Syrah: a pipeline to maximize spatial transcriptomics data output

Traditionally, these analyses were constrained to examining only a few candidate genes per sample. However, the advent of spatial transcriptomic techniques like Slide-seqV2 has transformed this field, enabling unbiased and massively parallel exploration of gene expression patterns within their tissue contexts through RNA sequencing.

Despite its potential, Slide-seq datasets often suffer from low read counts, loss of data points, and poor quality. We have identified that a significant source of these errors stems from the chemical synthesis of mRNA capture oligonucleotides used in Slide-seqV2. To address this issue, we have developed "Syrah," an analysis pipeline designed to correct these errors.