Abstract
Single-cell RNA sequencing (scRNA-seq) is a powerful tool for characterising the immune landscape. Multiple technologies are available, each with distinct specificities and inherent biases. Here, we focus on two technologies-10X Genomics and Parse Biosciences-for the paired profiling of TCR and whole-transcriptome in T cells using matched patient samples. Both platforms generated high-quality data and captured comparable TCR clonal landscapes, with strong concordance for dominant clones. More genes were captured with Parse, including a broader range of non-coding genes and pseudogenes. Although average gene expression was highly correlated across the platforms, feature selection, which retains only the most informative genes, yielded different sets of selected genes. Additionally, many T-cell subset markers varied substantially between platforms. Genes enriched in Parse were typically longer and associated with naive/central-memory T-cell genes, whereas those enriched in 10X were shorter and often associated with cytotoxic/effector genes. These patterns are consistent with differences in capture chemistry. These findings highlight meaningful considerations for platform selection, which should be aligned with study objectives. Parse offers an advantage for studies prioritising a wider range of genes, while 10X may be the apparent choice for detailed characterisation of effector function.