scholarly journals Erratum: Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity

Cell Research ◽  
2016 ◽  
Vol 26 (8) ◽  
pp. 967-967 ◽  
Author(s):  
Chang-lin Li ◽  
Kai-Cheng Li ◽  
Dan Wu ◽  
Yan Chen ◽  
Hao Luo ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Functional Heterogeneity ◽  
High Coverage ◽  
Single Cell Rna Sequencing

scholarly journals Somatosensory neuron types identified by high-coverage single-cell RNA-sequencing and functional heterogeneity

Cell Research ◽  
2015 ◽  
Vol 26 (1) ◽  
pp. 83-102 ◽  
Author(s):  
Chang-Lin Li ◽  
Kai-Cheng Li ◽  
Dan Wu ◽  
Yan Chen ◽  
Hao Luo ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Functional Heterogeneity ◽  
High Coverage ◽  
Single Cell Rna Sequencing

scholarly journals Deciphering the functional heterogeneity of skin fibroblasts using single‐cell RNA sequencing

2020 ◽  
Vol 34 (3) ◽  
pp. 3677-3692 ◽  
Author(s):  
Vera Vorstandlechner ◽  
Maria Laggner ◽  
Polina Kalinina ◽  
Werner Haslik ◽  
Christine Radtke ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Skin Fibroblasts ◽  
Functional Heterogeneity ◽  
Single Cell Rna Sequencing

scholarly journals Optimal design of single-cell RNA sequencing experiments for cell-type-specific eQTL analysis

2019 ◽  
Author(s):  
Igor Mandric ◽  
Tommer Schwarz ◽  
Arunabha Majumdar ◽  
Richard Perez ◽  
Meena Subramaniam ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Statistical Power ◽  
Cost Savings ◽  
Eqtl Analysis ◽  
Cell Type ◽  
Specific Expression ◽  
High Coverage ◽  
Single Cell Rna Sequencing ◽  
Cell Type Specific

AbstractSingle-cell RNA-sequencing (scRNA-Seq) is a compelling approach to simultaneously measure cellular composition and state which is impossible with bulk profiling approaches. However, it has not yet become a widely used tool in population-scale analyses, due to its prohibitively high cost. Here we show that given the same budget, the statistical power of cell-type-specific expression quantitative trait loci (eQTL) mapping can be increased through low-coverage per-cell sequencing of more samples rather than high-coverage sequencing of fewer samples. We also show that multiple experimental designs with different numbers of samples, cells per sample and reads per cell could have similar statistical power, and choosing an appropriate design can yield large cost savings especially when multiplexed workflows are considered. Finally, we provide a practical approach on selecting cost-effective designs for maximizing cell-type-specific eQTL power.

41-OR: Single Cell RNA-Sequencing Reveals the Developmental Heterogeneity of Brown Adipocytes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 41-OR
Author(s):  
FARNAZ SHAMSI ◽  
MARY PIPER ◽  
LI-LUN HO ◽  
TIAN LIAN HUANG ◽  
YU-HUA TSENG
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Brown Adipocytes ◽  
Single Cell Rna Sequencing
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