Single-cell foundation models (scFMs) are commonly benchmarked using final-layer embeddings, although useful depth may depend on the task. We evaluate Geneformer, scBERT, scGPT, and scFoundation as frozen feature extractors for cell-type and perturbation-response prediction using layer-wise probes, leave-one-dataset-ou...
Ming Wen, Yiwei Lyu, Andrew Robbins· bioRxiv· 0 citations
Correcting batch effects and integrating single-cell sequencing datasets has been a crucial step in large-scale biological studies. Many methods have been published for this task, with complementary strengths in various scenarios. Our previous work, LIGER, leveraging integrative non-negative matrix factorization (iNMF)...
Yi-Chen Wang, Andrew Robbins, Gaurav T. Gadhvi et al.· bioRxiv· 0 citations
In male mice with established two-hit HFpEF, autotaxin inhibition improved diastolic indices and reduced fibrosis, hypertrophy and cardiac myeloid accumulation and the autotaxin–LPA axis is nominated as a tractable therapeutic target.
Rajesh Chaudhary, Andrew Robbins, A. Singh et al.· bioRxiv· 0 citations
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