Posts Tagged ‘singlecell’

ScEQTL

May 12, 2022

https://www.nature.com/articles/s41586-022-04713-1

Published: 11 May 2022
Single-cell eQTL models reveal dynamic T cell state dependence of disease loci Aparna Nathan, Samira Asgari, Kazuyoshi Ishigaki, Cristian Valencia, Tiffany Amariuta, Yang Luo, Jessica I. Beynor, Yuriy Baglaenko, Sara Suliman, Alkes L. Price, Leonid Lecca, Megan B. Murray, D. Branch Moody & Soumya Raychaudhuri
Nature (2022)

Statistical and machine learning methods for spatially resolved transcriptomics data analysis | Genome Biology | Full Text

April 29, 2022

https://genomebiology.biomedcentral.com/articles/10.1186/s13059-022-02653-7

Identification of cell types from single cell data using stable clustering | Scientific Reports

March 27, 2022

https://www.nature.com/articles/s41598-020-66848-3

uses dbscan

Anatomical structures, cell types and biomarkers of the Human Reference Atlas

November 10, 2021

Anatomical structures, cell types and biomarkers of the Human Reference Atlas https://www.nature.com/articles/s41556-021-00788-6.pdf

host-viral infection maps from sc-rna seq with a computational framework

June 2, 2020

Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients

https://www.sciencedirect.com/science/article/pii/S0092867420305687

host-viral infection maps from sc-rna seq with a computational framework

June 2, 2020

https://www.sciencedirect.com/science/article/pii/S0092867420305687

Single cell estimation from bulk data

April 12, 2020

Accurate estimation of cell composition in bulk expression through robust integration of single-cell information

Brandon Jew, Marcus Alvarez, Elior Rahmani, Zong Miao, Arthur Ko, Jae Hoon Sul, Kirsi H. Pietiläinen, Päivi Pajukanta, Eran Halperin doi:

https://doi.org/10.1101/669911

Quantifying the tradeoff between sequencing depth and cell number in single-cell RNA-seq

November 2, 2019

https://www.biorxiv.org/content/10.1101/762773v1

New cell type analysis in human cortex

October 26, 2019

Published: 21 August 2019

Conserved cell types with divergent features in human versus mouse cortex

Rebecca D. Hodge, Trygve E. Bakken, Jeremy A. Miller, Kimberly A. Smith, Eliza R. Barkan, Lucas T. Graybuck, Jennie L. Close, Brian Long, Nelson Johansen, Osnat Penn, Zizhen Yao, Jeroen Eggermont, Thomas Höllt, Boaz P. Levi, Soraya I. Shehata, Brian Aevermann, Allison Beller, Darren Bertagnolli, Krissy Brouner, Tamara Casper, Charles Cobbs, Rachel Dalley, Nick Dee, Song-Lin Ding, Richard G. Ellenbogen, Olivia Fong, Emma Garren, Jeff Goldy, Ryder P. Gwinn, Daniel Hirschstein, C. Dirk Keene, Mohamed Keshk, Andrew L. Ko, Kanan Lathia, Ahmed Mahfouz, Zoe Maltzer, Medea McGraw, Thuc Nghi Nguyen, Julie Nyhus, Jeffrey G. Ojemann, Aaron Oldre, Sheana Parry, Shannon Reynolds, Christine Rimorin, Nadiya V. Shapovalova, Saroja
Somasundaram, Aaron Szafer, Elliot R. Thomsen, Michael Tieu, Gerald Quon, Richard H. Scheuermann, Rafael Yuste, Susan M. Sunkin, Boudewijn Lelieveldt, David Feng, Lydia Ng, Amy Bernard, Michael Hawrylycz, John W. Phillips, Bosiljka Tasic, Hongkui Zeng, Allan R. Jones, Christof Koch & Ed S. Lein

https://www.nature.com/articles/s41586-019-1506-7

Single Cell Resource for Mouse

August 2, 2019

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Tabula Muris is a compendium of single cell transcriptome data from the model organism Mus musculus, containing nearly 100,000 cells from 20 organs and tissues. The data allow for direct and controlled comparison of gene expression in cell types shared between tissues, such as immune cells from distinct anatomical locations. They also allow for a comparison of two distinct technical approaches: “}}

https://tabula-muris.ds.czbiohub.org/