Thank you for the suggestions. The Pacbio coverage is approximately 6X, so I presume PBJelly might be a good option for me.
Hi,
I am trying a donovo assembly of a reptilian genome (size comparable to humans) with ALLPATHS-LG. I have two illumina libraries paired-end and mate-pairs. In addition to it, I have a pacbio library.
I used LoRDEC to correct the errors in the pacbio data. For this I utilized the short reads from illumina (to get the deBruijn graph). I also carried out the trim-split step given in LoRDEC. My question is do I use the corrected pacbio reads (as is) or do I use the corrected-trimmed-split pacbio reads as long reads in ALLPATHS-LG deno assembly. pipeline
I am asking this because according to the LoRDEC manual "The output is the set of corrected reads also in FASTA format. In these corrected sequences: uppercase symbol denote correct nucleotides, while lowercase denote nucleotides left un-corrected."
Also, I plan to improve upon the correction process by using the corrected pacbio reads (either as corrected or as corrected-trim-split fasta files) as the input for the succeeding step of error correction with an increment in k-mer value and repeat the same. Could anyone tell me if the above steps are meaningful or if they are wrong, suggest an alternative iterated correction protocol.
Thanks
1 answer
The untrimmed un-split reads, contains uncorrected regions either because of lack of coverage or this regions of high errors and it could not be corrected. so using it could lead to miss-assemble.
regarding correction with different k-mer I think there is a suggested value by LoRDEC depends on the genome, as you mentioned it is a big genome, as I remember you should use 21.
Also I a recommend using HALC, based on this Efficiency of PacBio long read correction by 2nd generation Illumina sequencing
Regarding assembly: If you have high PacBio coverage (>20X) you can use canu for assembly without short reads.
also there is other ways to use PacBio
- filling gaps (case of low coverage)
- or hybrid assembly using tools like dbg2olc (Just an example, follow this link for more)
follow this post
C: Why we need 100X coverage to get a high-quality assembly?
With this coverage it is a good option. Good luck
Did you try to use FMLRC (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5807796)?
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I have the same question as you. What did you end up doing? Trim, split, both or nothing?