Report results RNAseq Basal vs Luminal PCa cells

Author

Francisco Porcel-Pastrana

1 Imput Data

1.1 DataSet

This DataSet comes from available data in GEO (Accession: GSE67070).

Zhang, D., Park, D., Zhong, Y., Lu, Y., Rycaj, K., Gong, S., Chen, X., Liu, X., Chao, H. P., Whitney, P., Calhoun-Davis, T., Takata, Y., Shen, J., Iyer, V. R., & Tang, D. G. (2016). Stem cell and neurogenic gene-expression profiles link prostate basal cells to aggressive prostate cancer. Nature communications, 7, 10798. https://doi.org/10.1038/ncomms10798

Here, you can take a brief view of upload dataset (and you also can download it):

1.2 Metadata

And here, you can take a brief view of upload dataset (and you also can download it):

2 Gene Expression Analisis

2.1 Normalized data

First we are going to normalize the counts of every samples and do a boxplot to check the normalization:

QC Analisis

Boxplot shows that all samples hava almost the same median and data dispersion so we can conclude that data is correct.

Here you are the normalized data (log10(counts)+1):

Warning
  • Gene_Symbol and Entrez_ID have been also included.
  • Original values have been rounded to 5 digits.

2.2 Expression profile disregulation of Lunimal cells relative to Basal cells: An Overview

For next aproach we will use the results of the DESeq2 differencial gene expression analisis which shricked results table (final table of results) is this one:

Warning
  • BaseMean, log2FoldChange, and lfcSE original values have been rounded to 5 digits.
  • pvalue and padj original values have been changed into scientific format.

Thresholds
  • Threshold for adjusted p-value: 0.05
  • Threshold for Fold change: <-2 and >2 (which means an log2foldchage of 0.58)

In addition we are going to perform some hyeralchical clustering analisys Like PCA and Heatmap to check that groups are well defined:

3 OVA and GSEA