Abstract
Spatial transcriptomic techniques such as Slide-seqV2 uncover novel relationships and interactions between cell types by coupling gene expression and spatial data. Here we discuss two unexpected sources of error in Slide-seqV2 data, one physical and one computational. To address this we present an analysis pipeline augmentation, Syrah, which corrects for these errors and show that it improves both data quantity and quality over the standard pipeline alone or in combination with additional sequencing.
Competing Interest Statement
The authors have declared no competing interest.
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.