Precise quantification of digital PCR data relies on accurate partition classification - Dividing dPCR partitions into "positive" and "negative" is critical for. However, partition classification can become very time-consuming as dPCR experiments scale up in throughput and complexity. Moreover, there are now good metrics to assess the reliability of the classification method.

DipcensR provides automates the assessment of partition classification robustness, reducing the need for extensive manual review. This helps make the dPCR data analysis workflow more efficient.

The tool includes an optional feature that can attempt to correct any aberrant partition classifications, further streamlining the analysis process.

DipcensR is available as an easy-to-use freely available R package.