Models

Please note that most functions are helper functions and are not meant to be used directly.

pyaging.models._models

class pyaging.models._models.ABEC

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.ADBahadoSingh

Bases: LinearReferenceClock

postprocess(x)

Logistic transform to an Alzheimer’s disease risk probability.

The published logit constant (-0.072) is carried in the linear intercept.

class pyaging.models._models.AltumAge

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Scales an array based on the median and standard deviation.

class pyaging.models._models.BiTAge

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Binarizes an array based on the median of each row, excluding zeros.

class pyaging.models._models.Bocklandt

Bases: LinearReferenceClock

class pyaging.models._models.Bohlin

Bases: LinearReferenceClock

postprocess(x)

Model returns gestational age in days; convert to weeks.

class pyaging.models._models.CTSLiver

Bases: LinearReferenceClock

class pyaging.models._models.CVDWesterman

Bases: LinearReferenceClock

postprocess(x)

Logistic transform to a CVD risk probability.

class pyaging.models._models.CamilloH3K27ac

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.CamilloH3K27me3

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.CamilloH3K36me3

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.CamilloH3K4me1

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.CamilloH3K4me3

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.CamilloH3K9ac

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.CamilloH3K9me3

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.CamilloPanHistone

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.CellPopAge

Bases: LinearReferenceClock

class pyaging.models._models.CompIL6

Bases: LinearReferenceClock

class pyaging.models._models.CorticalClock

Bases: LinearReferenceClock

postprocess(x)

Horvath anti-logarithmic linear transformation (adult age = 20).

class pyaging.models._models.CpGPTGrimAge3

Bases: pyagingModel

postprocess(x)

Converts from a Cox parameter to age in units of years.

preprocess(x)

Scales an array based on the median and standard deviation.

class pyaging.models._models.CpGPTPCGrimAge3

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x)

Converts from a Cox parameter to age in units of years.

preprocess(x)

Scales an array based on the mean and standard deviation.

class pyaging.models._models.DNAmFILi

Bases: LinearReferenceClock

class pyaging.models._models.DNAmFitAge

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.DNAmFitAgeGaitF

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.DNAmFitAgeGaitM

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.DNAmFitAgeGripF

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.DNAmFitAgeGripM

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.DNAmFitAgeVO2Max

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.DNAmIC

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.DNAmPhenoAge

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.DNAmStress

Bases: LinearReferenceClock

class pyaging.models._models.DNAmTL

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.DeconvoluteBloodEPIC

Bases: DeconvolutionSingleCell

class pyaging.models._models.DeconvolutionSingleCell

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.DepressionBarbu

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.DownSyndrome

Bases: LinearReferenceClock

class pyaging.models._models.DunedinPACE

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Apply quantile normalization on x using gold standard means.

class pyaging.models._models.DunedinPoAm38

Bases: LinearReferenceClock

class pyaging.models._models.ENCen100

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.ENCen40

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.EPICGA

Bases: LinearReferenceClock

postprocess(x)

Model returns gestational age in days; convert to weeks.

class pyaging.models._models.EnsembleAgeHumanMouse

Bases: LinearReferenceClock

class pyaging.models._models.EnsembleAgeStatic

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.EnsembleAgeStaticTop

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.EpiCMITHyper

Bases: epiTOC1

class pyaging.models._models.EpiCMITHypo

Bases: epiTOC1

class pyaging.models._models.EpiTOC3

Bases: epiTOC2

class pyaging.models._models.Garagnani

Bases: LinearReferenceClock

class pyaging.models._models.GliaSin

Bases: LinearReferenceClock

class pyaging.models._models.GrimAge

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x)

Converts from a Cox parameter to age in units of years.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.GrimAge2

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x)

Converts from a Cox parameter to age in units of years.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.GrimAge2ADM

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.GrimAge2B2M

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.GrimAge2CystatinC

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.GrimAge2GDF15

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.GrimAge2Leptin

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.GrimAge2LogA1C

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.GrimAge2LogCRP

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.GrimAge2PAI1

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.GrimAge2PackYrs

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.GrimAge2TIMP1

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.HRSInCHPhenoAge

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Han

Bases: pyagingModel

postprocess(x)

