COHCAP GUI is an accessible and reliable software that makes use of the City of Hope CpG Island Analysis Pipeline algorithm to analyze single-nucleotide resolution methylation data.
COHCAP GUI is a tool that manages to provide differential methylation for CpG Sites / Islands, QC metrics and integration with gene expression data.
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COHCAP GUI Features
COHCAP GUI is a web application that provides users with a dynamic
web interface to analyze CpG Island (CGI) data.
COHCAP GUI Description:
The tool allows users to analyze multi-sample methylation data at a
single nucleotide resolution, and to browse, search and select data.
Multi-sample analysis is possible through COHCAP GUI’s export and import functions.
Data can be imported from CHAMP ([1]) or a local binary file which COHCAP GUI will process. After importing, multi-sample data can be filtered by selecting one or more samples (samples can be selected by GO-term ([2]), tags ([3]), by variant ([4]) or matching the sample name to a string).
Manual quality control (QC) of the sample data can be performed by inspecting histogram graphs (using the select box at the bottom of the page) and inspecting bar-plots (an example of this can be seen in the web application example).
Differential methylation is provided through this module as well. Methylation levels can be selected by the sample name (GO-term), or they can be specified by set(s) of CpG Sites ([5]), CGIs ([6]) or FuncGenes ([7]) in the name of each file.
There is an option to save the methylation data, which provides an exported HTML file. This HTML file can be saved with the functionality ‘Export All Data’. This file can be loaded into any other software to show the data.
If gene expression data is available, it can be integrated into this analysis. This functionality is accomplished via a relationship that links a FuncGene to a gene expression file. To achieve this, the name of the FuncGene/FuncGene_ID is linked to the gene symbol of the gene expression file. If no gene expression data is available, the analysis is kept separate.
Users can explore or search the methylation data within this module. First, based on Gene Symbol ([8]), GO-term ([9]) or variant ([10]) selected, the methylation data is shown.
Additionally, users can search the methylation data by a specific CpG Island ([11]), or based on the CpG Island Summary ([12]). The methylation data can be explored by passing the CpG Island name to the FindCGI button.
For a complete list of
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CpG Island Analysis Pipeline (ciAP) algorithm for the analysis of high-resolution single-nucleotide resolution data from Illumina’s platform. For accurate quantification of the methylation states of CpG sites, a preprocessing is required to remove low-quality reads and adjust biases in the original data sets. This might introduce a bias in the methylation of CpG sites, either by calling “CpGs” as “not methylated”, or by calling “CpG island” as “unmethylated”. This step is performed by the COHCAP GUI Crack For Windows. There are some settings that can be selected to select the best data within the selected file (CLINICAL\_SINGLE_FILE.1.txt) and choose between methods with several options. Once the data are filtered, COHCAP GUI Cracked Accounts offers a clustering of CpGs. The clustering of CpGs is performed to remove duplicates or potential errors in the identified CpG sites. Based on the methodology used, COHCAP GUI offers several integration strategies, according to the users’ preference. These integration strategies provide the chance to perform a visualization of the results in a heat map with the presence/absence of methylation along the rows and a dendrogram for the selected CpGs (or a selected CpG class). The heat map can be performed with average, non-detected or detected methylation results. The following optional strategies can be selected to perform the clustering:
1. clustering by average methylation;
2. clustering by detected methylation;
3. clustering by non-detected methylation;
4. clustering by non-detected methylation of a selected CpG site.
Each clustering method includes the following steps:
1. normalization according to the library size;
2. integration of the CpGs that are identified to belong to the same cluster;
3. estimate the average methylation of the CpG sites within the cluster;
4. estimate the variance of the methylation of the CpG sites of the clusters.
The heterogeneity of the methylation states of the CpG sites may be visualized by dendrograms, where a hierarchical clustering can be performed, allowing to view the data as a tree. The user can select the number of groups that are to be selected to plot the dendrogram. The dendrogram can be calculated by the Cp
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What’s New in the COHCAP GUI?
COHCAP GUI is a tool that allows a user to perform a whole chromosome and single gene analysis.
COHCAP GUI supports single and pair wise comparison of sample groups allowing a user to compare two groups such as different cancer types.
COHCAP GUI reports the methylation status of individual CpG sites, Cytobands, corresponding gene information, and also indicates the differential methylation status in a pairwise comparison between groups.
COHCAP GUI Features:
● Allows methylation level of individual CpG sites, Cytoband level
● Allows individual CpG sites to be extracted and analyzed by Segmentation tab
● Supports pairwise comparison of two groups (e.g. tumor vs. normal)
● Detects differential methylation for individual CpG sites
● Detects differential methylation for Cytobands
● Analyzes gene expression data from two groups and compares gene expression data with methylation data
Goals and Features
COHCAP GUI supports any basic or advanced bioinformatics analysis that contains a whole chromosome and single gene methylation study and aims to find the differentially methylated loci between groups. COHCAP GUI facilitates the user to obtain interactive outputs, namely, methylation sites (whole chromosome, cytoband, individual CpG site and gene level), differential methylation detection and associated gene expression analysis.
COHCAP GUI was designed with the following goals in mind:
High-throughput analysis for many samples
Smallest file size for faster data transfer (especially over the internet)
Reliable user interface
Create interactive outputs for data analysis results
Interactive inspection of data at different levels
Applied Pipeline
COHCAP GUI is based on the CpG Island Analysis Pipeline by the City of Hope. The goal of the pipeline is to accurately identify and track non-CG methylated regions based on single-base resolution data across the entire human genome. COHCAP GUI takes the output of this tool and provides new interpretations and visualizations. The pipeline is made possible because the COHCAP GUI is a uniquely designed interface, application, and implementation to make use of the exact same code that runs the pipeline but simply provides new interpretations.
Background
Methylation refers to the covalent attachment of a methyl group to the 5′ carbon on cytosines. Non-CG methylation occurs only as part of a dinucleotide; with the exception
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