PyAging implements the paper’s conventional four-CpG logistic-regression equation and applies a sigmoid to return LOAD case probability; it does not implement the separate high-dimensional deep-learning classifiers also evaluated in the paper.
Predicts
late-onset Alzheimer's disease
Species
Homo sapiens
Tissue
whole blood
Data type
DNA methylation
Model type
logistic regression
Year
2021
Use with pyaging
import pyaging as pya
pya.pred.predict_age(adata, ["adbahadosingh"])
adbahadosingh huggingface.co is an AI model on huggingface.co that provides adbahadosingh's model effect (), which can be used instantly with this pyaging adbahadosingh model. huggingface.co supports a free trial of the adbahadosingh model, and also provides paid use of the adbahadosingh. Support call adbahadosingh model through api, including Node.js, Python, http.
adbahadosingh huggingface.co is an online trial and call api platform, which integrates adbahadosingh's modeling effects, including api services, and provides a free online trial of adbahadosingh, you can try adbahadosingh online for free by clicking the link below.
pyaging adbahadosingh online free url in huggingface.co:
adbahadosingh is an open source model from GitHub that offers a free installation service, and any user can find adbahadosingh on GitHub to install. At the same time, huggingface.co provides the effect of adbahadosingh install, users can directly use adbahadosingh installed effect in huggingface.co for debugging and trial. It also supports api for free installation.