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Colorectal cancer Colorectal cancerColorectal cancer starts in the colon or the rectum and most cases are adenocarcinoma tumors. Colorectal cancer commonly starts as a growth, or polyp, on the inner lining of the colon and can spread to other parts of the body. Most colorectal cancers are related to age and lifestyle factors, while a small number of cases are due to underlying genetic disorders. Some common symptoms include blood in the stool, weight loss, and a change in bowel movements. Colorectal cancer is the third most common cancer and the second most common cause of cancer deaths worldwide (World Health Organization, 2024-10-01). Differential Abundance Analysis ResultsThis section presents the results of the differential protein abundance analysis, visualized through a volcano plot and summarized in the accompanying table for all three comparisons: 1) disease vs. healthy samples, 2) disease vs. diseases from the same class, and 3) disease vs. all other diseases. Disease vs Healthy
Disease vs Class
Disease vs All other
Figure 1: In the volcano plot, proteins are plotted based on their fold change (logFC) on the x-axis and the statistical significance of the change (-log10 adjusted p-value) on the y-axis. Proteins considered differentially abundant are highlighted, defined by an adjusted p-value < 0.05 and an absolute logFC > 0.5.
Table 1: The summary table lists the results for all comparisons, sorted by p-value by default. It includes key metrics such as fold change and adjusted p-value, to allow exploration of the most significant proteins for each comparison.
Figure 1: In the volcano plot, proteins are plotted based on their fold change (logFC) on the x-axis and the statistical significance of the change (-log10 adjusted p-value) on the y-axis. Proteins considered differentially abundant are highlighted, defined by an adjusted p-value < 0.05 and an absolute logFC > 0.5.
Table 1: The summary table lists the results for all comparisons, sorted by p-value by default. It includes key metrics such as fold change and adjusted p-value, to allow exploration of the most significant proteins for each comparison.
Figure 1: In the volcano plot, proteins are plotted based on their fold change (logFC) on the x-axis and the statistical significance of the change (-log10 adjusted p-value) on the y-axis. Proteins considered differentially abundant are highlighted, defined by an adjusted p-value < 0.05 and an absolute logFC > 0.5.
Table 1: The summary table lists the results for all comparisons, sorted by p-value by default. It includes key metrics such as fold change and adjusted p-value, to allow exploration of the most significant proteins for each comparison.
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Contact
The Project
The Human Protein Atlas
The Human Protein Atlas project is funded
