imputomics 2.0

A common framework for reviewing, integrating and benchmarking missing-value imputation methods across multiomics data.

NCN · MINIATURA 9

Better choices when omics data are incomplete.

A common framework for reviewing, integrating and benchmarking missing-value imputation methods across multiomics data.

Multiomics · Missing values · Benchmarking

Programme: NCN · Miniatura 9
Grant ID: 2025/09/X/NZ7/00157
Start date: 25 Jun 2025
Duration: 12 months
Budget: PLN49,999.00

The research question

Missing values can change the conclusions drawn from omics experiments, yet the best imputation method depends on the dataset and the analytical question. Building on the imputomics web server and R package, this project broadens the framework from metabolomics to multiomics and makes methods easier to compare through common interfaces and curated benchmarks.

What the project sets out to do

01 / RESEARCH AIM

Curate methods and datasets

Review imputation algorithms and annotate their assumptions, applications and omics-specific characteristics.

02 / RESEARCH AIM

Build a common interface

Develop a standardised wrapper for methods across genomics, transcriptomics, proteomics and metabolomics.

03 / RESEARCH AIM

Compare what matters

Benchmark methods using error, correlation, interpretability and downstream tasks, and share an open repository of algorithms and datasets.

People & support

Project lead: Jarosław Chilimoniuk.

National Science Center Poland

Full project title
imputomics 2.0: comprehensive framework for missing value imputation in multi-omics data

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