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COHCAP: an integrative genomic pipeline for single-nucleotide resolution DNA methylation analysis.

Warden CD, Lee H, Tompkins JD, Li X, Wang C, Riggs AD, Yu H, Jove R, Yuan YC - Nucleic Acids Res. (2013)

Bottom Line: COHCAP is currently the only DNA methylation package that provides integration with gene expression data to identify a subset of CpG islands that are most likely to regulate downstream gene expression, and it can generate lists of differentially methylated CpG islands with ∼50% concordance with gene expression from both cell line data and heterogeneous patient data.For example, this article describes known breast cancer biomarkers (such as estrogen receptor) with a negative correlation between DNA methylation and gene expression.COHCAP also provides visualization for quality control metrics, regions of differential methylation and correlation between methylation and gene expression.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics Core, City of Hope National Medical Center, Duarte, CA 91010, USA. cwarden@coh.org

ABSTRACT
COHCAP (City of Hope CpG Island Analysis Pipeline) is an algorithm to analyze single-nucleotide resolution DNA methylation data produced by either an Illumina methylation array or targeted bisulfite sequencing. The goal of the COHCAP algorithm is to identify CpG islands that show a consistent pattern of methylation among CpG sites. COHCAP is currently the only DNA methylation package that provides integration with gene expression data to identify a subset of CpG islands that are most likely to regulate downstream gene expression, and it can generate lists of differentially methylated CpG islands with ∼50% concordance with gene expression from both cell line data and heterogeneous patient data. For example, this article describes known breast cancer biomarkers (such as estrogen receptor) with a negative correlation between DNA methylation and gene expression. COHCAP also provides visualization for quality control metrics, regions of differential methylation and correlation between methylation and gene expression. This software is freely available at https://sourceforge.net/projects/cohcap/.

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COHCAP workflows for integrative genomic analysis. (A) Average by Site workflow: CpG sites showing differential methylation are selected, and the average beta values for the two groups shown (red versus blue) are calculated per CpG site. Next, the consistency of signal between CpG sites within a CpG island is quantified to determine regions showing significant differential methylation. Finally, if the user has a corresponding gene expression dataset, COHCAP looks for differentially expressed genes that show inverse overlap with differentially methylated regions (e.g. increased methylation with decreased expression, and decreased methylation with increased expression). (B) Average within CpG Island workflow: this is the default workflow for COHCAP. CpG sites showing differential methylation are selected, and the average beta values are calculated for significant sites within a CpG island for each sample. Next, these averaged beta values for each CpG island are compared for the samples between the two groups (red versus blue). If the user has paired gene expression data, integration is performed by looking for a significant negative correlation between beta values and gene expression levels.
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gkt242-F1: COHCAP workflows for integrative genomic analysis. (A) Average by Site workflow: CpG sites showing differential methylation are selected, and the average beta values for the two groups shown (red versus blue) are calculated per CpG site. Next, the consistency of signal between CpG sites within a CpG island is quantified to determine regions showing significant differential methylation. Finally, if the user has a corresponding gene expression dataset, COHCAP looks for differentially expressed genes that show inverse overlap with differentially methylated regions (e.g. increased methylation with decreased expression, and decreased methylation with increased expression). (B) Average within CpG Island workflow: this is the default workflow for COHCAP. CpG sites showing differential methylation are selected, and the average beta values are calculated for significant sites within a CpG island for each sample. Next, these averaged beta values for each CpG island are compared for the samples between the two groups (red versus blue). If the user has paired gene expression data, integration is performed by looking for a significant negative correlation between beta values and gene expression levels.

Mentions: COHCAP is a pipeline that covers most user needs for differential methylation and integration with gene expression data (Figure 1, Supplementary Figure S1 and S2; Supplementary Table S1). This includes quality control metrics, defining differentially methylated CpG sites, defining differentially methylated CpG islands and visualization of methylation data. Although IMA has one method for providing statistics for differentially methylated regions, COHCAP contains two different methods of CpG island analysis. With the exception of MethLAB (25), COHCAP is the only algorithm to provide a graphical user interface for users without programming experience. Additionally, COHCAP is the only package with flexible analysis of one-group (or more-than-two-group) comparisons. Finally, bisulfite sequencing (BS-Seq) is another method of measuring methylation of CpG sites (32,33), and there are some methods to assist with analysis of BS-Seq data (34,35). However, COHCAP is the only package designed to analyze either Illumina methylation array or BS-Seq data.Figure 1.


