Errors about misencoded quality scores

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created by Geraldine_VdAuwera

on 2015-11-20

The problem

You get an error like this:

SAM/BAM/CRAM file <filename> appears to be using the wrong encoding for quality scores

Why this happens

The standard format for quality score encodings is that Q0 == ASCII 33 according to the SAM specification. However, in some datasets (including older Illumina data), encoding starts at ASCII 64. This is a problem because the GATK assumes that it can use the quality scores as they are. If they are in fact encoded using a different scale, our tools will make an incorrect estimation of the quality of your data, and your analysis results will be off.

To prevent this from happening, the GATK engine performs a sanity check of the quality score encodings that will abort the program run if they are not standard (since version 2.3), and output the error message shown above.

Solution

If this happens to you, you'll need to run again with the flag --fix_misencoded_quality_scores / -fixMisencodedQuals. What will happen is that the engine will simply subtract 31 from every quality score as it is read in, and proceed with the corrected values. Output files will include the correct scores where applicable.

Related problems

In some cases the data contains a mix of encodings (which is likely to arise if you're passing in a lot of different files from different sources together), and the GATK can't automatically compensate for that. There is an argument you can use to override this check: -allowPotentiallyMisencodedQuals / --allow_potentially_misencoded_quality_scores; but you use it at your own risk. We strongly encourage you to check the encodings of your files rather than use this option.

Updated on 2015-11-20

From jlrflores on 2016-01-25

I am using FastQC to evaluate the results of -fixMisencodedQuals on my data. I have a dataset that, according to FastQC, has Illumina 1.5 encoding. After applying -fixMisencodedQuals, GATK proceeds normally, however the FastQC results look strange. The quality score distribution appears to be totally squashed, and it does not appear that a simple “subtract 31” was applied. Before/after pictures attached.

The sample was sequenced on multiple technologies, and this dataset has a very high error rate after processing. I also have results for the same sequence data on an earlier version of GATK and the results look better, the error rate is lower.

Is there an alternative tit “-fixMisencodedQuals”? Am I the only one observing this strange behavior?

Thanks,

Juan

after.png

before.png

From Sheila on 2016-01-25

@jlrflores

Hi,

I am getting Geraldine’s opinion before I post a final response here. We will get back to you soon.

-Sheila

From Geraldine_VdAuwera on 2016-01-26

How did you apply the encoding fix? As part of a separate command? Can you list any and all commands that were applied to this dataset?

What kind of data is this?