Systems Biology

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RNA-seq data analysis

Advanced I

(supplementary)

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Heatmap visualization

May 24, 2022

Bioinformatics & Genomics Lab

Department of Life Science

Hanyang University

Sang-Ho Yoon

Bioinformatics & Genomics, the BIG lab.

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MA plot highlights statistically significant DEGs

1. Normalize read count to TPM values using following python script

2. cp pheatmap R script to draw heatmap of top 10 DEG

3. Extracting gene clusters visualized in your heatmap is often your first objective

Bioinformatics & Genomics, the BIG lab.

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Connect VPN and open your Shell

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Visualization of gene expression using heatmap

Bioinformatics & Genomics, the BIG lab.

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Visualization of gene expression using heatmap

$ ssh biglab1

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$ cd systems_biology_2022/YOUR_DIRECTORY

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$ mkdir session_12

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$ cd session_12

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Navigate into your directory and link DESeq2 result file

Bioinformatics & Genomics, the BIG lab.

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Visualization of gene expression using heatmap

$ ln –s <path_to_your_session_7>/immune_cells.symbols.txt

$ ln –s <path_to_your_session_7>/immune_cells_deseq2.txt

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Or

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$ cp ~/systems_biology_2022/TA/session_12/immune_cells.symbols.txt .

$ cp ~/systems_biology_2022/TA/session_12/immune_cells_deseq2.txt .

Navigate into your directory and link DESeq2 result file or copy templates (if you don’t have yours)

Bioinformatics & Genomics, the BIG lab.

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1. Normalize read count to TPM values using following python script

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Visualization of gene expression using heatmap

$ cp /home/biguser/systems_biology_2022/TA/src/count_to_tpm.py .

$ ./count_to_tpm.py --help

*Usage

because we need gene length to calculate TPM

Bioinformatics & Genomics, the BIG lab.

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Run count_to_tpm python script

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Visualization of gene expression using heatmap

$ ./count_to_tpm.py \

-c immune_cells.symbols.txt

-f <path_to_your>/7_featureCounts/Naive_CD8_T_cells_rep1.txt

-o immune_cells.symbols.tpm.txt

Bioinformatics & Genomics, the BIG lab.

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2. cp pheatmap R script to draw heatmap of top 10 DEG

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Visualization of gene expression using heatmap

$ cp /home/biguser/systems_biology_2022/TA/src/pheatmap.R .

Input files

B cell gene

T cell gene

Bioinformatics & Genomics, the BIG lab.

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3. Extracting gene clusters visualized in your heatmap is often your first objective

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Visualization of gene expression using heatmap

You can access each dendrogram in your pheatmap using

Bioinformatics & Genomics, the BIG lab.

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Visualization of gene expression using heatmap

These commands will draw the dendrogram of gene clustering

(*my_hm is your pheatmap object name)

Use “height” to divide clusters

Bioinformatics & Genomics, the BIG lab.

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Visualization of gene expression using heatmap