Pancreatic Adenocarcinoma (PAAD) is the third most common cause of death from cancer, with an overall 5-year survival rate of less than 5%, and is predicted to become the second leading cause of cancer mortality in the United States by 2030.

Here we had a dataset of normalized RNA Sequencing reads for pancreatic cancer tumors. The measurement consists of ~20,000 genes for 185 pancreatic cancer tumors.

• Read data from GCT file, a tab-delimited file used for sharing gene expression data and metadata (details for each sample) for samples.
• Remove genes with NaNs
• Generate gene expression distribution for all samples.

• Visualize the data whole data using PCA and analyze the variance of PCA
• Analyse the general behavior of the different samples
• Remove the neuroendocrine tumors from the dataset so that it contains only the adenocarcinoma tumor samples

• Plot the gene expression values for these genes for pancreatic adenocarcinoma
• Unsupervised clustering on the gene expression data

EDA on Titanic dataset

Dimensionality Reduction

Unsupervised Clustering Algorithms

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