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Methods and Insights from Single-Cell Expression Quantitative Trait Loci

Overview of attention for article published in Annual Review of Genomics & Human Genetics, May 2023
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  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#30 of 388)
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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Title
Methods and Insights from Single-Cell Expression Quantitative Trait Loci
Published in
Annual Review of Genomics & Human Genetics, May 2023
DOI 10.1146/annurev-genom-101422-100437
Pubmed ID
Authors

Joyce B Kang, Alessandro Raveane, Aparna Nathan, Nicole Soranzo, Soumya Raychaudhuri

Abstract

Recent advancements in single-cell technologies have enabled expression quantitative trait locus (eQTL) analysis across many individuals at single-cell resolution. Compared with bulk RNA sequencing, which averages gene expression across cell types and cell states, single-cell assays capture the transcriptional states of individual cells, including fine-grained, transient, and difficult-to-isolate populations at unprecedented scale and resolution. Single-cell eQTL (sc-eQTL) mapping can identify context-dependent eQTLs that vary with cell states, including some that colocalize with disease variants identified in genome-wide association studies. By uncovering the precise contexts in which these eQTLs act, single-cell approaches can unveil previously hidden regulatory effects and pinpoint important cell states underlying molecular mechanisms of disease. Here, we present an overview of recently deployed experimental designs in sc-eQTL studies. In the process, we consider the influence of study design choices such as cohort, cell states, and ex vivo perturbations. We then discuss current methodologies, modeling approaches, and technical challenges as well as future opportunities and applications. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 24 is August 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

X Demographics

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The data shown below were collected from the profiles of 81 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 18%
Researcher 4 10%
Student > Bachelor 4 10%
Unspecified 3 8%
Professor 3 8%
Other 7 18%
Unknown 12 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 13 33%
Unspecified 3 8%
Agricultural and Biological Sciences 3 8%
Computer Science 2 5%
Mathematics 1 3%
Other 5 13%
Unknown 13 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 44. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 September 2023.
All research outputs
#968,243
of 25,838,141 outputs
Outputs from Annual Review of Genomics & Human Genetics
#30
of 388 outputs
Outputs of similar age
#20,045
of 395,543 outputs
Outputs of similar age from Annual Review of Genomics & Human Genetics
#1
of 9 outputs
Altmetric has tracked 25,838,141 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 388 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 21.8. This one has done particularly well, scoring higher than 92% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 395,543 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them