Predict the retention times for missing peptides using the Soft-Impute algorithm
Cortado is currently in a usable prototype state.
To use Cortado, you'll need to read your retention times into a 2D Numpy array. For example:
import polars as pl
from cortado import SoftImpute
# Each column is a sample and each row is a precursor.
df = pl.read_csv("my_data.csv")
# Remove any columns that are not reten
mat = df.drop("precursor_id").to_numpy()
Now you can impute the missing retention times:
filled_mat = SoftImpute().fit_transform(mat)