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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
661
Tumor
1.3
917
Tumor
1.1
434
Normal
1.1
536
Normal
1.0
724
Normal
0.9
188
Normal
0.9
262
Normal
0.9
311
Tumor
0.9
224
Normal
0.8
211
Tumor
0.8
914
Normal
0.7
524
Normal
0.7
383
Tumor
0.7
268
Normal
0.7
137
Tumor
0.7
213
Tumor
0.7
978
Normal
0.7
444
Normal
0.7
455
Tumor
0.7
126
Normal
0.6
852
Normal
0.6
966
Normal
0.6
716
Normal
0.6
491
Tumor
0.6
721
Tumor
0.6
283
Tumor
0.6
217
Tumor
0.6
192
Normal
0.6
861
Tumor
0.6
362
Normal
0.6
195
Tumor
0.6
686
Normal
0.6
124
Normal
0.6
498
Normal
0.5
467
Tumor
0.5
535
Tumor
0.5
516
Normal
0.5
628
Normal
0.5
925
Tumor
0.5
814
Normal
0.5
141
Tumor
0.5
375
Tumor
0.5
478
Normal
0.5
492
Normal
0.4
778
Normal
0.4
916
Normal
0.4
538
Normal
0.4
1015
Tumor
0.4
666
Normal
0.4
384
Normal
0.4
816
Normal
0.4
284
Normal
0.4
386
Normal
0.4
461
Tumor
0.4
662
Normal
0.4
1044
Normal
0.4
954
Normal
0.4
272
Normal
0.4
563
Tumor
0.4
421
Tumor
0.4
913
Tumor
0.4
212
Normal
0.4
113
Tumor
0.4
487
Tumor
0.4
926
Normal
0.4
1028
Normal
0.3
884
Normal
0.3
1042
Normal
0.3
851
Tumor
0.3
1031
Tumor
0.3
146
Normal
0.3
191
Tumor
0.3
786
Normal
0.3
518
Normal
0.3
958
Normal
0.3
558
Normal
0.3
756
Normal
0.3
918
Normal
0.3
423
Tumor
0.3
696
Normal
0.3
391
Tumor
0.3
312
Normal
0.3
218
Normal
0.3
663
Tumor
0.3
943
Tumor
0.2
447
Tumor
0.2
366
Normal
0.2
352
Normal
0.2
114
Normal
0.2
874
Normal
0.2
387
Tumor
0.2
713
Tumor
0.2
714
Normal
0.2
857
Tumor
0.2
125
Tumor
0.2
456
Normal
0.2
956
Normal
0.2
392
Normal
0.2
111
Normal
0.2
332
Normal
0.2
474
Normal
0.2
465
Tumor
0.2
185
Tumor
0.2
466
Normal
0.2
416
Normal
0.2
573
Tumor
0.2
574
Normal
0.2
446
Normal
0.2
364
Normal
0.2
432
Normal
0.2
664
Normal
0.1
723
Tumor
0.1
882
Normal
0.1
722
Normal
0.1
468
Normal
0.1
286
Normal
0.1
385
Tumor
0.1
955
Tumor
0.1
528
Normal
0.1
1046
Normal
0.1
396
Normal
0.1
138
Normal
0.1
823
Tumor
0.1
952
Normal
0.1
424
Normal
0.1
344
Normal
0.1
514
Normal
0.1
228
Normal
0.1
343
Tumor
0.1
161
Tumor
0.1
968
Normal
0.1
755
Tumor
0.1
557
Tumor
0.1
554
Normal
0.1
976
Normal
0.1
698
Normal
0.1
984
Normal
0.1
922
Normal
0.1
957
Tumor
0.1
1026
Normal
0.1
938
Normal
0.1
963
Tumor
0.1
862
Normal
0.0
223
Tumor
0.0
1016
Normal
0.0
298
Normal
0.0
858
Normal
0.0
1045
Tumor
0.0
672
Normal
0.0
395
Tumor
0.0
367
Tumor
0.0
1022
Normal
0.0
187
Tumor
0.0
353
Tumor
0.0
777
Tumor
0.0
436
Normal
0.0
627
Tumor
0.0
924
Normal
0.0
448
Normal
0.0
728
Normal
0.0
135
Tumor
0.0
881
Tumor
0.0
142
Normal
0.0
818
Normal
0.0
1043
Tumor
0.0
258
Normal
0.0
473
Tumor
0.0
824
Normal
0.0
866
Normal
