Chapter 7 Nanopore Read QC

Quality Control

  1. What do we need in order to run a Quality Control Check?
  • Sequencing Summary File
    • Automatically produced by the MinIon basecaller.
  • PycoQC package + dependencies
    • Already downloaded for you in Ghostwheel.
  • Line of code to produce .html file.
  • Line of code to secure copy file to your computer.

7.1 Sequencing Summary File

Where is it?

/home/data/metagenomics/red-alder-reads/sequencing_summary_FAS21661_9ac87089.txt

7.2 PycoQC package & code

  1. Where is it? How to activate it?
  • Log in to Ghostwheel
  • Stay in your home directory (check with pwd)
  • Type the following:
source activate pycoQC
pycoQC
pycoQC –f inputfilename.txt –o outputfilename.html

7.3 Secure Copy

  1. What terminal to copy from? What is the code?
  • Open new Terminal window but don’t connect to the linux server
  • Type:
scp -P 2310 <username>@inbre.ncgr.org:/home/<username>/outputfile.html ~/Desktop/

7.4 Open your URL

Find your file on your desktop.

Double-click to open, or right-click to select browser

https://a-slide.github.io/pycoQC/
https://a-slide.github.io/pycoQC/

7.4.1 Normalization

With normalization we are trying to get the correct relative gene expression abundances between cells.

Gene expression between cells is based on count data.

What does a count in a count matrix represent?

  • mRNA Capture
  • Reverse transcription of mRNA
  • sequencing of a molecule of mRNA

The most common normalization protocol is:

  • count depth scaling
  • aka CPM or counts per million
  • it assumes that all cells in the dataset initially contain an equal number of mRNA molecules
  • it assumes that count depth differences arise from sampling

Normalize complete

  • But wait!
  • We still have unwanted variability in the data.
  • What kind of unwanted variability?
  • What is the solution? Data Correction.

7.4.2 Data correction and integration

Biological Covariates

  • Cell-Cycle effects
  • Batch
  • Dropout

Which Covariates to Consider?

  • Depends on downstream analysis
  • Correct for biological and technical to be considered separately
  • Corrections are used for different purposes
  • Each approach to correction presents unique challenges

What are the Correction methods?

  • Regressing out biological effects
  • Regressing out technical effects
  • Batch effects and data integration
  • Expression recovery