GEOapplication/xmlftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE289nnn/GSE289299/primaryOK200OtherSchmidtea mediterraneaOtherhttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE289299GEOGSEfalseSyrah: a pipeline to maximize spatial transcriptomics data outputSpatial analysis of gene expression patterns has been a key technique for revealing the functions of genes. 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. Syrah can dramatically enhance Slide-seqV2 datasets by recovering nearly 30% more reads. Unlike other dataset improvement methods that rely on complex mathematical imputation or single-cell RNA-seq references, Syrah operates independently, requiring no additional datasets or intricate calculations. This innovative technique promises to salvage previously unusable Slide-seq datasets by restoring valuable reads that were inadvertently discarded during analysis.2026/04/21GSE289299GSM8788641GSM878864021689289299Schmidtea mediterranea