Quality Control of Illumina Data
Mick Watson
Director of ARK-Genomics
The Roslin Institute
QUALITY SCORES
Quality scores
• The sequencer outputs base calls at each position of a read
• It also outputs a quality value at each position
– This relates to the probability that that base call is incorrect
• The most common Quality value is the Sanger Q score, or Phred score
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Qsanger -10 * log10(p)
Where p is the probability that the call is incorrect
If p = 0.05, there is a 5% chance, or 1 in 20 chance, it is incorrect
If p = 0.01, there is a 1% chance, or 1 in 100 chance, it is incorrect
If p = 0.001, there is a 0.1% chance, or 1 in 1000 chance, it is incorrect
• Using the equation:
– p=0.05, Qsanger = 13
– p=0.01, Qsanger = 20
– p=0.001, Qsanger = 30
For the geeks….
• In R, you can investigate this:
sangerq <- function(x) {return(-10 * log10(x))}
sangerq(0.05)
sangerq(0.01)
sangerq(0.001)
plot(seq(0,1,by=0.00001),sangerq(seq(0,1,by=0.00001)),
type="l")
The plot
For the geeks….
• And the other way round….
qtop <- function(x) {return(10^(x/-10))}
qtop(30)
qtop(20)
qtop(13)
plot(seq(40,1,by=-1), qtop(seq(40,1,by=-1)), type="l")
The important stuff
• Q30 – 1 in 1000 chance base is incorrect
• Q20 – 1 in 100 chance base is incorrect
QUALITY ENCODING
Quality Encoding
• Bioinformaticians do not like to make your life easy!
• Q scores of 20, 30 etc take two digits
• Bioinformaticians would prefer they only took 1
• In computers, letters have a corresponding ASCII code:
• Therefore, to save space, we convert the Q score (two digits)
to a single letter using this scheme
The process in full
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p (probability base is wrong) : 0.01
Q (-10 * log10(p))
: 30
Add 33
: 63
Encode as character
:?
P
Q
Code
0.05
13
.
0.01
20
5
0.001
30
?
For the geeks….
code2Q <- function(x) { return(utf8ToInt(x)-33) }
code2Q(".")
code2Q("5")
code2Q("?")
code2P <- function(x) { return(10^((utf8ToInt(x)-33)/-10)) }
code2P(".")
code2P("5")
code2P("?")
QC OF ILLUMINA DATA
FastQC
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FastQC is a free piece of software
Written by Babraham Bioinformatics group
http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
Available on Linux, Windows etc
Command-line or GUI
Read the documentation
Follow the course notes
Per sequence quality
• One of the most important plots from FastQC
• Plots a box at each position
• The box shows the distribution of quality values at that position across all
reads
Obvious problems
Less obvious problems
Really bad problems
Other useful plots
• Per sequence N content
– May identify cycles that are unreliable
• Over-represented sequences
– May identify Illumina adapters and primers