Click here to use the multiple testing calculator.

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Probe sets and genes

A TXT file of genes to probe sets mapping for 70,632 genes recognized by the KM-plotter.

A TXT file of the complete list of all 54,675 probe sets utilized in the Kaplan-Meier plotter. The table contains the JetSet parameters and the JetSet best probe set is marked for each gene.

A TXT file of the exact sequences for each of the 16 probes in the 22,277 probe sets of the HGU133A arrays.

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Click on icon to download our publications related to the KM-plotter

miRpower: a web-tool to validate survival-associated miRNAs utilizing expression data from 2178 breast cancer patients, Breast Cancer Res Treat, 2016.

Here, the database behind the miRpower analysis system is described with a cross-validation in multiple datasets.

Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients, Oncotarget, 2016.

Here, the database construction behind the gastric cancer analysis page is described with a cross-validation of previously published prognostic markers.

TP53 mutation-correlated genes predict the risk of tumor relapse and identify MPS1 as a potential therapeutic kinase in TP53-mutated breast cancers, Molecular Oncology, 2014.

In this paper, the background for the extension of the KM-plotter with TP53 status for breast cancer analysis is described. The same upgrade was also added to ovarian cancer.

MEK1 is associated with carboplatin resistance and is a prognostic biomarker in epithelial ovarian cancer. BMC Cancer, 2014.

We describe in this publication the prediction of survival in ovarial cancer patients receiving different chemotherapy regimens.

Online Survival Analysis Software to Assess the Prognostic Value of Biomarkers Using Transcriptomic Data in Non-Small-Cell Lung Cancer, PLoS One, 2013.

In this paper, the extension of the KM-plotter for lung cancer analysis system is described. The frameworks for multivariate analysis and plotting funnel plots are also summarized.

A meta-analysis of gene expression-based biomarkers predicting outcome after tamoxifen treatment in breast cancer, Breast Cancer Res Treatment, 2013.

Here we describe the updated version of the breast cancer database and filtering options. In addition, we evaluate endocrine therapy resistance biomarker candidates of the literature.

Implementing an online tool for genome-wide validation of survival-associated biomarkers in ovarian cancer using microarray data from 1287 patients, Endocrine-Related Cancer, 2012.

Here we describe the ovarian cancer edition of the Kaplan-Meier plotter and also evaluate the prognostic power of 37 previously published biomarkers on ovarian cancer prognosis.

RecurrenceOnline: an online analysis tool to determine breast cancer recurrence and hormone receptor status using microarray data, Breast Cancer Res Treatment, 2012.

Here we integrated all available knowledge in one platform to validate currently used predictors and to provide a global tool for the online determination of different prognostic parameters simultaneously using genome-wide microarrays.

Jetset: selecting the optimal microarray probe set to represent a gene, BMC Bioinformatics, 2011.

A method is described to calculate principled, unbiased quality scores for Affymetrix probe sets, and to use these scores to define a simple, unambiguous mapping from gene to probe set.

An online survival analysis tool to rapidly assess the effect of 22,277 genes on breast cancer prognosis using microarray data of 1,809 patients, Breast Cancer Res Treatment, 2010.

In this publication we describe the construction of the first online version of the Kaplan-Meier plotter and also describe the setup of the web server behind the system.

Meta-analysis of gene expression profiles related to relapse-free survival in 1,079 breast cancer patients, Breast Cancer Res Treatment, 2009.

This meta-analysis utilizes the first version of the integrated database of breast cancer microarrays. The identification of the re-published microarrays is described. The performance of 20 gene sets is compared.

Evaluation of Microarray Preprocessing Algorithms Based on Concordance with RT-PCR in Clinical Samples, PLoS One, 2009.

In this paper we introduce the log-ratio discrepancy to measure discordance between gene expression platforms. The use of the MAS5 algorithm for the database construction is based on this study.

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Supplemental materials

Powerpoint template to enable changing font and text size.

Supplemental table for our 2013 PLoS One paper: an XLS file containing genes in the gene expression signatures.

Supplemental data for our 2013 Breast Cancer Res Treatment paper: TXT files including clinical and normalized gene expression data for Affymetrix, Illumina and RNA-seq datasets used in the study.

Supplemental R script for our 2013 Breast Cancer Res Treatment paper: the R script used to generate Kaplan-Meier plots.

Supplemental R script for our 2013 Breast Cancer Res Treatment paper: the R script employed to compute ROC (Receiver Operating Characteristic) analysis.

Supplemental database for our 2012 Endocrine-Related Cancer paper: a TXT file of the normalized gene expression data for 1,394 ovarian cancer microarrays.

Supplemental database for our 2012 Endocrine-Related Cancer paper: a TXT file of the experimental descriptors for the ovarian cancer samples.

Supplemental database for our 2010 Breast Cancer Res Treatment paper: a TXT file of the normalized gene expression data for 1,809 breast cancer microarrays.

Supplemental table for our 2010 Breast Cancer Res Treatment paper: a TXT file of the experimental descriptors for 1,809 breast cancer samples.

Supplemental sweave file for our 2009 PLoS One paper: the R scripts used to download, process and visualize the data.

Supplemental table for our 2009 Breast Cancer Res Treatment paper: an XLS file of the microarrays published under multiple GEO accession numbers.

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