Evidence map›Paper›PMID 25649046›Full record

ArticleBioData mining2014

Integrative genomics and transcriptomics analysis of human embryonic and induced pluripotent stem cells.

Kirsti Laurila, Reija Autio, Lingjia Kong, Elisa Närvä, Samer Hussein, Timo Otonkoski, Riitta Lahesmaa, Harri Lähdesmäki

Abstract read
In one paragraph

Article in BioData mining, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. 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

8 authors.

Kirsti Laurila *Department of Information and Computer Science, Aalto University School of Science, Espoo, Finland.
Reija Autio *Department of Signal Processing, Tampere University of Technology, Tampere, Finland.
Lingjia KongDepartment of Signal Processing, Tampere University of Technology, Tampere, Finland.
Elisa NärväTurku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland.
Samer HusseinSamuel Lunenfeld Research Institute, Toronto, Canada.
Timo OtonkoskiResearch Program Unit, Molecular Neurology, Biomedicum Stem Cell Center, University of Helsinki, Helsinki, Finland.
Riitta LahesmaaTurku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland.
Harri LähdesmäkiDepartment of Information and Computer Science, Aalto University School of Science, Espoo, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHuman genomic variations, including single nucleotide polymorphisms (SNPs) and copy number variations (CNVs), are associated with several phenotypic traits varying from mild features to hereditary diseases. Several genome-wide studies have reported genomic variants that correlate with gene expression levels in various tissue and cell types.

resultsWe studied human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs) measuring the SNPs and CNVs with Affymetrix SNP 6 microarrays and expression values with Affymetrix Exon microarrays. We computed the linear relationships between SNPs and expression levels of exons, transcripts and genes, and the associations between gene CNVs and gene expression levels. Further, for a few of the resulted genes, the expression value was associated with both CNVs and SNPs. Our results revealed altogether 217 genes and 584 SNPs whose genomic alterations affect the transcriptome in the same cells. We analyzed the enriched pathways and gene ontologies within these groups of genes, and found out that the terms related to alternative splicing and development were enriched.

conclusionsOur results revealed that in the human pluripotent stem cells, the expression values of several genes, transcripts and exons were affected due to the genomic variation.

Indexed as

Association analysisCNVExon expressionGene expressionhESChiPSCSNPTranscript expression

Identifiers

PMID25649046
PMCPMC4298950

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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.