Microarray analysis of gene expression: considerations in data mining and statistical treatment

Verducci, Joseph S.; Melfi, Vincent; Lin, Shili; Wang, Zailong; Roy, Sashwati; Sen, Chandan K.

doi:10.1152/physiolgenomics.00314.2004

Cited by 66 publications

(50 citation statements)

References 64 publications

(57 reference statements)

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“…The arrays were washed, stained with streptavidinphycoerythrin and scanned with the GeneArray scanner (Affymetrix) in our own facilities as described in refs. [21][22][23][24][25]. Data analyses.…”

Section: Lmpc Of Tissuementioning

confidence: 99%

“…Raw data were collected and analyzed by using Stratagene ArrayAssist Expression software, Version 5.1 (Stratagene). Additional processing of data were performed by using dChip software, Version 1.3 (Harvard University, Cambridge, MA) (24). Data acquisition and image processing was performed by using Gene Chip Operating Software (Affymetrix).…”

Section: Lmpc Of Tissuementioning

confidence: 99%

“…Data normalization and background corrections were performed by using GC-RMA. Differentially expressed genes were identified by using a two-class t test where significance level was set at P Ͼ 0.05 with Benjamin-Hochberg false discovery rate correction (24). Genes that were Ͼ1.5 fold up-or down-regulated compared with skin sample were selected.…”

Section: Lmpc Of Tissuementioning

confidence: 99%

See 2 more Smart Citations

Transcriptome-wide analysis of blood vessels laser captured from human skin and chronic wound-edge tissue

Roy

Patel

Khanna

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

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105

131

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Chronic wounds represent a substantial public health problem. The development of tools that would enable sophisticated scrutiny of clinical wound tissue material is highly desirable. This work presents evidence enabling rapid specific identification and laser capture of blood vessels from human tissue in a manner which lends itself to successful high-density (U133A) microarray analysis. Such screening of transcriptome followed by real-time PCR and immunohistochemical verification of candidate genes and their corresponding products were performed by using 3 mm biopsies. Of the 18,400 transcripts and variants screened, a focused set of 53 up-regulated and 24 down-regulated genes were noted in woundderived blood vessels compared with blood vessels from intact human skin. The mean abundance of periostin in wound-site blood vessels was 96-fold higher. Periostin is known to be induced in response to vascular injury and its expression is associated with smooth muscle cell differentiation in vitro and promotes cell migration. Forty-fold higher expression of heparan sulfate 6-Oendosulfatase1 (Sulf1) was noted in wound-site vessels. Sulf1 has been recently recognized to be anti-angiogenic. During embryonic vasculogenesis, CD24 expression is down-regulated in human embryonic stem cells. Wound-site vessels had lower CD24 expression. The findings of this work provide a unique opportunity to appreciate the striking contrast in the transcriptome composition in blood vessels collected from the intact skin and from the wound-edge tissue. Sets of genes with known vascular functions but never connected to wound healing were identified to be differentially expressed in wound-derived blood vessels paving the way for innovative clinically relevant hypotheses.angiogenesis ͉ microarray ͉ wound healing

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Section: Lmpc Of Tissuementioning

confidence: 99%

Section: Lmpc Of Tissuementioning

confidence: 99%

Section: Lmpc Of Tissuementioning

confidence: 99%

See 1 more Smart Citation

Transcriptome-wide analysis of blood vessels laser captured from human skin and chronic wound-edge tissue

Roy

Patel

Khanna

et al. 2007

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

105

131

View full text Add to dashboard Cite

show abstract

“…As such, fold change has often been used. However, fold change is not a reliable measure because it does not take variability in the data into account (2,48). Therefore, other measures that do take variability into consideration should be used.…”

Section: Gene Rankingmentioning

confidence: 99%

A framework to identify physiological responses in microarray-based gene expression studies: selection and interpretation of biologically relevant genes

Rodenburg

Heidema

Boer

et al. 2008

Physiological Genomics

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“…A high-throughput microarray experiment has been designed to analyze genetic expression patterns and identify potential genes to target HF (Xu et al, 2011). Genomic expression profiling has also evolved as a useful tool for identifying novel pathomechanisms in human cardiac disorders (Verducci et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Transcriptome network analysis of potential candidate genes for heart failure

Chen¹,

Wang²,

Zeng³

2013

Genet. Mol. Res.

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ABSTRACT. The purpose of this study was to examine the hypothesis that a transcriptome network can be developed through a set of transcription factors regulated by the expression of various genes induced by dilated cardiomyopathy can be identified and modulated to respond to heart failure. We searched for significant pathways related to dilated cardiomyopathy using the GSE4172 microarray data to identify potential genes related to heart failure. We mapped differentially expressed genes to pathways and constructed a regulation network to investigate the regulatory relationships between transcription factors and pathways. Some transcription factors and target genes in the networks have been clearly linked to heart failure in previous studies. We also found new transcription factors and target genes, such as CCAAT/ enhancer-binding protein delta and JunB, responsible for inflammatory cardiomyopathy. Transcriptome network analysis was useful in the identification of candidate genes in heart failure. This method is well suited for microarray data and therefore is proposed as a powerful tool in the search for new pathways related to disease.

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Microarray analysis of gene expression: considerations in data mining and statistical treatment

Cited by 66 publications

References 64 publications

Transcriptome-wide analysis of blood vessels laser captured from human skin and chronic wound-edge tissue

Transcriptome-wide analysis of blood vessels laser captured from human skin and chronic wound-edge tissue

A framework to identify physiological responses in microarray-based gene expression studies: selection and interpretation of biologically relevant genes

Transcriptome network analysis of potential candidate genes for heart failure

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