Evidence map›Paper›PMID 26217107›Full record

ArticleGenomics insights2013

Inter-Laboratory Variability in Array-Based RNA Quantification Methods.

Victoria Y Wong, Manuel X Duval

Abstract read
In one paragraph

Article in Genomics insights, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Victoria Y WongPfizer Global Research and Development, External Research solutions Groton CT 06333, USA.
Manuel X DuvalUniversity of New Haven, West Haven, CT 06516, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ribonucleic acids (RNA) are hypothesized to have preceded their derivatives, deoxyribonucleic acids (DNA), as the molecular media of genetic information when life emerged on earth. Molecular biologists are accustomed to the dramatic effects a subtle variation in the ribose moiety composition between RNA and DNA can have on the stability of these molecules. While DNA is very stable after extraction from biological samples and subsequent treatment, RNA is notoriously labile. The short half-life property, inherent to RNA, benefits cells that do not need to express their entire repertoire of proteins. The cellular machinery turns off the production of a given protein by shutting down the transcription of its cognate coding gene and by either actively degrading the remaining mRNA or allowing it to decay on its own. The steady-state level of each mRNA in a given cell varies continuously and is specified by changing kinetics of synthesis and degradation. Because it is technically possible to simultaneously measure thousands of nucleic acid molecules, these quantities have been studied by the life sciences community to investigate a range of biological problems. Since the RNA abundance can change according to a wide range of perturbations, this makes it the molecule of choice for exploring biological systems; its instability, on the other hand, could be an underestimated source of technical variability. We found that a large fraction of the RNA abundance originally present in the biological system prior to extraction was masked by the RNA labeling and measurement procedure. The method used to extract RNA molecules from cells and to label them prior to hybridization operations on DNA arrays affects the original distribution of RNA. Only if RNA measurements are performed according to the same procedure can biological information be inferred from the assay read out.

Indexed as

DNA arrayprincipal component analysesreproducibilitytechnical variabilitytranscriptomics

Identifiers

PMID26217107
PMCPMC4510603

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.