Evidence map›Paper›PMID 38194038›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Patch-seq: Multimodal Profiling of Single-Cell Morphology, Electrophysiology, and Gene Expression.

Cathryn R Cadwell, Andreas S Tolias

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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.

Cathryn R CadwellDepartments of Neurological Surgery and Pathology, School of Medicine, University of California San Francisco, San Francisco, CA, USA. Cathryn.Cadwell@ucsf.edu.
Andreas S ToliasDepartment of Neuroscience, Baylor College of Medicine, Houston, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cells exhibit diverse morphologic phenotypes, biophysical and functional properties, and gene expression patterns. Understanding how these features are interrelated at the level of single cells has been challenging due to the lack of techniques for multimodal profiling of individual cells. We recently developed Patch-seq, a technique that combines whole-cell patch clamp recording, immunohistochemistry, and single-cell RNA-sequencing (scRNA-seq) to comprehensively profile single cells. Here we present a detailed step-by-step protocol for obtaining high-quality morphological, electrophysiological, and transcriptomic data from single cells. Patch-seq enables researchers to explore the rich, multidimensional phenotypic variability among cells and to directly correlate gene expression with phenotype at the level of single cells.

Indexed as

Gene Expression ProfilingTranscriptomeBiophysicsElectrophysiologyPatch-Clamp TechniquesCell typeElectrophysiologyMorphologyPatch clampPatch-seqSingle-cell RNA-sequencingTranscriptomicsWhole-cell recording

Identifiers

PMID38194038

What OpenQuestion holds

Textmetadata
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.