Bioinformatics #13: UALCAN — user friendly web application for multi-omics analysis in Cancer

Multi-omics analysis is trending nowadays in order to make sure our analysis is consistent and to know our genes target connection in organisms physiology.

If you don’t know about multi-omics analysis, multi-omics is combination several biological data from genomics level (DNA, mutation), transcriptomics (mRNA, miRNA), epigenomics (methylation), proteomics (protein), and metabolomics (hormones, other chemical compounds). Actually, there are still other -omics that I don’t mention because those -omics are not mature enough such as exposomics which studies about exposure data.

Analyzing multi-omics data can’t be done by only using our local computer. It takes a lot of memory to analyze the data. Even, my laptop which has 16 GB RAM can’t finish the analysis. To solve this problem, the people usually need supercomputer or server that has a lot of memory although it’s expensive to have that facility. Luckily, there are several web applications that you can use to analyze multi-omics data and it’s user-friendly as well.

Figure 1. UALCAN user interface. Source: http://ualcan.path.uab.edu/tutorial.html

One of the best web-application for multi-omics analysis is UALCAN. It’s a portal for cancer data analysis that you can use for finding gene expression, survival analysis from mRNA, miRNA, lncRNA, and prognostic marker (Chandrashekar, et al., 2022). UALCAN has been cited more than 100 times within one year shows this web application is popular and useful in cancer research community.

Features

UALCAN has several database for cancer genes analysis (Figure 1). You can check the data from TCGA (The Cancer Genome Atlas), CPTAC (Clinical Proteomic Tumor Analysis Consortium), and CBTTC (Childhood Brain Tumor Tissue Consortium). Each database usually have different approach in collecting their data. For example, TCGA will collect the data from genomics, transcriptomics, proteomics, and metabolomics but CPTAC will only collect proteomics data with mass spectrometry method.

Figure 2. UALCAN input format. Source: http://ualcan.path.uab.edu/analysis.html

After you click the database format, you can select cancer type that you want to target (Figure 2). You can visualize the result with heatmap as you can see in side page (Figure 2). The gene target can be typed in the white box.

Figure 3. Gene class variation can be selected. Source: http://ualcan.path.uab.edu/analysis.html

The gene contribution can be specified as well like in the Figure 3. It has several classes such as clock gene class, metastasis class, pathway-associated class. The result from gene class selection can be seen in the Figure 4 that shows several genes and its expression can be checked in the second column result.

Figure 4. Gene class result interface. source: http://ualcan.path.uab.edu/cgi-bin/CPTAC-Result-Phos.pl?genenam=TK1&ctype=Breast

When you enter which cancer you want to analyze in the second column, it will show boxplot that shows gene expression between normal and cancer patients (Figure 5). The expression is calculated in transcript per million (TPM) which produced more stable calculation than FPKM.

Figure 5. Gene expression based on TCGA samples. Source: http://ualcan.path.uab.edu/cgi-bin/CPTAC-Result-Phos.pl?genenam=TK1&ctype=Breast.

In figure 5, you can see the statistical significance as well and you can check other features such as pan-cancer review, methylation, survival, protein expression, CHIP-seq data, correlated genes, DepMap, and external links.

Figure 6. Survival analysis result. Source: http://ualcan.path.uab.edu/cgi-bin/TCGA-survival1.pl?genenam=ACTN1&ctype=BRCA

One of the most popular analysis in cancer research is survival analysis and UALCAN also provides the survival analysis in the Figure 5. The result will be like Figure 6 that shows significance score (p = 0.3) and comparison graphic between normal and cancer patient group. There are page 1 until 5 which shows survival analysis based on clinical data such as age, menopause condition, race, and others.

Overall, the web application can analyze multi-omics data but it seems they analyze the -omics data separately. When you select another analysis like methylation and protein, they will show each analysis result in different pages. However, this application is suitable for introduction research level when the researcher is searching candidate genes for wet lab experiment.

Reference

1. Chandrashekar, D. S., Karthikeyan, S. K., Korla, P. K., Patel, H., Shovon, A. R., Athar, M., Netto, G. J., Qin, Z. S., Kumar, S., Manne, U., Creighton, C. J., & Varambally, S. (2022). UALCAN: An update to the integrated cancer data analysis platform. Neoplasia (New York, N.Y.), 25, 18–27. https://doi.org/10.1016/j.neo.2022.01.001