Hi everyone: this is the graph I get when doing quality control using fastqc. Does anyone know what this means? why are there no yellow boxes? This figure doesn't show me the IQ ranges. Why is this so? Can I proceed with this? I believe not, but can someone confirm this for me? Do I maybe need to trim the basepairs to 40 bp? And how do you do that?
Thanks in advance,
a confused beginner!
1 answer
There are no yellow boxes because the data at the beginning of the read is all > Q36. There is no need to trim anything at the beginning of reads.
From link below:
The elements of the plot are as follows:
The central red line is the median value
The yellow box represents the inter-quartile range (25-75%)
The upper and lower whiskers represent the 10% and 90% points
The blue line represents the mean quality
See this for more: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/2%20Per%20Base%20Sequence%20Quality.html
FastQC reports need to be taken in context of the experiment you are doing. "Fails" on FastQC categories do not automatically mean your data is bad. These QC intervals are meant for normal genomic DNA sequencing and thus "fail" on other types of experiments.
There are multiple blog posts by authors of FastQC that address some of these: https://sequencing.qcfail.com/software/fastqc/
Thanks, I'll read it here.
with experiment do you mean the way of sequencing or do you mean the exact experiment of like the paper where I got this data from?
Type of experiment. e.g. with RNAseq, ChIPseq etc you will have multiple copies of fragments so "sequence duplication" level may show a fail. But that result is expected for this kind of experiment.
We'll I'm working with next generation sequencing (Illumina). So sequence duplication may show a fail? I didn't read it in the link you sent here.
One or more tests may show a fail with any kind of sequencing. FastQC is a QC program and there is no rule that says one needs to have all "pass" before you move on to actual analysis. Keep the context of experiment in mind as you look at FastQC results.
Thanks a lot, GenoMax for the explanation!
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