PUBLICATIONS LEAD OR CO-LEAD BY NYGCtech
Our ECCITE-seq paper describing the capture of multiple modalities of information from single cells, including direct capture of guide RNAs (Nature Methods, online April 22, 2019). You can also access the pre-print on bioRxiv (online since November 8, 2018).
If you can’t access any of these papers above, please send us an email.
PUBLICATIONS USING CITE-SEQ / HASHING (not lead by NYGCtech)
Comprehensive integration of single cell data – Stuart, Butler, … Satija (2019) Cell
A single cell framework for multi-omic analysis of disease identifies malignant regulatory signatures in mixed phenotype acute leukemia – Granja, Klemm, McGinnis … Greenleaf (2019) BioRxiv
RNA velocity and protein acceleration from single-cell multiomics experiments – Gorin, Svensson & Pachter (2019) BioRxiv
Single-Cell Transcriptomic Analysis of mIHC Images via Antigen Mapping – Govek, Tiosi … Camara (2019) BioRxiv
Surface protein imputation from single cell transcriptomes by deep neural networks – Zhou … Zhang (2019) BioRxiv
Mapping Vector Field of Single Cells – Qiu, Zhang … Xing, Weissman (2019) BioRxiv
High Throughput pMHC-I Tetramer Library Production Using Chaperone Mediated Peptide Exchange – Overall, Toor … Sgourakis (2019) BioRxiv
Nuclei multiplexing with barcoded antibodies for single-nucleus genomics – Gaublomme … Rozenblatt-Rosen, Regev (2019) Nature Communications