Evidence map›Paper›PMID 24270603›Full record

ArticleNature methods2014

Quantifying RNA allelic ratios by microfluidic multiplex PCR and sequencing.

Rui Zhang, Xin Li, Gokul Ramaswami, Kevin S Smith, Gustavo Turecki, Stephen B Montgomery, Jin Billy Li

Abstract read
In one paragraph

Article in Nature methods, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.

0numbers the graph read from it
0cells of the map it votes in
57citing 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

57 citing papers in PubMed.

  1. Review
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  10. Quantitative Analysis of Adenosine-to-Inosine RNA Editing.Methods in molecular biology (Clifton, N.J.) · 2021
    Article
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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

7 authors.

Rui ZhangDepartment of Genetics, Stanford University, Stanford, California, USA.
Xin LiDepartment of Pathology, Stanford University, Stanford, California, USA.
Gokul RamaswamiDepartment of Genetics, Stanford University, Stanford, California, USA.
Kevin S SmithDepartment of Pathology, Stanford University, Stanford, California, USA.
Gustavo TureckiMcGill Group for Suicide Studies, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada.
Stephen B Montgomery1] Department of Genetics, Stanford University, Stanford, California, USA. [2] Department of Pathology, Stanford University, Stanford, California, USA.
Jin Billy LiDepartment of Genetics, Stanford University, Stanford, California, USA.ORCID 0000000307131399

Funding

INSTITUTIONAL TRAINING GRANT IN GENOME SCIENCET32HG000044 · NHGRI · STANFORD UNIVERSITY · PI MICHAEL P. SNYDER · 1995 to 2026
$32.2M
Profiling and Dissecting the Dynamic Regulation of RNA EditingR01GM102484 · NIGMS · STANFORD UNIVERSITY · PI LI, JIN BILLY · 2013 to 2021
$3.1M
NHGRI NIH HHS T32 HG000044NIGMS NIH HHS GM102484NIGMS NIH HHS R01 GM102484
6 · The paper itself

Abstract

We developed a targeted RNA sequencing method that couples microfluidics-based multiplex PCR and deep sequencing (mmPCR-seq) to uniformly and simultaneously amplify up to 960 loci in 48 samples independently of their gene expression levels and to accurately and cost-effectively measure allelic ratios even for low-quantity or low-quality RNA samples. We applied mmPCR-seq to RNA editing and allele-specific expression studies. mmPCR-seq complements RNA-seq for studying allelic variations in the transcriptome.

Indexed as

AllelesBrainDNA Barcoding, TaxonomicDNA, ComplementaryGene Expression ProfilingGenotypeHigh-Throughput Nucleotide SequencingHumansMultiplex Polymerase Chain ReactionReproducibility of ResultsReverse Transcriptase Polymerase Chain ReactionRNARNA EditingSequence Analysis, RNATranscriptomeDNA, ComplementaryRNA

Identifiers

PMID24270603
PMCPMC3877737

What OpenQuestion holds

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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.