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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.
OVARY SEROUS CYSTADENOCARCINOMA - Protein relative expression (CPTAC)
Number of samples
108
Samples
Sample ID
Sample type
nRPX
d38f40fb-dd78-43b2-8b7b-4b6977_D2
Tumor
2.5
e7b656bf-3c34-4ba1-bdf3-c7eefe_D2
Tumor
2.3
0c87932d-b6fd-4eb5-b86a-a34d07_D2
Tumor
1.9
161317f3-1a39-438e-af45-cd2502_D2
Tumor
1.6
1c9145ad-1981-4871-aa7e-8b11de_D2
Tumor
1.5
bd266bdd-12e4-42cb-9c49-911bfc_D2
Tumor
1.5
2b4ce90c-8036-4207-ac3e-54a76f_D2
Tumor
1.4
256ac9f5-1e19-44b4-92fb-fef3fc_D2
Tumor
1.1
1de8d3d8-fc0e-4be0-8aa7-127c7b_D2
Tumor
1.1
347e379b-77c0-4dd3-aa25-18c9d1_D2
Tumor
1.1
62f5840e-6cd7-4200-b651-645e53_D2
Tumor
1.0
994f9b8e-46cb-413f-8ec8-2c2fed_D2
Normal
1.0
a8853382-b726-4ce8-98d5-ca89df_D2
Tumor
1.0
e9d416e7-f661-400a-896e-388545_D2
Tumor
1.0
1db5574d-aca7-403c-8100-6e705f_D2
Normal
0.9
3d3e1888-d67e-4c69-ba83-112d0f_D2
Tumor
0.9
927f0958-db5a-4bc5-92b7-2a3695_D2
Tumor
0.9
7069e990-4a4e-4984-a66d-4d835a_D2
Tumor
0.9
092af714-b97a-457c-b0e9-8c20e8_D2
Normal
0.9
285fed94-1495-448e-879b-b55de9_D2
Tumor
0.8
9a7a86d3-bbf2-4d36-941d-c75c03_D1_D2
Tumor
0.8
3a380577-c134-47ba-a1ce-988d7c_D2
Tumor
0.8
9b90eb78-2f50-4aeb-b010-d642f9_D2
Tumor
0.8
7c7ce2d7-6c8a-424e-8e6c-d14ad1_D2
Tumor
0.8
0745488e-0bfb-4d1f-8228-dedf76_D1_D2
Normal
0.8
eb0a53df-7620-4024-8d2d-051142_D2
Tumor
0.8
50997c44-1c8b-4d34-b535-4a6cc2_D2
Tumor
0.8
27f3ca2d-a86f-479d-8e7e-5307c7_D2
Tumor
0.7
08296da7-70ea-44df-8646-09f2cc_D2
Tumor
0.7
1772e913-f62e-446a-8cf3-720348_D2
Tumor
0.7
76e77c6b-c80e-4391-bdbb-e1dcea_D2
Tumor
0.7
f6c215ea-5381-4521-bb61-be8e97_D2
Tumor
0.6
28d0abdb-f682-4bd3-9425-a9c508_D2
Tumor
0.6
91b287fd-eadb-442d-abcd-20b741_D2
Tumor
0.6
e3ebe010-cd31-4b5d-8fcb-b7103b_D2
Tumor
0.6
318d53c3-216b-4de1-a098-77d6dd_D2
Tumor
0.5
340a3769-3031-41ae-bb08-a2f696_D2
Normal
0.5
8d78194e-fbef-4819-a7b5-b73ae9_D2
Tumor
0.5
5c3971ee-87c7-4dff-b66e-f18892_D2
Tumor
0.5
79b60f32-6cca-4cb6-9a1e-22a3ac_D2
Tumor
0.5
2563cb02-d58a-4286-8634-7502cd_D2
Tumor
0.5
8ed739dd-ae0f-4881-971a-db3cf4_D1_D2
Normal
0.5
3e746bea-ed68-40e6-b348-6ddf08_D2
Normal
0.5
4ccb249a-6722-491e-97e9-e3b4e7_D2
Tumor
0.5
41d0619e-b299-42e2-ac32-29e784_D2
Tumor
0.5
c17b0ff9-9057-4848-a0cc-abb25f_D2
Tumor
0.4
3946a96c-e0ae-442f-83b4-a9350e_D2
Tumor
0.4
2115808b-6a0d-49bc-a8d7-b83bde_D2
Tumor
0.4
d4791079-c826-4fc7-9d9b-ee20ba_D2
Tumor
0.4
80873a0c-1f40-4d51-bab1-3f2071_D2
Tumor
0.4
1b2ab076-c72f-4bbe-b9f9-657d24_D2
Tumor
0.4
69d552be-7cb2-4bb4-b602-a27b3e_D2
Tumor
0.4
a65d8e76-640f-4341-a561-afbb57_D2
Normal
