RADseq Data Exploration, Manipulation and Visualization using R
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Aug 20, 2026 - HTML
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RADseq Data Exploration, Manipulation and Visualization using R
sciblox - Easier Data Science and Machine Learning
From QC to summary statistics
An efficient genetic data imputation pipeline
A highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.
A highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning.
{shinymice} is an R package for interactive evaluation of incomplete data by Hanne Oberman, guided by Gerko Vink and Stef van Buuren.
Prova: probabilistic-statistical variate analysis and inference, nonparametric and with automated MCMC
Example code for the handbook "Comparative effectiveness and personalized medicine using real-world data"
Marker based imputation of MoCap data.
Stefan's imputation accuracy package
DSI Capstone Project
Investigate the reasons behind bankruptcy and attempt to identify early warning signs. Perform exploratory data analytics using pandas profiling and apply missing value treatments and oversampling
MSc thesis 'Missing the Point: Non-Convergence in Iterative Imputation Algorithms' by Hanne Oberman
Apply unsupervised learning techniques to identify customers segments.
📊 A Customer Credit Risk dataset collected from multiple sources (CSV, JSON, SQL, and an external API). perform full-scale preprocessing and feature engineering so that the dataset is clean, consistent, and suitable for building a Machine Learning model that predicts whether a customer is likely to default on a loan.
Interactive MATLAB interface for masking Rayleigh and Raman scatter in EEM fluorescence data and handling masked pixels with NaN, interpolation, SVD, PARAFAC-ALS, O-ALS, or MCR-ALS.
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