Introduction
The aim of ColPortal is to provide an open web platform in which users can analyze, visualize and download clinical and omics data in an integrated way. One of the main features of this application is the possibility of making integrated analyses in real time. It has been developed using Java and R technologies.
The following document is an aid for the user to navigate through this web portal.
Home
Home page is the access tab to the different omics analysis, such as ‘Methylome’, ‘Microbiome’, ‘Transcriptome’ and ‘MicroTranscriptome’ options. In addition, the user may access from there the clinical data included in the different studies and different omic analyses, located in ‘Clinical cases’. From ‘Molecular Features’, it is also possible to obtain information about the amount of samples analyzed under different omics.
Clinical cases
This view shows a summary of clinical cases. Many filters can be set to obtain clinical cases that match desired conditions. In the ‘Aggregated view’, the distribution of each variable is displayed on a pie chart.
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| Aggregated View |
The ‘List view’ option shows detailed information of each clinical case.
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| List View |
Finally, in the ‘Aggregated view’, multiple correspondence analysis (MCA) can be performed by selecting one or several variables as classes, to be differentiated by colour and two or more variables to calculate the suitable statistical analysis.
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| MCA plot |
Molecular features
This view provides information about the number of samples shared by, at least, two selected clinical and/or molecular features. It is necessary to click on ‘Compare’ button to obtain the report. The shared samples for all data combinations would be shown below.
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| Molecular Features |
Methylome
This view has three tabs:
- Methylome Analysis. The user can filter by methylated region relative to gene – 3’UTR, TSS200, 5’UTR, 1stExon, TSS1500 or body –, region related to CpG island – Island, shore, self, open sea –, FDR (adjusted p-value) and log2FC, to obtain differentially methylated genes (DMG). Then, it is possible to select those interested genes for further analysis.
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| Methylome Analysis tab |
- Methylome Gene Visualization. The user can filter, not only by technical methylation parameters, but also by clinical parameters to obtain DMG. Individual gene name should be provided for this tool to work.
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| Methylation plots |
- Genes selected. Methylation level from previously selected genes in ‘Methylome Analysis’ tab can be visualized through a box plot for each probe and separated by status (normal vs tumoral).
Microbiome
In this view a cohort of patients can be selected by means of filters to obtain microbiome abundance data and differentialy methylated genes from this patiens.
When the cohort is selected, it is necessary to indicate the maximum and/or minimum abundance and click on ‘Filter genus’.
In addition, the user must to click on ‘Show differentially methylated genes’ either filtering by some criteria or without filter to get a list of DM genes from the cohort.
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| Microbiome Analysis view |
Then it is necessary to select one or several taxa and several genes to obtain a correlation plot and correlation table after clicking on ‘Correlation analysis’.
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| Microbiome correlation analysis view |
Finally, selecting one or several genus and several genes from the correlation table, a principal components analysis and a hierarchical classification with data labeled as normal or tumoral can be obtained.
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| Microbiome PCA & Clustering analysis view |
Then, by clicking on correlation analysis, a heatmap of correlation between the methylation values of the genes and the abundance levels of the different taxonomic groups selected is obtained.
A correlation table between taxa and genes is also shown.
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| Microbiome and methylome correlation plot |
Transcriptome
This view has two tabs:
- Transcriptome and methylation. There are two predetermined classes (normal and tumoral) and some filters for each status that can be set to restrict the search using ‘Generate cohort’ buttons. Assign a name to the analysis that will facilitate the reuse of it and press ‘RNA differential expression’ button. Thereupon, selected genes can be filtered based on methylation data, using the related filters. Other extra filters, such as pathways or human phenotypes (HPO) terms, can also be added. As a result, a heatmap expression per sample level and class (normal and tumoral) is shown.
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| Expression plots base on methylation values |
- Transcriptome. The user may define some parameters from the cohorts to perform a differential expression analysis in real time. It is necessary to define labels of each cohort and analysis. This view also allows to filter results by pathway, gene and/or human phenotype.
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| Expression plots |
MicroTranscriptome
Similar to transcriptome, the user defines the parameters from the cohorts to calculate a miRNA differential expression analysis in real time. It is necessary to define labels of each cohort and analysis. This view also allows to filter results by pathway, gene and/or human phenotype. Gene filter select those miRNAs that regulate, with strong evidence, selected genes.
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| Microtranscriptome plots |
Glossary
- 3’UTR
- 3’ untranslated region gene
- 1stExon
- First gene exon
- 5’UTR
- 5’ untranslated region gene
- TSS200
- Up to 200 bp from translate start site
- Body
- Region within gene
- TSS1500
- Up to 1500 bp from translate start site
- Island
- Region >200bp in length with GC percent >50%
- [N/S]_shore
- Regions up to 2kb from CpG island (upstream or downstream from CpG)
- [N/S]_self
- Regions up to 2-4 kb from CpG island (upstream or downstream from CpG)
- OpenSea
- Isolated CpGs in the genome
- Tumour budding
- dissociation of some malignant neoplastic cells from the tumour invasion front
- CIMP Ogino
- CpG Island Methylation Phenotype (evaluation method following criteria by Ogino et al.)
- CIMP Weisemberg
- CpG Island Methylation Phenotype (evaluation method following criteria by Weisemberg et al.)
- Disease Status
- disease status of sample. Possible values: tumoral, polyp and normal
- Grade
- histological tumor grade according to WHO
- MSI status
- Microsatellite Instability status
- TNM
- staging system for tumors
- T stage
- describes the tumor size and any spread of cancer into nearby tissue
- N stage
- describes spread of cancer to nearby lymph nodes
- M stage
- describe metastasis
- Tumor budding
- describes the presence of clusters of tumoral cells detaching from invasive margin of main tumor
- TB Grade
- tumor budding grade
- Type
- hystological type of the tumor