TraitCorr - correlating gene expression measurements with phenotypic data
Thomas NußbaumeriD, Olivia DebnathiD, Christian Wagner, Parviz HeidariiD
Abstract
Today, transcriptomes and microarrays can be generated and analysed in high quantity. In addition, experiments often include descriptive information about each sample which needs to be compared to the gene expression profiles. The understanding of the relationships between gene expression and phenotype is introduced as new challenge in system biology. Combining expression (RNA-seq and microarray) and phenotype data could reveal the role or effects of each gene on traits. To address all these needs, the user-interface TraitCorr was developed which allows to determine genes that are significantly correlating with a selected trait. Furthermore, it allows to determine significantly correlated genes among different traits and provides visualisation and analysis possibilities.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 1
- FWCI
- 0.08
- Field percentile
- 33th percentile
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Reference trait analysis reveals correlations between gene expression and quantitative traits in disjoint samples
Daniel A. Skelly, Narayanan Raghupathy, … Elissa J. Chesler·GeneticsPeer-reviewed·May 21, 2019
- Robust gene coexpression networks using signed distance correlation
Javier Pardo-Diaz, Lyuba V. Bozhilova, … Gesine Reinert·BioinformaticsPeer-reviewed·Jan 20, 2021
- Metric Learning on Expression Data for Gene Function Prediction
Stavros Makrodimitris, Marcel J. T. Reinders, Roeland C. H. J. van Ham·BioinformaticsPeer-reviewed·Sep 26, 2019
- Can we assume the gene expression profile as a proxy for signaling network activity?
Mehran Piran, Reza Karbalaei, … Mohieddin Jafari·BiomoleculesPeer-reviewed·Jun 3, 2020
- A systematic analysis of genetically regulated differences in gene expression and the role of co-expression networks across 16 psychiatric disorders and substance use phenotypes
Zachary F. Gerring, Jackson G. Thorp, … Eske M. Derks·bioRxiv·Jan 28, 2021
- Proportionality: a valid alternative to correlation for relative data
David Lovell, Vera Pawlowsky-Glahn, … Jürg Bähler·PLOS Computational BiologyPeer-reviewed·Mar 16, 2015