Expression View : This analysis is composed of 3 major plots. sorting plot by subset, Box plot and Mean-trend plot. Each plots are made by PCTA dataset, and you can see expression trends of your gene or gene list.
Correlation View : This analysis is composed of scatter plots and regression line. As a result, you can check correlation between 2 sets of your input through PCTA dataset. Correlation statistic is spearman rank sum.
GSEA and MRA : This analysis is a big category of 2 different analyses. Gene Set Enrichment Analysis and Master Regulator Analysis. You will have GSEA result of your gene set and its master regulator candidates through PCTA dataset.
Entrez ID and official gene symbol in this version. Here is example :
Pathway input : Click Pathway input button above input box, then you can see dialog box to choose pathway. Choose one of them, and Click enter button
Expression View : Copy and paste a gene and gene set. If input is gene set, it will be calculated to Z score.
Correlation View : Copy and paste a gene and gene set in 2 different input boxes. If input is gene set, it will be calculated to Z score. Additionally, Input name can be customized
GSEA and MRA : Copy and paste gene set only and input name can be customized. Set analysis needs more than 10 genes for the input to increase accuracy.
*Supplemnet : If you enter a set of genes, it will be calculated Z score(Gene set Z score) automatically not original expression values.
Expression View : This analysis has 4 options, Disease course, PCS, PAM50 and BCR. Disease course option will divide PCTA samples by Gleason score (GS<7, GS=7, GS>7, mCRPC). PCS is one of stratification system for prostate cancer, and it will categorize samples as PCS1, PCS2 and PCS3. PAM50 is one of stratification system for prostate cancer as similar as PCS, and it will divide PCTA dataset by Luminal A, Luminal B and Basal. BCR means Biochemical Recurrence Free analysis, and you will have Kaplan-Meier plot and Cox Proportional Hazard Analysis for your input. Here is example:
Correlation View : This analysis has 3 options. Disease course, PCS, PAM50 and BCR. Disease course option will divide PCTA samples by Gleason score (GS<7, GS=7, GS>7, mCRPC). PCS is one of stratification system for prostate cancer, and it will categorize samples as PCS1, PCS2 and PCS3. PAM50 is one of stratification system for prostate cancer as similar as PCS, and it will divide PCTA dataset by Luminal A, Luminal B and Basal.
GSEA and MRA : This analysis has bi-sampling options(ex. GS<7 versus Others in Disease Course). Bi-sampling option is composed of 3 major categories such as Disease course, PCS and PAM50.
You will have results of every analysis by clicking Image Download and Table Download at the top of result screen.
GSEA and MRA : GSEA shows you the enrichment values of your geneset through PCTA. Master regulator analysis is using Fisher exact test and some filtering option(P-value < 0.01, Fold change > 0.1(Only positive-value case), The number of target genes of candidate > 10)to decide candidates. In network, node size means the number of mapped genes, and edge thickness indicates negative Log value of p-value from Chi-square test between nodes.
Color degree means fold change between user-selected samples and others
You can download Source Code, PCTA dataset and its clinical data in Download section.
Main workframe : Django (v1.11.4)
Web Server : Nginx (uWSGI Connected)
1. GSEA : gseapy for python (Link)
2. Network plot : networkx for python (Link)
3. Survival analysis : lifelines for python (Link)
4. Message passing library : celery (Link)
5. ETC library : pandas, scipy, numpy, seaborn, matplotlib
6. Database : MySQL
PAM50 :Associations of Luminal and Basal Subtyping of Prostate Cancer With Prognosis and Response to Androgen Deprivation Therapy.(Shuang G. Zhao et al, 2017 JAMA)
PCS :Integrated classification of prostate cancer reveals a novel luminal subtype with poor outcome. (Sungyong You et al, 2016 Cancer Research)
GSE40272 (BCR dataset) :Increased expression of NuSAP in recurrent prostate cancer is mediated by E2F1. (Zulfiqar G. Gulzar et al, 2013 Oncogene)
GSE70769 (BCR dataset) :Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study. (H.Ross-Adams et al, 2015 EBioMedicine)
GDC TCGA Prostate Cancer (BCR dataset) :Xena by UCSC
PCTA Version 1.0.1-Public, Cedars-Sinai Medical Center, All right reserved, Copyright
Bug Report & Contact : Sungyong.You@cshs.org