Peptide-Spectrum match IMPutation Library
Project description
Peptide-Spectrum match IMPutation Library (PSIMPL)
PSIMPL is a python library for easy imputation of missing PSM data. Given an input PIN file, PSIMPL determines which features contain missing values. PSIMPL then performs imputation by training a regressor on fully observed feature samples.
PSIMPL's API offers a high degree of flexibility, including a large number of state-of-the-art regression algorithms such as: -Linear Regression -Ridge Regression -Lasso (i.e., L1 regularization) -ElasticNet (i.e., L1+L2 regularization)
Future work: cross-validation (CV) for hyperparameter optimization, XGBoost/DNN/Support Vector Regression
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