
Tumor
-1.1
527
Tumor
-1.1
331
Tumor
-1.1
777
Tumor
-1.1
363
Tumor
-1.2
983
Tumor
-1.2
131
Tumor
-1.2
171
Tumor
-1.2
647
Tumor
-1.2
727
Tumor
-1.2
743
Tumor
-1.2
283
Tumor
-1.3
1027
Tumor
-1.3
671
Tumor
-1.3
921
Tumor
-1.4
737
Tumor
-1.5
351
Tumor
-1.5
877
Tumor
-1.6
545
Tumor
-1.6
473
Tumor
-1.8
965
Tumor
-1.9
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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.