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Need help regarding assembler

Hi all,

I am very new to genome assembly. I have got 4 data for a genome of size 50M. Data what i have are, illumina short insert lib (200-500), long insert lib (300-600), mate pair (3-5kb) and nanopore (yet to receive). Kindly suggest which assemblers to use?? which data to use what stage (assembly, scaffolding or gapclosure)?? how do i get best kmer apart from kmergenie? Any other kmer identifier?

Detailed input is much appreciated.

Right now i am thinking of spades and idba_ud for assembly using both short and long insert together. Further need some assistance.

Thank you

genome next-gen

Please elaborate on the species, or at least kingdom of life to which your species belongs. Also, does a reference genome already exist for this species?

There are many options for assembly, including:

  • ABySS
  • Velvet, which allows you to have analyse multiple read-lengths together, and VelvetOptimiser, which assists you in identifying the ideal K-mer size

Data what I have is 150 x 2. Data is for green algae. I thought velvet is for max read length of 100 x 2. I have already started with abyss .. K from kmergenie.. Also trying idba-ud as it is a multi k mer assembler. What other options ??

No reference available..

Velvet can tolerate any read lengths. It was designed to cater for short-read assembly, but it accepts a mixture or either of both. To be honest, I don't believe that any genome can be faithfully assembled from short reads and I think that using short reads is sacrificing precision of the assembly a bit too much - a personal opinion based on my knowledge of the assembly algorithms.

Thank you. I will try with velvet. Any luck on scaffolding and gapcloser .

I'd suggest unicycler, heard lots of good things about it.

Unicycler is a exclusive bacterial assembler. Mine is algal sample. I could try this for a bacterial sample. Thank you for suggestion. Are there any specific for algal

I have already used spades, abyss and idba_ud

If you already have a bunch of assemblies then you should think about consolidating them using GARM or equivalent.

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