0.0
738
Normal
0.0
354
Normal
0.0
964
Normal
0.0
428
Normal
0.0
365
Tumor
0.0
494
Normal
0.0
953
Tumor
-0.1
878
Normal
-0.1
482
Normal
-0.1
944
Normal
-0.1
358
Normal
-0.1
915
Tumor
-0.1
136
Normal
-0.1
232
Normal
-0.1
257
Tumor
-0.1
472
Normal
-0.1
864
Normal
-0.1
513
Tumor
-0.1
883
Tumor
-0.1
172
Normal
-0.1
464
Normal
-0.1
526
Normal
-0.1
983
Tumor
-0.1
912
Normal
-0.1
462
Normal
-0.1
327
Tumor
-0.1
868
Normal
-0.1
564
Normal
-0.1
452
Normal
-0.1
546
Normal
-0.1
865
Tumor
-0.1
616
Normal
-0.1
361
Tumor
-0.1
433
Tumor
-0.1
128
Normal
-0.1
342
Normal
-0.1
715
Tumor
-0.1
488
Normal
-0.1
261
Tumor
-0.1
368
Normal
-0.1
975
Tumor
-0.1
214
Normal
-0.1
568
Normal
-0.1
737
Tumor
-0.1
422
Normal
-0.1
376
Normal
-0.2
493
Tumor
-0.2
911
Tumor
-0.2
937
Tumor
-0.2
394
Normal
-0.2
1013
Tumor
-0.2
744
Normal
-0.2
412
Normal
-0.2
525
Tumor
-0.2
982
Normal
-0.2
746
Normal
-0.2
815
Tumor
-0.2
697
Tumor
-0.2
297
Tumor
-0.2
328
Normal
-0.2
162
Normal
-0.2
813
Tumor
-0.2
1014
Normal
-0.2
415
Tumor
-0.2
427
Tumor
-0.2
414
Normal
-0.2
533
Tumor
-0.2
1032
Normal
-0.2
231
Tumor
-0.2
356
Normal
-0.2
867
Tumor
-0.2
572
Normal
-0.3
341
Tumor
-0.3
817
Tumor
-0.3
145
Tumor
-0.3
132
Normal
-0.3
617
Tumor
-0.3
363
Tumor
-0.3
741
Tumor
-0.3
148
Normal
-0.3
665
Tumor
-0.3
534
Normal
-0.3
951
Tumor
-0.3
695
Tumor
-0.3
647
Tumor
-0.3
285
Tumor
-0.3
426
Normal
-0.3
742
Normal
-0.3
186
Normal
-0.3
222
Normal
-0.3
413
Tumor
-0.3
278
Normal
-0.4
355
Tumor
-0.4
388
Normal
-0.4
484
Normal
-0.4
648
Normal
-0.4
451
Tumor
-0.4
471
Tumor
-0.4
923
Tumor
-0.4
636
Normal
-0.4
497
Tumor
-0.4
147
Tumor
-0.4
313
Tumor
-0.4
196
Normal
-0.4
553
Tumor
-0.4
671
Tumor
-0.4
1025
Tumor
-0.4
642
Normal
-0.5
863
Tumor
-0.5
545
Tumor
-0.5
227
Tumor
-0.5
727
Tumor
-0.5
877
Tumor
-0.5
1041
Tumor
-0.5
481
Tumor
-0.5
785
Tumor
-0.5
967
Tumor
-0.5
1027
Tumor
-0.5
523
Tumor
-0.6
873
Tumor
-0.6
618
Normal
-0.6
267
Tumor
-0.7
685
Tumor
-0.7
431
Tumor
-0.7
127
Tumor
-0.7
745
Tumor
-0.7
641
Tumor
-0.7
463
Tumor
-0.7
977
Tumor
-0.7
443
Tumor
-0.7
331
Tumor
-0.8
271
Tumor
-0.8
483
Tumor
-0.8
314
Normal
-0.8
615
Tumor
-0.8
411
Tumor
-0.8
537
Tumor
-0.8
1021
Tumor
-0.8
351
Tumor
-0.8
277
Tumor
-0.8
921
Tumor
-0.9
965
Tumor
-0.9
571
Tumor
-0.9
527
Tumor
-0.9
515
Tumor
-0.9
112
Tumor
-0.9
477
Tumor
-0.9
567
Tumor
-1.0
981
Tumor
-1.0
517
Tumor
-1.0
171
Tumor
-1.1
221
Tumor
-1.1
445
Tumor
-1.1
635
Tumor
-1.1
123
Tumor
-1.1
357
Tumor
-1.2
425
Tumor
-1.3
131
Tumor
-1.3
393
Tumor
-1.3
435
Tumor
-1.5
743
Tumor
-2.3
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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.