Evidence map›Paper›PMID 29028866›Full record

ArticleBriefings in functional genomics2018

Global and targeted approaches to single-cell transcriptome characterization.

Aleksandra A Kolodziejczyk, Tapio Lönnberg

Abstract read
In one paragraph

Article in Briefings in functional genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Single-cell multi-omics in the study of digestive system cancers.Computational and structural biotechnology journal · 2024
    Review
  4. Review
  5. A miR-34a-guided, tRNACell death discovery · 2022
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Evolution of Drug-ResistantFrontiers in microbiology · 2021
    Review
  13. Article
  14. Article
  15. Review
  16. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Aleksandra A KolodziejczykWellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
Tapio LönnbergWellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analysing transcriptomes of cell populations is a standard molecular biology approach to understand how cells function. Recent methodological development has allowed performing similar experiments on single cells. This has opened up the possibility to examine samples with limited cell number, such as cells of the early embryo, and to obtain an understanding of heterogeneity within populations such as blood cell types or neurons. There are two major approaches for single-cell transcriptome analysis: quantitative reverse transcription PCR (RT-qPCR) on a limited number of genes of interest, or more global approaches targeting entire transcriptomes using RNA sequencing. RT-qPCR is sensitive, fast and arguably more straightforward, while whole-transcriptome approaches offer an unbiased perspective on a cell's expression status.

Indexed as

Gene Expression ProfilingReverse Transcriptase Polymerase Chain ReactionSequence Analysis, RNASingle-Cell Analysis

Identifiers

PMID29028866
PMCPMC6063303

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.