COHCAP: an integrative genomic pipeline for single-nucleotide resolution DNA methylation analysis.

Warden CD, Lee H, Tompkins JD, Li X, Wang C, Riggs AD, Yu H, Jove R, Yuan YC - Nucleic Acids Res. (2013)

COHCAP workflows for integrative genomic analysis. (A) Average by Site workflow: CpG sites showing differential methylation are selected, and the average beta values for the two groups shown (red versus blue) are calculated per CpG site. Next, the consistency of signal between CpG sites within a CpG island is quantified to determine regions showing significant differential methylation. Finally, if the user has a corresponding gene expression dataset, COHCAP looks for differentially expressed genes that show inverse overlap with differentially methylated regions (e.g. increased methylation with decreased expression, and decreased methylation with increased expression). (B) Average within CpG Island workflow: this is the default workflow for COHCAP. CpG sites showing differential methylation are selected, and the average beta values are calculated for significant sites within a CpG island for each sample. Next, these averaged beta values for each CpG island are compared for the samples between the two groups (red versus blue). If the user has paired gene expression data, integration is performed by looking for a significant negative correlation between beta values and gene expression levels.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3675470&req=5

gkt242-F1: COHCAP workflows for integrative genomic analysis. (A) Average by Site workflow: CpG sites showing differential methylation are selected, and the average beta values for the two groups shown (red versus blue) are calculated per CpG site. Next, the consistency of signal between CpG sites within a CpG island is quantified to determine regions showing significant differential methylation. Finally, if the user has a corresponding gene expression dataset, COHCAP looks for differentially expressed genes that show inverse overlap with differentially methylated regions (e.g. increased methylation with decreased expression, and decreased methylation with increased expression). (B) Average within CpG Island workflow: this is the default workflow for COHCAP. CpG sites showing differential methylation are selected, and the average beta values are calculated for significant sites within a CpG island for each sample. Next, these averaged beta values for each CpG island are compared for the samples between the two groups (red versus blue). If the user has paired gene expression data, integration is performed by looking for a significant negative correlation between beta values and gene expression levels.
Mentions: COHCAP is a pipeline that covers most user needs for differential methylation and integration with gene expression data (Figure 1, Supplementary Figure S1 and S2; Supplementary Table S1). This includes quality control metrics, defining differentially methylated CpG sites, defining differentially methylated CpG islands and visualization of methylation data. Although IMA has one method for providing statistics for differentially methylated regions, COHCAP contains two different methods of CpG island analysis. With the exception of MethLAB (25), COHCAP is the only algorithm to provide a graphical user interface for users without programming experience. Additionally, COHCAP is the only package with flexible analysis of one-group (or more-than-two-group) comparisons. Finally, bisulfite sequencing (BS-Seq) is another method of measuring methylation of CpG sites (32,33), and there are some methods to assist with analysis of BS-Seq data (34,35). However, COHCAP is the only package designed to analyze either Illumina methylation array or BS-Seq data.Figure 1.

Bottom Line: COHCAP is currently the only DNA methylation package that provides integration with gene expression data to identify a subset of CpG islands that are most likely to regulate downstream gene expression, and it can generate lists of differentially methylated CpG islands with ∼50% concordance with gene expression from both cell line data and heterogeneous patient data.For example, this article describes known breast cancer biomarkers (such as estrogen receptor) with a negative correlation between DNA methylation and gene expression.COHCAP also provides visualization for quality control metrics, regions of differential methylation and correlation between methylation and gene expression.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics Core, City of Hope National Medical Center, Duarte, CA 91010, USA. cwarden@coh.org

ABSTRACT
COHCAP (City of Hope CpG Island Analysis Pipeline) is an algorithm to analyze single-nucleotide resolution DNA methylation data produced by either an Illumina methylation array or targeted bisulfite sequencing. The goal of the COHCAP algorithm is to identify CpG islands that show a consistent pattern of methylation among CpG sites. COHCAP is currently the only DNA methylation package that provides integration with gene expression data to identify a subset of CpG islands that are most likely to regulate downstream gene expression, and it can generate lists of differentially methylated CpG islands with ∼50% concordance with gene expression from both cell line data and heterogeneous patient data. For example, this article describes known breast cancer biomarkers (such as estrogen receptor) with a negative correlation between DNA methylation and gene expression. COHCAP also provides visualization for quality control metrics, regions of differential methylation and correlation between methylation and gene expression. This software is freely available at https://sourceforge.net/projects/cohcap/.

Show MeSH
Related in: MedlinePlus