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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 interactive Survival Scatter plot allows for the cutoff to be changed by dragging the vertical line or by entering a cutoff value in the square labeled "Survival analysis". Under the Survival Scatter plot the p-score landscape is shown together with the difference in median between survival time for patients who have died with respect to high and low expression. This is intended to aid the user in exploring custom cutoffs.
Individual patient data is displayed in an interactive plot 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).
THY1 is prognostic, high expression is unfavourable in glioma
Stage:
Survival analysis
Current cut off: Best expression cut offi
Based on the FPKM value of each gene, we classified the patients into two groups and examined their prognoses. In the analysis, we excluded genes with low expression, i.e., those with a median expression among samples less than FPKM 1. The prognosis of each group of patients was examined by Kaplan-Meier survival estimators, and the survival outcomes of the two groups were compared by log-rank tests. To choose the best FPKM cut-offs for grouping the patients most significantly, all FPKM values from the 20th to 80th percentiles were used to group the patients, significant differences in the survival outcomes of the groups were examined and the value yielding the lowest log-rank P value is selected.
: 49.86
Median expression: N/A
Median follow up time: N/A P scorei
Log-rank P value for Kaplan-Meier plot showing results from analysis of correlation between mRNA expression level and patient survival.
N/A 3-year survival highi
5-year survival for patients with higher expression than the expression cutoff.
For melanoma and glioma, 3-year survival is shown.
N/A 3-year survival lowi
5-year survival for patients with lower expression than the expression cutoff.
For melanoma and glioma, 3-year survival is shown.
N/A
TCGA RNA samplesi
RNA-seq data is reported as median FPKM (number Fragments Per Kilobase of exon per Million reads), generated by the The Cancer Genome Atlas (TCGA) .
Normal distribution across the dataset is visualized with box plots, shown as median and 25th and 75th percentiles. Points are displayed as outliers if they are above or below 1.5 times the interquartile range. FPKM values of the individual samples are presented next to the box plot.
Average FPKM
42.3
Number of samples
153
Samples
Sample
Description
FPKM
TCGA-06-0644-01A
71 years, male, black or african american, dead, 384 days
122.2
TCGA-06-5412-01A
78 years, female, white, dead, 138 days
96.2
TCGA-27-2523-01A
63 years, male, white, dead, 489 days
94.8
TCGA-06-0745-01A
59 years, male, white, dead, 239 days
92.2
TCGA-27-2524-01A
56 years, male, white, dead, 231 days
91.7
TCGA-06-5413-01A
67 years, male, white, alive, 268 days
91.3
TCGA-27-1837-01A
36 years, male, white, dead, 427 days
90.5
TCGA-26-5135-01A
72 years, female, white, dead, 270 days
87.9
TCGA-32-1980-01A
72 years, male, white, dead, 36 days
87.0
TCGA-19-2629-01A
60 years, male, white, dead, 737 days
87.0
TCGA-06-5411-01A
51 years, male, white, dead, 254 days
83.9
TCGA-02-0055-01A
62 years, female, white, dead, 76 days
83.2
TCGA-06-2558-01A
75 years, female, white, dead, 380 days
82.7
TCGA-06-2562-01A
81 years, male, white, dead, 382 days
80.9
TCGA-06-0130-01A
54 years, male, white, dead, 394 days
74.4
TCGA-06-0750-01A
43 years, male, white, dead, 28 days
71.9
TCGA-06-0138-01A
43 years, male, white, dead, 737 days
70.5
TCGA-02-0047-01A
78 years, male, white, dead, 448 days
68.9
TCGA-32-4213-01A
47 years, female, white, alive, 604 days
68.7
TCGA-06-0686-01A
53 years, male, white, dead, 432 days
66.7
TCGA-06-0646-01A
61 years, male, white, dead, 175 days
66.2
TCGA-06-0132-01A
49 years, male, white, dead, 771 days
65.5
TCGA-14-1825-01A
70 years, male, white, dead, 232 days
65.0
TCGA-28-5215-01A
62 years, female, white, dead, 335 days
64.5
TCGA-28-1753-01A
53 years, male, white, alive, 37 days
63.8
TCGA-27-2519-01A
