TY - JOUR
T1 - TRGAted
T2 - A web tool for survival analysis using protein data in the Cancer Genome Atlas
AU - Zhang, Weizhou
AU - Borcherding, Nicholas
AU - Bormann, Nicholas L.
AU - Voigt, Andrew P.
N1 - Funding Information:
Grant information: Funding for this project was provided from National Institute of Health F30 fellowship [CA206255] to N.B. and NIH Grant R01 [CA200673] to W.Z.
Funding Information:
Funding for this project was provided from National Institute of Health F30 fellowship [CA206255] to N.B. and NIH Grant R01 [CA200673] to W.Z.
Publisher Copyright:
© 2018 Borcherding N et al.
PY - 2018
Y1 - 2018
N2 - Reverse-phase protein arrays (RPPAs) are a highthroughput approach to protein quantification utilizing antibody-based micro-to-nano scale dot blot. Within the Cancer Genome Atlas (TCGA), RPPAs were used to quantify over 200 proteins in 8,167 tumor and metastatic samples. Protein-level data has particular advantages in assessing putative prognostic or therapeutic targets in tumors. However, many of the available pipelines do not allow for the partitioning of clinical and RPPA information to make meaningful conclusions. We developed a cloud-based application, TRGAted to enable researchers to better examine patient survival based on single or multiple proteins across 31 cancer types in the TCGA. TRGAted contains up-to-date overall survival, disease-specific survival, disease-free interval and progression-free interval information. Furthermore, survival information for primary tumor samples can be stratified based on gender, age, tumor stage, histological type, and subtype, allowing for highly adaptive and intuitive user experience. The code and processed data are open sourced and available on github and contains a tutorial built into the application for assisting users.
AB - Reverse-phase protein arrays (RPPAs) are a highthroughput approach to protein quantification utilizing antibody-based micro-to-nano scale dot blot. Within the Cancer Genome Atlas (TCGA), RPPAs were used to quantify over 200 proteins in 8,167 tumor and metastatic samples. Protein-level data has particular advantages in assessing putative prognostic or therapeutic targets in tumors. However, many of the available pipelines do not allow for the partitioning of clinical and RPPA information to make meaningful conclusions. We developed a cloud-based application, TRGAted to enable researchers to better examine patient survival based on single or multiple proteins across 31 cancer types in the TCGA. TRGAted contains up-to-date overall survival, disease-specific survival, disease-free interval and progression-free interval information. Furthermore, survival information for primary tumor samples can be stratified based on gender, age, tumor stage, histological type, and subtype, allowing for highly adaptive and intuitive user experience. The code and processed data are open sourced and available on github and contains a tutorial built into the application for assisting users.
KW - Bioinformatics
KW - Cancer Proteomics
KW - Survival Analysis
KW - TCGA
UR - http://www.scopus.com/inward/record.url?scp=85055081106&partnerID=8YFLogxK
U2 - 10.12688/f1000research.15789.2
DO - 10.12688/f1000research.15789.2
M3 - Article
C2 - 30345029
AN - SCOPUS:85055081106
SN - 2046-1402
VL - 7
JO - F1000Research
JF - F1000Research
M1 - 1235
ER -