BURNS : Bioinformatics Utility for RevealiNg Senescence
This tool will load in your raw count data from an RNA-Seq experiment and output a table predicting the human age of the sample(s).
BURNS will convert and filter genes, imputed missing genes, perform a TMM normalization, run a batch correction, and then use a trained model to predict age.
If asked, BURNS will try to convert your IDs to symbols using
. IDs can be from ensembl, entrez, ucsc, or refseq. Conversion is not perfect.
Two models are available: one trained on the top 100 variable genes and one trained on the top 100 differential genes from a normalized, batch-corrected, cohort of 3,060 human samples.
Input datasets should have IDs in the first column, sample names in the first row, and raw read counts for all genes. For more information, please see the
To download a sample dataset please right-click and
Save Link As.
Please note that this tool is provided AS IS and without any guarantees. Use at your own risk!