48 years, male, white, dead, 550 days
62.8
TCGA-32-1982-01A
76 years, female, white, dead, 142 days
62.4
TCGA-27-1832-01A
59 years, female, white, dead, 300 days
62.3
TCGA-26-5133-01A
59 years, male, white, alive, 452 days
62.2
TCGA-26-5134-01A
74 years, male, white, alive, 167 days
62.0
TCGA-41-5651-01A
59 years, female, black or african american, dead, 460 days
61.9
TCGA-06-0157-01A
63 years, female, white, dead, 97 days
60.5
TCGA-27-1830-01A
57 years, male, white, dead, 154 days
60.4
TCGA-27-2521-01A
34 years, male, white, dead, 510 days
59.9
TCGA-14-1829-01A
57 years, male, black or african american, alive, 218 days
59.8
TCGA-28-5218-01A
63 years, male, white, dead, 157 days
58.8
TCGA-12-5295-01A
60 years, female, white, dead, 454 days
58.6
TCGA-06-0238-01A
46 years, male, white, dead, 405 days
58.4
TCGA-06-5418-01A
75 years, female, white, dead, 83 days
58.3
TCGA-26-5136-01B
78 years, female, white, dead, 577 days
57.2
TCGA-06-5856-01A
58 years, male, white, dead, 114 days
55.9
TCGA-06-0645-01A
56 years, female, white, dead, 175 days
54.0
TCGA-28-2514-01A
45 years, male, asian, alive, 160 days
53.7
TCGA-06-0139-01A
40 years, male, white, dead, 362 days
53.0
TCGA-14-0781-01B
49 years, male, black or african american, dead, 29 days
52.5
TCGA-06-5416-01A
23 years, female, white, alive, 204 days
52.5
TCGA-28-5204-01A
72 years, male, white, dead, 454 days
51.8
TCGA-12-3650-01A
46 years, male, white, dead, 333 days
51.4
TCGA-06-2559-01A
83 years, male, white, dead, 150 days
51.3
TCGA-06-0749-01A
50 years, male, black or african american, dead, 82 days
51.2
TCGA-02-2483-01A
43 years, male, asian, alive, 466 days
50.9
TCGA-06-0156-01A
57 years, male, white, dead, 178 days
50.2
TCGA-19-2624-01A
51 years, male, white, dead, 5 days
50.1
TCGA-06-0878-01A
74 years, male, white, alive, 218 days
49.6
TCGA-06-0178-01A
39 years, male, white, dead, 2681 days
49.1
TCGA-06-2570-01A
21 years, female, white, alive, 958 days
48.4
TCGA-28-5216-01A
52 years, male, white, alive, 415 days
46.7
TCGA-06-2563-01A
72 years, female, white, alive, 932 days
46.7
TCGA-12-0821-01A
62 years, male, white, dead, 323 days
45.8
TCGA-16-1045-01B
49 years, female, white, dead, 883 days
45.7
TCGA-28-5209-01A
66 years, female, white, alive, 77 days
45.3
TCGA-12-0618-01A
49 years, male, white, dead, 395 days
44.4
TCGA-28-2513-01A
69 years, female, white, alive, 222 days
44.0
TCGA-12-5299-01A
56 years, female, white, dead, 98 days
43.8
TCGA-41-2572-01A
67 years, male, white, dead, 406 days
43.6
TCGA-76-4927-01A
58 years, male, white, dead, 535 days
43.4
TCGA-06-0649-01B
73 years, female, black or african american, dead, 64 days
43.3
TCGA-76-4928-01B
85 years, female, white, dead, 94 days
42.2
TCGA-27-2528-01A
62 years, male, white, dead, 480 days
41.3
TCGA-28-2509-01A
77 years, female, white, alive, 145 days
40.4
TCGA-19-4065-01A
36 years, male, white, alive, 214 days
40.2
TCGA-06-0174-01A
54 years, male, white, dead, 98 days
40.2
TCGA-28-5207-01A
71 years, male, white, dead, 343 days
39.9
TCGA-06-0184-01A
63 years, male, white, dead, 2126 days
39.5
TCGA-06-0187-01A
69 years, male, white, dead, 828 days
39.3
TCGA-27-2526-01A
79 years, female, white, dead, 87 days
38.7
TCGA-41-4097-01A
63 years, female, white, dead, 6 days
38.7
TCGA-06-0168-01A
59 years, female, white, dead, 598 days
37.7
TCGA-06-0210-01A
72 years, female, white, dead, 225 days
37.2
TCGA-06-0141-01A
62 years, male, white, dead, 313 days
37.1
TCGA-32-2632-01A
80 years, male, white, dead, 269 days
36.4
TCGA-41-2571-01A
89 years, male, white, dead, 26 days
35.8
TCGA-27-1835-01A
53 years, female, white, dead, 648 days
35.7
TCGA-19-1390-01A
63 years, female, white, dead, 772 days
35.6
TCGA-15-0742-01A
65 years, male, white, dead, 419 days
35.4
TCGA-06-5410-01A
72 years, female, white, dead, 108 days
35.3
TCGA-15-1444-01A
21 years, male, white, dead, 1537 days
35.0
TCGA-32-2616-01A
48 years, female, white, dead, 224 days
34.8
TCGA-28-5213-01A
72 years, male, white, alive, 951 days
34.4
TCGA-12-0616-01A
36 years, female, white, dead, 448 days
34.4
TCGA-41-3915-01A
48 years, male, white, dead, 360 days
