LoFreq-Star-FAQ
FAQ for LoFreq-Star
How to Cite
Where to get Help:
- See the mailing list
- See the LoFreq blog for news and updates
Do I need to filter LoFreq Predictions?
You usually don't. Predicted variants are already filtered using default parameters (which include coverage, strand-bias, snv-quality etc). If you however, need extra conservative settings you can use lofreq filter to add some more filter criteria.
What Happens if I didn't recalibrate Base-Qualities?
We usually recommend to follow GATK's best practices on post-processing of you BAM file which include base quality recalibration. You can run LoFreq on non-recalibrated data, which might however results in a higher rate of false positive calls. We would recommend GATK base-recalibration even for non-human data or targeted sequencing. GATK usually requires the input of known variant sites (which is a circular problem) which are however not known for most organisms non-human data (use dbsnp for human data). One option is to use initial LoFreq predictions as vcf input to GATK and then run LoFreq again.
Regions for Targeted Sequencing
If you want to run LoFreq only on certain regions use the appropriate bed-file as input with -l regions.bed. Not doing so will negatively affect LoFreq sensitivity and it might calls variants
outside of the desired regions.
PCR Amplified Data
If your data was heavily PCR-amplified LoFreq will likely call SNVs in primer regions, due
to ambiguous primer positions, primer impurities etc. You should ignore primer positions after SNV
calling. The best way to achieve this is to create a bed-file that only lists non-primer regions and use that as input to Lofreq with -l regions.bed.
Another problem with heavily PCRed input is that PCR artifacts will show up as low-frequency SNVs. Their allele frequency will usually be low, unless a mis-amplification happened in early cycles. Computational tools will be unable to distinguish these from true low-frequency variants, since the mis-incorporated bases look real to the sequencing machine. To get rid of these you will either have to run your samples in duplicates (before amplification) or remove SNVs below the expected PCR error frequency.
I get fewer SNVs than Expected When Running LoFreq on a BAM file with Bowtie/BWA-SW
BWA-SW assigns very low mapping qualities to mapped reads. Consider disabling the use of mapping quality on lofreq call with -J. The same is true for Bowtie, depending on the parameters you used. Bowtie it will sometimes produce alignments with reads that have either only mapping quality 0 (non unique) or 255 (not available). It is unclear to us why that happens, or what exactly that means (see also this thread). LoFreq uses mapping quality by default for the prediction of SNVs, which doesn't help in this scenario. We would suggest to switch off the use of mapping quality (see above) in such cases.
Call-Parallel Fails with an Error Message Which is Hard to Interpret
This is easiest to debug by running the single-threaded version call first with the same parameters, check the error message and fix the command accordingly. Then execute call-parallel again with fixed parameters.