The gene-editing systems as represented by CRISPR/Cas and their derivates enable genome-wide targeted editing in humans and a wide variety of other organisms by either DNA or RNA level modulation. Quantifying the on- and off-target editing outcomes and profiling the mixed complex mutational spectrum in vitro and in vivo, in bulk or even at the single-cell level, at high accuracy and sensitivity becomes an urgent need for both industry and clinical studies. However, the vast diverse mutations with variable frequency plus multiple-target gene-editing makes systematical enumerating the editome and cataloging rare but relevant co-occurring events and monitoring the single-cell level clonal dynamics very challenging in the real world, especially for the interpretation of the noisy amplicon deep sequencing data. Despite many efforts, the existing pipelines and analytic tools are either defective in processing high-depth multiplexed amplicon data or do not support single-cell data analysis. To address these challenging issues and attempt to standardize the gene-editing data analysis, we have developed getools, a native integrated gene-editing data analysis software toolkit for determining editing efficiency and cataloging outcomes at the ‘perread’ level from next-generation sequencing data.Code availability: https://github.com/edigene/getools