Applies an anti-logarithmic linear transformation to a PyTorch tensor.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Hannum

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Hep

Bases: LinearReferenceClock

class pyaging.models._models.HepatoXu

Bases: LinearReferenceClock

class pyaging.models._models.Horvath2013

Bases: pyagingModel

postprocess(x)

Applies an anti-logarithmic linear transformation to a PyTorch tensor.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.HypoClock

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Compute mean beta per sample, excluding missing (-1) values.

class pyaging.models._models.IntrinClock

Bases: pyagingModel

postprocess(x)

Applies an anti-logarithmic linear transformation to a PyTorch tensor.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Knight

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.LeeControl

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.LeeRefinedRobust

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.LeeRobust

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Lin

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.LinearReferenceClock

Bases: pyagingModel

Base class for linear methylation clocks that impute missing features from reference_values (when provided) and apply no output transform.

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Mammalian1

Bases: pyagingModel

postprocess(x)

Applies an anti-logarithmic transformation with an offset of -2.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Mammalian2

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x, x_species)

Converts output of relative age to age in units of years.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Mammalian3

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x, x_species)

Converts output of to units of years.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.MammalianBlood2

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x, x_species)

Converts output of relative age to age in units of years.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.MammalianBlood3

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x, x_species)

Converts output of to units of years.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.MammalianFemale

Bases: pyagingModel

postprocess(x)

Applies a sigmoid transformation.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.MammalianLifespan

Bases: pyagingModel

postprocess(x)

Applies an anti-log transformation.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.MammalianSkin2

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x, x_species)

Converts output of relative age to age in units of years.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.MammalianSkin3

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x, x_species)

Converts output of to units of years.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Mayne

Bases: LinearReferenceClock

postprocess(x)

Gestational age in weeks (as published).

class pyaging.models._models.McCartneyAlcohol

Bases: LinearReferenceClock

class pyaging.models._models.McCartneyBMI

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.McCartneyBodyFat

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.McCartneyEducation

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.McCartneyHDLCholesterol

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.McCartneyLDLCholesterol

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.McCartneySmoking

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.McCartneyTotalCholesterol

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.McCartneyTotalHDLRatio

Bases: LinearReferenceClock

class pyaging.models._models.McCartneyWHR

Bases: LinearReferenceClock

class pyaging.models._models.Meer

Bases: pyagingModel

postprocess(x)

Transforms age in days to age in months.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.NeuSin

Bases: LinearReferenceClock

class pyaging.models._models.OcampoATAC1

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Normalize a PyTorch tensor of counts to TPM (Transcripts Per Million) then transforms with log1p.

class pyaging.models._models.OcampoATAC2

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Normalize a PyTorch tensor of counts to TPM (Transcripts Per Million) then transforms with log1p.

class pyaging.models._models.PCDNAmTL

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.PCGrimAge

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.PCHannum

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.PCHorvath2013

Bases: pyagingModel

postprocess(x)

Applies an anti-logarithmic linear transformation to a PyTorch tensor.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.PCPhenoAge

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.PCSkinAndBlood

Bases: pyagingModel

postprocess(x)

Applies an anti-logarithmic linear transformation to a PyTorch tensor.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Pasta

Bases: pyagingModel

postprocess(x)

Apply linear scaling and shifting constants from the original Pasta definition.

preprocess(x)

Fill missing values with the global median then rank-normalize per sample.

class pyaging.models._models.PastaMouse

Bases: Pasta

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

set_mouse_features(full_features, full_reference_values=None, mouse_prefix='ENSMUSG')

Configure the mouse-only interface while keeping the full feature space for the base model.

class pyaging.models._models.PedBE

Bases: pyagingModel

postprocess(x)

Applies an anti-logarithmic linear transformation to a PyTorch tensor.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Petkovich

Bases: pyagingModel

postprocess(x)

Applies a convertion from the output of an ElasticNet to mouse age in months.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.PhenoAge

Bases: pyagingModel

postprocess(x)

Applies a convertion from a CDF of the mortality score from a Gompertz distribution to phenotypic age.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.PipekElasticNet

Bases: pyagingModel

postprocess(x)

