Methylation age calculator
This application is a phenotypic prediction tool, designed to predict the age of an unknown biological material donor.
In the forensic setting, DNA can serve as evidence in court, through the direct comparison of the suspect's DNA profile with the DNA profile
from the crime scene. It can however play also the role of investigative lead in cases with DNA profiles from the crime scene that doesn't match
with the database and standard investigation methods result in a situation with no or too many suspects. DNA can be used to predict different
characteristics of an unknown trace donor and thus help to narrow down the investigation, pointing it toward a specific group of people.
Molecular age prediction is based on the changing activity of specific genes during a lifetime. One of the mechanisms providing these changes is
the increase or decrease of methylation of promotors of these genes.
The model for blood samples uses methylation data of 7 DNA loci in genes:
MIR29B2CHG (formerly C1orf132), FHL (2 loci), ELOVL (2 loci), CCDC102B and PDE4C.
The model for semen samples uses methylation data of 5 DNA loci in genes: cg12837463B, SH2B2, NOX4, TTC7B and GALR2.
Set the methylations in the range of 0 to 100. You can either set the methylation values individually for each sample
or upload the file in CSV format.
Individual blood sample
You can set methylation values with usage of sliders (step = 1) or
in case of decimal numbers representing percentage of methylation as a numeric input (right subwindow).
Both methods of metylation settings (subwindows) are independent - the values set in one subwindows do not affect the values in the other subwindow.
Slider input
Numeric input
Many blood samples - file input
Upload file in CSV format with samples in rows and methylation values in the first 7 columns.
Use semicolon as a separator and '.' as a decimal point character.
Header of the file is expected but not used as identifiers - methylation column must correspond to these locuses (in the same order):
MIR29B2CHG (formerly C1orf132), FHL (1st locus), FHL (2nd locus), ELOVL (1st locus), ELOVL (2nd locus), CCDC102B and PDE4C.
Last three columns added to the original CSV file contain: point estimation of age (Estimated age) and lower (lower PI90 = 5 %)
and upper limits (upper PI90 = 95 %) of 90% interval estimation (Bayesian predictive interval).
Individual semen sample
You can set methylation values with usage of sliders (step = 1) or
in case of decimal numbers representing percentage of methylation as a numeric input (right subwindow).
Both methods of metylation settings (subwindows) are independent - the values set in one subwindows do not affect the values in the other subwindow.
Slider input
Numeric input
Many semen samples - file input
Upload file in CSV format with samples in rows and methylation values in the first 5 columns.
Use semicolon as a separator and '.' as a decimal point character.
Header of the file is expected but not used as identifiers - methylation column must correspond to these locuses (in the same order):
cg12837463B, SH2B2, NOX4, TTC7B, GALR2.
Last three columns added to the original CSV file contain: point estimation of age (Estimated age) and lower (lower PI90 = 5 %)
and upper limits (upper PI90 = 95 %) of 90% interval estimation (Bayesian predictive interval).