0.4
a3a26070-fb84-406a-8280-d555e6_D2
Normal
0.3
6530147a-efe9-4df6-ac2f-03ece3_D2
Tumor
0.3
1556af7e-c2ae-4fce-9aae-87c459_D1_D2
Normal
0.3
a583d3ff-8165-43e9-b764-23b7ef_D1_D2
Normal
0.3
d109a3c0-350e-47f5-bda0-61899c_D2
Tumor
0.3
2b73e01c-347a-4dae-a71d-752aeb_D2
Normal
0.3
52c064a7-78d9-4a1a-85b4-27c6d1_D2
Tumor
0.3
3490835c-c004-45ed-91f3-7c206f_D2
Tumor
0.3
46c73531-f531-4ec3-97fe-b39d9d_D2
Tumor
0.3
51a4ce2f-4166-4c6b-a7e0-942d0a_D2
Tumor
0.3
7edfd606-4bee-4529-9fec-1ca7f0_D2
Normal
0.3
6319b36b-533c-4e86-8e12-80552e_D3
Tumor
0.3
7d953d1d-84b6-4ecd-b1d7-1ed865_D2
Tumor
0.3
1abbcb28-f221-4cd4-8c01-37b9bb_D1_D2
Normal
0.3
685ec3c2-e67a-40d3-9eb3-aa01c9_D1_D2
Normal
0.3
15524912-685a-47ce-a824-567848_D2
Tumor
0.2
e23eb014-69c1-460a-b9d4-9786c8_D2
Normal
0.2
fe83e13f-9754-403b-8f74-d6caf8_D2
Tumor
0.2
2f901c90-617e-46da-9fac-d68369_D2
Tumor
0.2
8234f8ea-bdbd-45b0-bd0b-16f1e7_D2
Tumor
0.2
2224c03f-b7b1-4368-887e-2b4cdf_D2
Tumor
0.2
cfd76f9a-ce60-4ec7-8e6b-a8fc31_D3
Tumor
0.2
627e6e36-3dca-4ee5-9755-6f3510_D2
Tumor
0.2
af95e2c6-25c4-4ab8-bf06-3e15ff_D2
Tumor
0.2
b22659b9-e12c-4725-a7db-a833de_D1_D2
Normal
0.2
ce1e5dfc-2ef1-4633-af93-5ea4d9_D2
Tumor
0.1
2ed8beb2-bc63-4bad-b5fe-1916a0_D2
Tumor
0.1
10c2d629-0287-4511-ac25-f29031_D2
Tumor
0.1
61f76fe6-a1c6-41b8-bdc2-2f9209_D2
Normal
0.1
6e209757-a7f4-45af-b5f3-2ebc02_D2
Normal
0.1
b9c1f22e-61f7-45ed-b3b4-5094c7_D2
Normal
0.1
21efd60f-6a31-4b98-9477-16a905_D2
Normal
0.1
3dcf8b3c-c0c5-4dfa-9543-5d30fb_D2
Tumor
0.1
05387aad-2a1f-42c2-8d6f-950598_D3
Tumor
0.1
1a10c200-3895-4648-b951-94f99f_D2
Tumor
0.0
5ea22f5e-307b-491d-801f-8b7fa6_D2
Tumor
0.0
9c8e78bf-b03e-4ba0-9909-5ff070_D2
Tumor
0.0
9e0d47e0-f633-468b-b82b-4d752d_D2
Tumor
0.0
3fbf076a-824b-4eac-b6dc-bf5e59_D2
Normal
0.0
558333b0-ea23-4303-9e3c-4932b1_D2
Tumor
0.0
49bd51fe-48a1-4828-b66e-b30c38_D2
Tumor
0.0
a03d1103-b809-42c4-ad5c-5aff58_D2
Tumor
-0.1
efc971f8-54c5-4531-a792-705ecf_D2
Tumor
-0.1
8e17b45e-6a06-4e4e-913d-7b1edb_D2
Tumor
-0.1
0cc794c3-5bf5-4621-b238-58a0f6_D2
Tumor
-0.1
2dc28da8-7ff1-4b9b-b5bd-17cc25_D2
Tumor
-0.1
fbb41c94-aabd-49cc-90b2-882c3e_D2
Tumor
-0.2
42d860a3-8a0c-4c44-a09a-9ad8cf_D2
Tumor
-0.2
2433b136-fc7b-4cea-b958-bc6efb_D2
Tumor
-0.2
31c15e30-21d4-4843-bd4a-9cd0d8_D2
Normal
-0.2
eb3f3494-7057-4afe-b212-e6e9a3_D2
Tumor
-0.3
35a345a4-e954-4c81-ae3f-7797cd_D2
Tumor
-0.3
e6850782-fd2a-4c53-b682-1852fe_D2
Tumor
-0.4
74a45e5a-a35a-4c60-a4b4-f3f5ea_D2
Tumor
-0.5
51c1c79e-5a8e-4b0a-bf92-1c0cab_D2
Tumor
-0.7
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OVARIAN 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.