Applies an anti-logarithmic linear transformation to a PyTorch tensor.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.PipekFilteredH

Bases: pyagingModel

postprocess(x)

Applies an anti-logarithmic linear transformation to a PyTorch tensor.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.PipekRetrainedH

Bases: pyagingModel

postprocess(x)

Applies an anti-logarithmic linear transformation to a PyTorch tensor.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.ProstateCancerKirby

Bases: LinearReferenceClock

class pyaging.models._models.ReedBMI

Bases: LinearReferenceClock

class pyaging.models._models.Reg

Bases: pyagingModel

postprocess(x)

Add the REG intercept term after linear prediction.

preprocess(x)

Fill missing values with the global median then rank-normalize per sample.

class pyaging.models._models.RepliTali

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.RepliTaliNorm

Bases: LinearReferenceClock

class pyaging.models._models.RetroelementAgeV1

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.RetroelementAgeV2

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.SenChronoAge

Bases: LinearReferenceClock

class pyaging.models._models.SenCultureAge

Bases: LinearReferenceClock

class pyaging.models._models.SenMortalityAge

Bases: LinearReferenceClock

class pyaging.models._models.SexScoreBase

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.SkinAndBlood

Bases: pyagingModel

postprocess(x)

Applies an anti-logarithmic linear transformation to a PyTorch tensor.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.StemTOCvitro

Bases: stemTOC

class pyaging.models._models.StocH

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.StocP

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.StocZ

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.Stubbs

Bases: pyagingModel

postprocess(x)

Applies a convertion from the output of an ElasticNet to mouse age in months.

preprocess(x)

Apply quantile normalization on x using gold standard means and then scale with the means and standard deviation.

class pyaging.models._models.SystemsAge

Bases: SystemsAgeBase

class pyaging.models._models.SystemsAgeBase

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.SystemsAgeBlood

Bases: SystemsAgeBase

class pyaging.models._models.SystemsAgeBrain

Bases: SystemsAgeBase

class pyaging.models._models.SystemsAgeHeart

Bases: SystemsAgeBase

class pyaging.models._models.SystemsAgeHormone

Bases: SystemsAgeBase

class pyaging.models._models.SystemsAgeImmune

Bases: SystemsAgeBase

class pyaging.models._models.SystemsAgeInflammation

Bases: SystemsAgeBase

class pyaging.models._models.SystemsAgeKidney

Bases: SystemsAgeBase

class pyaging.models._models.SystemsAgeLiver

Bases: SystemsAgeBase

class pyaging.models._models.SystemsAgeLung

Bases: SystemsAgeBase

class pyaging.models._models.SystemsAgeMetabolic

Bases: SystemsAgeBase

class pyaging.models._models.SystemsAgeMusculoSkeletal

Bases: SystemsAgeBase

class pyaging.models._models.Thompson

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.TwelveCellDeconvoluteBloodEPIC

Bases: DeconvolutionSingleCell

class pyaging.models._models.VidalBralo

Bases: LinearReferenceClock

class pyaging.models._models.Weidner

Bases: LinearReferenceClock

class pyaging.models._models.Wu

Bases: LinearReferenceClock

postprocess(x)

Horvath anti-log (adult age = 48) giving months, then months to years.

class pyaging.models._models.XChrom

Bases: SexScoreBase

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

class pyaging.models._models.YChrom

Bases: SexScoreBase

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

class pyaging.models._models.YingAdaptAge

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.YingCausAge

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.YingDamAge

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.ZhangBLUP

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Scales the input PyTorch tensor per row with mean 0 and std 1.

class pyaging.models._models.ZhangEN

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Scales the input PyTorch tensor per row with mean 0 and std 1.

class pyaging.models._models.ZhangMortality

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.cABEC

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.eABEC

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.epiTOC1

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.

class pyaging.models._models.epiTOC2

Bases: pyagingModel

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Replace NaNs with zero; missing features should already be imputed via reference_values.

class pyaging.models._models.stemTOC

Bases: pyagingModel

postprocess(x)

Postprocess the model output. This method should be implemented by all subclasses.

preprocess(x)

Preprocess the input data. This method should be implemented by all subclasses.