SpatialArtifacts: a computational framework for tissue artifact detection in spatial transcriptomics data (opens in new tab)

Spatial transcriptomics data are frequently compromised by technical artifacts, such as dry patches, tissue lifting, and uneven reagent coverage, which manifests as regions with low UMI counts, in particular at tissue borders. It can often be challenging to identify these regions using existing quality control methods. Here, we present SpatialArtifacts, a framework that combines median absolute deviation (MAD)-based outlier detection with mathematical morphology operations to identify and cla...