Evidence map›Paper›PMID 30453873›Full record

ArticleBMC bioinformatics2018

Expression analysis of RNA sequencing data from human neural and glial cell lines depends on technical replication and normalization methods.

V Bleu Knight, Elba E Serrano

Abstract read
In one paragraph

Article in BMC bioinformatics, 2018. 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. 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.

V Bleu KnightDepartment of Biology, New Mexico State University, Las Cruces, NM, USA.
Elba E SerranoDepartment of Biology, New Mexico State University, Las Cruces, NM, USA. serrano@nmsu.edu.

Funding

BRAiN: Building Research Achievement in NeuroscienceR25NS080685 · NINDS · UNIVERSITY OF COLORADO DENVER · PI BLAND, SONDRA T, LYONS, BARBARA A · 2012 to 2019
$3.8M
NINDS NIH HHS R25 NS080685
6 · The paper itself

Abstract

backgroundThe potential for astrocyte participation in central nervous system recovery is highlighted by in vitro experiments demonstrating their capacity to transdifferentiate into neurons. Understanding astrocyte plasticity could be advanced by comparing astrocytes with stem cells. RNA sequencing (RNA-seq) is ideal for comparing differences across cell types. However, this novel multi-stage process has the potential to introduce unwanted technical variation at several points in the experimental workflow. Quantitative understanding of the contribution of experimental parameters to technical variation would facilitate the design of robust RNA-Seq experiments.

resultsRNA-Seq was used to achieve biological and technical objectives. The biological aspect compared gene expression between normal human fetal-derived astrocytes and human neural stem cells cultured in identical conditions. When differential expression threshold criteria of |log

conclusionsThe similarity in gene expression between astrocytes and neural stem cells supports the potential for astrocytic transdifferentiation into neurons, and emphasizes the need to evaluate the therapeutic potential of astrocytes for central nervous system damage. The choice of normalization method influences the contributions to experimental variance as well as the outcomes of differential expression analysis. However irrespective of normalization method, our findings illustrate that library preparation contributed the largest component of technical variance.

Indexed as

Gene Expression RegulationBase SequenceCell LineGene Expression ProfilingHumansImaging, Three-DimensionalMetabolic Networks and PathwaysNeural Stem CellsNeurogliaNeuronsPrincipal Component AnalysisReproducibility of ResultsRNASequence Analysis, RNARNAExperimental designGliaHuman astrocytesHuman neural stem cellsNext generation sequencingNormalizationPrincipal variance component analysisRNA Seq

Identifiers

PMID30453873
PMCPMC6245503

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.