↓ Skip to main content

Single Cell Transcriptomics

Overview of attention for book
Cover of 'Single Cell Transcriptomics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Guidance on Processing the 10x Genomics Single Cell Gene Expression Assay
  3. Altmetric Badge
    Chapter 2 BD Rhapsody™ Single-Cell Analysis System Workflow: From Sample to Multimodal Single-Cell Sequencing Data
  4. Altmetric Badge
    Chapter 3 Profiling Transcriptional Heterogeneity with Seq-Well S3: A Low-Cost, Portable, High-Fidelity Platform for Massively Parallel Single-Cell RNA-Seq
  5. Altmetric Badge
    Chapter 4 A MATQ-seq-Based Protocol for Single-Cell RNA-seq in Bacteria
  6. Altmetric Badge
    Chapter 5 Full-Length Single-Cell RNA-Sequencing with FLASH-seq
  7. Altmetric Badge
    Chapter 6 Plant Single-Cell/Nucleus RNA-seq Workflow
  8. Altmetric Badge
    Chapter 7 Ensuring Quality Cell Input for Single Cell Sequencing Experiments by Viability and Singlet Enrichment Using Cell Sorting
  9. Altmetric Badge
    Chapter 8 Tissue RNA Integrity in Visium Spatial Protocol (Fresh Frozen Samples)
  10. Altmetric Badge
    Chapter 9 Single-Cell RNAseq Data QC and Preprocessing
  11. Altmetric Badge
    Chapter 10 Single-Cell RNAseq Complexity Reduction
  12. Altmetric Badge
    Chapter 11 Functional-Feature-Based Data Reduction Using Sparsely Connected Autoencoders
  13. Altmetric Badge
    Chapter 12 Single-Cell RNAseq Clustering
  14. Altmetric Badge
    Chapter 13 Identifying Gene Markers Associated with Cell Subpopulations
  15. Altmetric Badge
    Chapter 14 A Guide to Trajectory Inference and RNA Velocity
  16. Altmetric Badge
    Chapter 15 Integration of scATAC-Seq with scRNA-Seq Data
  17. Altmetric Badge
    Chapter 16 Using “Galaxy-rCASC”: A Public Galaxy Instance for Single-Cell RNA-Seq Data Analysis
  18. Altmetric Badge
    Chapter 17 Bringing Cell Subpopulation Discovery on a Cloud-HPC Using rCASC and StreamFlow
  19. Altmetric Badge
    Chapter 18 Profiling RNA Editing in Single Cells
  20. Altmetric Badge
    Chapter 19 Practical Considerations for Complex Tissue Dissociation for Single-Cell Transcriptomics
Attention for Chapter 6: Plant Single-Cell/Nucleus RNA-seq Workflow
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

blogs
1 blog
twitter
1 X user

Citations

dimensions_citation
2 Dimensions

Readers on

mendeley
3 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
Plant Single-Cell/Nucleus RNA-seq Workflow
Chapter number 6
Book title
Single Cell Transcriptomics
Published in
Methods in molecular biology, December 2022
DOI 10.1007/978-1-0716-2756-3_6
Pubmed ID
Book ISBNs
978-1-07-162755-6, 978-1-07-162756-3
Authors

Thibivilliers, Sandra, Farmer, Andrew, Schroeder, Susan, Libault, Marc, Sandra Thibivilliers, Andrew Farmer, Susan Schroeder, Marc Libault

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Unknown 2 67%
Readers by discipline Count As %
Agricultural and Biological Sciences 1 33%
Unknown 2 67%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 13 December 2022.
All research outputs
#3,843,518
of 23,344,526 outputs
Outputs from Methods in molecular biology
#961
of 13,338 outputs
Outputs of similar age
#72,358
of 437,098 outputs
Outputs of similar age from Methods in molecular biology
#26
of 386 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,338 research outputs from this source. They receive a mean Attention Score of 3.4. 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 437,098 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 386 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.