The quick start guide for analyzing Fiber-seq data
Fiber-seq starting with PacBio
HiFi kinetics are required for predicting m6A with fibertools. Check with your sequencing provider prior to sequencing to ensure that the output file will have kinetics. Additionally, many of fibertools commands are compatible with CpG methylation which can be completed on instrument (if requested) or later with Jasmine, e.g. jasmine --keep-kinetics input.ccs.bam output.ccs.bam. This command should be run prior to fibertools if CpG methylation information is desired as Jasmine will overwrite the m6A predictions in the MM and ML tags.
Predict m6A and infer nucleosomes
To create useable Fiber-seq data you must first call m6A base-mods on the PacBio CCS bam using fibertools. First install fibertools and then process your bam file using the prediction command.
ft predict-m6a -t 16 input.ccs.bam output.fiberseq.bam
This will both make m6A calls and identify nucleosomes on each fiber.
Note, the input CCS bam must have average kinetics to be able to call m6A.
Alignment and phasing
We recommend aligning with pbmm2 and phasing with HiPhase. Please see their respective documentation for more information.
Alternatively, we have written a snakemake pipeline to align and phase Fiber-seq data; however, this pipeline is not officially supported outside of our lab at this time.
After this point, you will have a Fiber-seq BAM file that is compatible with all the extraction commands in fibertools.
Fiber-seq peaks and UCSC browser tracks (FIRE)
Once you have a phased bam file, you can identify Fiber-seq inferred regulatory elements (FIREs) to call Fiber-seq peaks and make a UCSC trackHub. Please see the FIRE repository for more details.
Fiber-seq starting with Oxford Nanopore Technologies (ONT)
Predict m6A
ft predict-m6a does not include a model for ONT data; however, you can use software, such as Dorado, to add CpG and m6A to your ONT BAM file.
Alignment and phasing
You can either use Dorado to align your ONT data or use a tool like minimap2 to align your data. If you do use minimap2 be sure to include the flag -y to preserve the CpG and m6A information in the output BAM file.
If you do want to do phasing we recommend using WhatsHap for phasing ONT data. Please see their documentation for more information.
Filtering m6A calls
If you do use Dorado you must then filter the m6A calls with modkit using a tenth percentile cutoff for each flow-cell independently. This is the only way to get good m6A calls in our experience, and using any hard ML threshold will not hold between flow-cells. Here is an example command:
modkit call-mods -t 8 -p 0.1 input.dorado.bam filtered.dorado.bam
Infer nucleosomes and MSPs
Once you have CpG and m6A information in your filtered ONT BAM file, you can use ft add-nucleosomes to infer nucleosomes and MSPs.
ft add-nucleosomes filtered.dorado.bam output.bam
A full example for processing ONT data
Here is an example summary of the commands to process ONT data assuming you have already completed 6mA and CpG calling with dorado:
`#converts to fastq keeping all the BAM tags` \
samtools fastq -@ 8 -T "*" ONT.dorado.with.6mA.bam \
`#aligns the data inserting the tags back into the output BAM`
| minimap2 -t 32 --secondary=no -I 8G --eqx --MD -Y -y -ax map-ont reference.fasta - \
`#optionally add back in the read groups from the original bam using rustybam` \
| rb add-rg -u ONT.dorado.with.6mA.bam \
`#sort and index the BAM` \
| samtools sort -@ 32 --write-index -o tmp.ONT.fiberseq.bam
#filters the ONT data for the best 6mA calls and write to stdout
modkit call-mods -p 0.1 tmp.ONT.fiberseq.bam - \
`# adds nucleosome calls to the ONT Fiber-seq` \
| ft add-nucleosomes - ONT.fiberseq.bam
After this point, you will have a Fiber-seq BAM file that is compatible with all the extraction commands in fibertools.
Fiber-seq peaks and UCSC browser tracks (FIRE)
We have had good success in applying the FIRE pipeline to ONT data. However, this does require a heuristic in FIRE that must be enabled. To enable this add ont: true to your config.yaml file when setting up your FIRE run.
You can find more details in on installing and running FIRE here:
Running the FIRE pipeline.