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