5 papers · ranked by Valyu relevance
Anthony Christidis, Andrew Ghazi, Smriti Chawla, Nitesh Turaga + 2 more
Although cell type annotation has become an integral part of single-cell analysis workflows, the assessment of computational annotations remains challenging. Many annotation tools transfer labels from an annotated reference dataset to a new query dataset of interest, but blindly transferring labels from one dataset to…
Li Zhang, Haicheng Rao, Mengge Li, Xiaobo Qian + 3 more
Single-cell atlas annotations are routinely treated as ground truth but rarely validated before use. We present AnnoAudit, a marker-based audit protocol that combines four convergent checks—marker scoring, unsupervised clustering, margin-gated module scoring, and applicability-gated pretrained models—into a composite…
Yuqiao Liu, Siyu Yi, Hengchuang Yin, Wei Ju
Single-cell RNA sequencing profiles cellular heterogeneity at atlas scale, making automated annotation essential. However, target datasets often contain novel cell types missing from incomplete references. We present scOLAR, an ontology-guided open-set framework that learns prototypes over the Cell Ontology and uses…
Huihai Wu, Ashleigh Lister, Iain Macaulay, Katie Long + 10 more
Single-cell and spatial transcriptomics are transforming our understanding of cellular heterogeneity and tissue organization, yet their analytical complexity remains a major bottleneck. Here, we present EISCA and EISTA, two standardized, end-to-end pipelines for single-cell RNA- seq and imaging-based spatial…
Himanshu Goel, Miklos Sahin -Toth
Inherited retinal diseases provide some of the strongest evidence that clinically relevant transcripts may not be represented adequately by canonical annotations. Deep retinal transcriptomic studies have identified previously unrecognised exons and transcript isoforms that are highly expressed in photoreceptor cells…