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Cell fixation and preservation for droplet-based single-cell transcriptomics

Overview of attention for article published in BMC Biology, May 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)

Mentioned by

blogs
2 blogs
twitter
35 tweeters
patent
1 patent
q&a
1 Q&A thread

Citations

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107 Dimensions

Readers on

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453 Mendeley
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Title
Cell fixation and preservation for droplet-based single-cell transcriptomics
Published in
BMC Biology, May 2017
DOI 10.1186/s12915-017-0383-5
Pubmed ID
Authors

Jonathan Alles, Nikos Karaiskos, Samantha D. Praktiknjo, Stefanie Grosswendt, Philipp Wahle, Pierre-Louis Ruffault, Salah Ayoub, Luisa Schreyer, Anastasiya Boltengagen, Carmen Birchmeier, Robert Zinzen, Christine Kocks, Nikolaus Rajewsky

Abstract

Recent developments in droplet-based microfluidics allow the transcriptional profiling of thousands of individual cells in a quantitative, highly parallel and cost-effective way. A critical, often limiting step is the preparation of cells in an unperturbed state, not altered by stress or ageing. Other challenges are rare cells that need to be collected over several days or samples prepared at different times or locations. Here, we used chemical fixation to address these problems. Methanol fixation allowed us to stabilise and preserve dissociated cells for weeks without compromising single-cell RNA sequencing data. By using mixtures of fixed, cultured human and mouse cells, we first showed that individual transcriptomes could be confidently assigned to one of the two species. Single-cell gene expression from live and fixed samples correlated well with bulk mRNA-seq data. We then applied methanol fixation to transcriptionally profile primary cells from dissociated, complex tissues. Low RNA content cells from Drosophila embryos, as well as mouse hindbrain and cerebellum cells prepared by fluorescence-activated cell sorting, were successfully analysed after fixation, storage and single-cell droplet RNA-seq. We were able to identify diverse cell populations, including neuronal subtypes. As an additional resource, we provide 'dropbead', an R package for exploratory data analysis, visualization and filtering of Drop-seq data. We expect that the availability of a simple cell fixation method will open up many new opportunities in diverse biological contexts to analyse transcriptional dynamics at single-cell resolution.

Twitter Demographics

The data shown below were collected from the profiles of 35 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 453 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Sweden 1 <1%
Unknown 451 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 107 24%
Researcher 107 24%
Student > Master 38 8%
Student > Bachelor 35 8%
Other 23 5%
Other 75 17%
Unknown 68 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 145 32%
Agricultural and Biological Sciences 95 21%
Neuroscience 31 7%
Medicine and Dentistry 30 7%
Immunology and Microbiology 23 5%
Other 42 9%
Unknown 87 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 35. 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 06 January 2020.
All research outputs
#617,862
of 15,786,444 outputs
Outputs from BMC Biology
#154
of 1,349 outputs
Outputs of similar age
#18,203
of 270,284 outputs
Outputs of similar age from BMC Biology
#1
of 1 outputs
Altmetric has tracked 15,786,444 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 1,349 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.6. This one has done well, scoring higher than 88% 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 270,284 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 93% of its contemporaries.
We're also able to compare this research output to 1 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