DNA Ghost:

This note based blog covers bioinformatics and cancer genomics 

May 25, 2020


  In previous POST, we discussed some basics of probability distribution and corresponding hypothesis testing. Here let's continue this topic and talk about the usage of probability distribution in NGS data analysis. More specifically, why do we choose what we choose...

November 30, 2018

Ghost encountered dimension reduction problem while designing a model aiming to describe patient's immuno-oncology (IO) status. The model is supposed to incorporate well-known immune related factors listed in the figure below (for factor selection details, please read...

February 12, 2018

For RNA-Seq, it has been challenging to distinguish PCR duplicates from biological duplicates. Ghost found a tool that tackles this and answer question:

  • In your RNA-Seq library, whether the duplicates primarily come from PCR duplicates or biological duplicates?

  • ...

October 24, 2017

In previous POST, we discussed several possible bias sources and how to correct them. Here Ghost wanna talk about two other bias that must be normalized in every RNA-Seq analysis.

Heteroscedasticity issue 

For genes that are highly expressed, their high expression c...

August 25, 2017

Roughly, RNA-Seq may have the following bias sources:

  • Random priming

  • PolyA selection (3’ bias) and ribosomal depletion

  • PCR duplicates

  • Normal cell contamination (when evaluating tumor)

  • Tumor purity

  • Batch effect

Random priming

Appears at firs...

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