Evidence map›Paper›PMID 15850491›Full record

ArticleBMC bioinformatics2005

Redefinition of Affymetrix probe sets by sequence overlap with cDNA microarray probes reduces cross-platform inconsistencies in cancer-associated gene expression measurements.

Scott L Carter, Aron C Eklund, Brigham H Mecham, Isaac S Kohane, Zoltan Szallasi

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
7.8field-weighted citation impact, top 2% of its field
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

62 citing papers in PubMed, 130 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Meta-Analysis of Gene Expression Profiles in Acute Promyelocytic Leukemia Reveals Involved Pathways.International journal of hematology-oncology and stem cell research · 2017
    Article
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  8. Probe mapping across multiple microarray platforms.Briefings in bioinformatics · 2012
    Article
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  12. Review
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2 more citing papers are in PubMed but not listed here.

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

5 authors at 3 institutions in 1 country.

Scott L CarterChildren's Hospital Informatics Program, Harvard Medical School, Boston, MA 02115 USA. scott.carter@childrens.harvard.edu
Aron C Eklund
Brigham H Mecham
Isaac S Kohane
Zoltan Szallasi
Boston Children's Hospital · USBrigham and Women's Hospital · USHarvard University · US

Funding

Informatics for Integrating Biology/ the Bedside (RMI)U54LM008748 · NLM · BRIGHAM AND WOMEN'S HOSPITAL · PI KOHANE, ISAAC S. · 2004 to 2013
$39.0M
The Role of PlGF in Normal and Neoplastic AngiogenesisP01CA092644 · NCI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI DVORAK, HAROLD FISHER · 2002 to 2013
$17.2M
NCI NIH HHS 1PO1CA-092644-01NCI NIH HHS P01 CA092644NHLBI NIH HHS HL02-005NLM NIH HHS U54 LM008748NLM NIH HHS U54LM008748-01
6 · The paper itself

Abstract

backgroundComparison of data produced on different microarray platforms often shows surprising discordance. It is not clear whether this discrepancy is caused by noisy data or by improper probe matching between platforms. We investigated whether the significant level of inconsistency between results produced by alternative gene expression microarray platforms could be reduced by stringent sequence matching of microarray probes. We mapped the short oligo probes of the Affymetrix platform onto cDNA clones of the Stanford microarray platform. Affymetrix probes were reassigned to redefined probe sets if they mapped to the same cDNA clone sequence, regardless of the original manufacturer-defined grouping. The NCI-60 gene expression profiles produced by Affymetrix HuFL platform were recalculated using these redefined probe sets and compared to previously published cDNA measurements of the same panel of RNA samples.

resultsThe redefined probe sets displayed a substantially higher level of cross-platform consistency at the level of gene correlation, cell line correlation and unsupervised hierarchical clustering. The same strategy allowed an almost complete correspondence of breast cancer subtype classification between Affymetrix gene chip and cDNA microarray derived gene expression data, and gave an increased level of similarity between normal lung derived gene expression profiles using the two technologies. In total, two Affymetrix gene-chip platforms were remapped to three cDNA platforms in the various cross-platform analyses, resulting in improved concordance in each case.

conclusionWe have shown that probes which target overlapping transcript sequence regions on cDNA microarrays and Affymetrix gene-chips exhibit a greater level of concordance than the corresponding Unigene or sequence matched features. This method will be useful for the integrated analysis of gene expression data generated by multiple disparate measurement platforms.

Indexed as

Gene Expression RegulationGene Expression Regulation, NeoplasticBreast NeoplasmsCell Line, TumorCluster AnalysisComputational BiologyData Interpretation, StatisticalDNA, ComplementaryDNA ProbesGene ExpressionGene Expression ProfilingHumansLung NeoplasmsNeoplasmsOligonucleotide Array Sequence AnalysisPhylogenyDNA, ComplementaryDNA ProbesRNARNA, Neoplasm

Identifiers

PMID15850491
PMCPMC1127107
OpenAlexW2143953211

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.