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This article will explain in detail how to use EPIC to predict the composition of immune cells in tumor microenvironment. The content of the article is of high quality, so the editor shares it for you as a reference. I hope you will have some understanding of the relevant knowledge after reading this article.

In traditional RNA_seq sequencing, each sample actually contains thousands of cells after sampling. Compared with single-cell sequencing single cell, such samples are called bulk samples. Among so many cells in bulk samples, there may be multiple cell subsets.

In tumor tissues, due to the infiltration of various cells in tumor microenvironment, there must be many kinds of cell subsets in RNA_seq samples, such as tumor cells, infiltrating immune cells and so on. In order to accurately evaluate the composition of immune cells in tumor microenvironment, scientists have made a lot of efforts. EPIC is a software that uses RNA_seq expression profile data of tumor samples to evaluate the composition of immune cells in tumor samples.

Https://elifesciences.org/articles/26476

The software is packaged into an R package, and the URL is as follows

Https://github.com/GfellerLab/EPIC

Online services are also provided at the following URL

Https://gfellerlab.shinyapps.io/EPIC_1-1/

You only need to upload the expression profile data of the tumor sample, as shown below

The contents of the uploaded file are as follows

Each row represents a gene, each column represents a sample, and the result is divided into two parts

1. Tabular data

The proportion of each cell subgroup in each sample is given as follows

two。 Visualization result

The cell components of each sample are shown in the form of a bar chart, and the results are as follows

The cell components of each sample are shown in the form of a heat map, and the results are as follows

The distribution of each cell subgroup is shown in the form of a box diagram, and the results are as follows

The immune cell infiltration of tumor samples can be predicted and compared by EPIC, and the operation is simple.

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