34.2
TCGA-14-0871-01A
75 years, female, white, dead, 880 days
33.0
TCGA-06-0743-01A
69 years, male, white, dead, 803 days
31.9
TCGA-06-5858-01A
45 years, female, white, alive, 187 days
31.9
TCGA-06-5408-01A
54 years, female, white, dead, 357 days
31.7
TCGA-14-0817-01A
69 years, female, white, dead, 164 days
31.6
TCGA-06-0190-01A
62 years, male, white, dead, 317 days
31.2
TCGA-06-2569-01A
24 years, female, black or african american, alive, 13 days
30.9
TCGA-32-2638-01A
67 years, male, white, dead, 766 days
30.2
TCGA-12-1597-01B
62 years, female, white, dead, 675 days
30.1
TCGA-28-5208-01A
52 years, male, white, dead, 544 days
30.0
TCGA-06-2564-01A
50 years, male, white, alive, 181 days
29.1
TCGA-27-1831-01A
66 years, male, white, dead, 505 days
28.9
TCGA-06-2561-01A
53 years, female, white, dead, 537 days
28.7
TCGA-26-5139-01A
65 years, female, white, alive, 48 days
28.2
TCGA-08-0386-01A
74 years, male, white, dead, 548 days
28.0
TCGA-16-0846-01A
85 years, male, white, dead, 119 days
27.1
TCGA-32-2634-01A
82 years, male, white, alive, 693 days
27.0
TCGA-12-0619-01A
60 years, male, white, dead, 1062 days
26.4
TCGA-06-0158-01A
73 years, male, white, dead, 329 days
26.1
TCGA-76-4931-01A
70 years, female, white, dead, 279 days
25.7
TCGA-76-4929-01A
76 years, female, white, dead, 111 days
25.7
TCGA-06-0219-01A
67 years, male, white, dead, 22 days
25.1
TCGA-06-0747-01A
53 years, male, white, dead, 82 days
24.8
TCGA-06-0125-01A
63 years, female, white, dead, 1448 days
24.3
TCGA-06-5414-01A
61 years, male, white, alive, 273 days
23.9
TCGA-19-5960-01A
56 years, male, white, dead, 455 days
23.7
TCGA-06-0211-01B
47 years, male, white, dead, 360 days
23.6
TCGA-06-2567-01A
65 years, male, white, dead, 133 days
23.5
TCGA-26-5132-01A
74 years, male, white, alive, 286 days
23.2
TCGA-76-4925-01A
76 years, male, white, dead, 146 days
23.1
TCGA-06-0129-01A
30 years, male, asian, dead, 1024 days
23.0
TCGA-26-1442-01A
43 years, male, white, alive, 953 days
23.0
TCGA-06-2565-01A
59 years, male, asian, dead, 506 days
22.7
TCGA-19-2619-01A
55 years, female, black or african american, alive, 294 days
21.7
TCGA-06-0744-01A
67 years, male, white, dead, 1426 days
21.2
TCGA-28-5220-01A
67 years, male, white, dead, 388 days
20.6
TCGA-14-0790-01B
64 years, female, white, dead, 419 days
20.5
TCGA-14-0787-01A
69 years, male, asian, dead, 68 days
19.6
TCGA-02-2485-01A
53 years, male, black or african american, alive, 470 days
19.4
TCGA-06-2557-01A
76 years, male, black or african american, dead, 33 days
19.4
TCGA-28-1747-01C
44 years, male, white, dead, 77 days
19.2
TCGA-06-5859-01A
63 years, male, white, alive, 139 days
18.1
TCGA-06-0882-01A
30 years, male, white, dead, 632 days
17.7
TCGA-19-1787-01B
49 years, male, white, dead, 385 days
17.2
TCGA-14-1823-01A
58 years, female, white, dead, 543 days
17.0
TCGA-27-1834-01A
56 years, male, white, dead, 1233 days
16.3
TCGA-32-5222-01A
66 years, male, white, dead, 585 days
16.3
TCGA-76-4932-01A
50 years, female, white, dead, 1458 days
16.2
TCGA-32-1970-01A
59 years, male, white, dead, 468 days
15.7
TCGA-14-1034-01A
60 years, female, dead, 485 days
15.1
TCGA-06-5417-01A
45 years, female, white, alive, 155 days
14.6
TCGA-14-0789-01A
54 years, male, white, dead, 342 days
14.1
TCGA-19-2625-01A
76 years, female, white, dead, 124 days
13.5
TCGA-02-2486-01A
64 years, male, white, dead, 618 days
13.1
TCGA-76-4926-01B
68 years, male, white, dead, 138 days
12.7
TCGA-28-2499-01A
59 years, male, white, dead, 95 days
12.5
TCGA-06-1804-01A
81 years, female, white, dead, 414 days
12.4
TCGA-14-2554-01A
52 years, female, white, dead, 532 days
10.8
TCGA-32-2615-01A
62 years, male, white, dead, 485 days
10.7
TCGA-19-2620-01A
70 years, male, white, dead, 148 days
8.1
TCGA-12-3652-01A
60 years, male, white, dead, 1062 days
7.7
TCGA-12-3653-01A
34 years, female, white, dead, 442 days
5.1
Show all
GLIOMA - 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
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).
The Human Protein Atlas project is funded
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