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