Evidence map›Paper›PMID 19545372›Full record

ArticleBMC bioinformatics2009

Platform dependence of inference on gene-wise and gene-set involvement in human lung development.

Rose Du, Kelan Tantisira, Vincent Carey, Soumyaroop Bhattacharya, Stephanie Metje, Alvin T Kho, Barbara J Klanderman, Roger Gaedigk, Ross Lazarus, Thomas J Mariani and 2 more

Abstract read
In one paragraph

Article in BMC bioinformatics, 2009. 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

12 authors.

Rose DuChanning Laboratory, Brigham and Women's Hospital, Boston, MA 02115, USA. rdu@partners.org
Kelan Tantisira
Vincent Carey
Soumyaroop Bhattacharya
Stephanie Metje
Alvin T Kho
Barbara J Klanderman
Roger Gaedigk
Ross Lazarus
Thomas J Mariani
J Steven Leeder
Scott T Weiss

Funding

THE PHARMACOGENETICS OF ASTHMA TREATMENTU01HL065899 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI TANTISIRA, KELAN G, WEISS, SCOTT T · 2000 to 2014
$38.5M
PHARMACOGENETIC DETERMINANTS OF HUMAN BIRTH DEFECTSR01ES010855 · NIEHS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI MITCHELL, ALLEN A · 2000 to 2004
$3.6M
A Developmental Basis for Chronic Obstructive Lung DiseaseK25HL091124 · NHLBI · BOSTON CHILDREN'S HOSPITAL · PI KHO, ALVIN THONG-JUAK · 2008 to 2012
$743k
Pharmacogenetic Linkage of Corticosteroid Response: Asthma Therapy ImplicationsK23HG003983 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI TANTISIRA, KELAN G · 2006 to 2008
$485k
NHGRI NIH HHS K23 HG003983NHGRI NIH HHS K23 HG3983NHLBI NIH HHS K25 HL091124NHLBI NIH HHS U01 HL065899NHLBI NIH HHS U01 HL65899NIEHS NIH HHS R01 ES010855NIEHS NIH HHS R01 ES10855
6 · The paper itself

Abstract

backgroundWith the recent development of microarray technologies, the comparability of gene expression data obtained from different platforms poses an important problem. We evaluated two widely used platforms, Affymetrix U133 Plus 2.0 and the Illumina HumanRef-8 v2 Expression Bead Chips, for comparability in a biological system in which changes may be subtle, namely fetal lung tissue as a function of gestational age.

resultsWe performed the comparison via sequence-based probe matching between the two platforms. "Significance grouping" was defined as a measure of comparability. Using both expression correlation and significance grouping as measures of comparability, we demonstrated that despite overall cross-platform differences at the single gene level, increased correlation between the two platforms was found in genes with higher expression level, higher probe overlap, and lower p-value. We also demonstrated that biological function as determined via KEGG pathways or GO categories is more consistent across platforms than single gene analysis.

conclusionWe conclude that while the comparability of the platforms at the single gene level may be increased by increasing sample size, they are highly comparable ontologically even for subtle differences in a relatively small sample size. Biologically relevant inference should therefore be reproducible across laboratories using different platforms.

Indexed as

Computational BiologyGene Expression ProfilingHumansLung

Identifiers

PMID19545372
PMCPMC2711081

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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.