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pyScaf

pyScaf orders contigs from genome assemblies utilising several types of information:

  • paired-end (PE) and/or mate-pair libraries ([NGS-based mode](#ngs-based-scaffolding))
  • long reads ([NGS-based mode](#scaffolding-based-on-long-reads))
  • synteny to the genome of some related species ([reference-based mode](#reference-based-scaffolding))

Scaffolding modes

NGS-based scaffolding

This is under development… Stay tuned.

Scaffolding based on long reads

Experimental version available.

Reference-based scaffolding

In reference-based mode, pyScaf uses synteny to the genome of closely related species in order to order contigs and estimate distances between adjacent contigs.

Contigs are aligned globally (end-to-end) onto reference chromosomes, ignoring:

  • matches not satisfying cut-offs (–identity and –overlap)
  • suboptimal matches (only best match of each query to reference is kept)
  • and removing overlapping matches on reference.

In preliminary tests, pyScaf performed superbly on simulated heterozygous genomes based on C. parapsilosis (13 Mb; CANPA) and A. thaliana (119 Mb; ARATH) chromosomes, reconstructing correctly all chromosomes always for CANPA and nearly always for ARATH (Figures in dropbox, CANPA table, ARATH table). Runs took ~0.5 min for CANPA on 4 CPUs and ~2 min for ARATH on 16 CPUs.

Important remarks:

  • Reduce your assembly before (fasta2homozygous.py) as any redundancy will likely break the synteny.
  • pyScaf works better with contigs than scaffolds, as scaffolds are often affected by mis-assemblies (no de novo assembler / scaffolder is perfect…), which breaks synteny.
  • pyScaf works very well if divergence between reference genome and assembled contigs is below 20% at nucleotide level.
  • pyScaf deals with large rearrangements ie. deletions, insertion, inversions, translocations. Note however, this is experimental implementation!
  • Consider closing gaps after scaffolding.

Usage

Parameters

Given reference genome, the program generates pairwise genome alignment (dotplots) by default.

  • Genral options:

    -h, --help

    show this help message and exit

    -f FASTA, --fasta FASTA
     

    assembly FASTA file

    -o OUTPUT, --output OUTPUT
     

    output stream [scaffolds.fa]

    -t THREADS, --threads THREADS
     

    max no. of threads to run [4]

    --log LOG

    output log to [stderr]

    --dotplot

    generate dotplot as [png]

    --version

    show program’s version number and exit

  • Reference-based scaffolding options:

    -r REF, --ref REF, --reference REF
     

    reference FastA file

    --identity IDENTITY
     

    min. identity [0.33]

    --overlap OVERLAP
     

    min. overlap [0.66]

    -g MAXGAP, --maxgap MAXGAP
     

    max. distance between adjacent contigs [0.01 * assembly_size]

    --norearrangements
     

    high identity mode (rearrangements not allowed)

  • Long read-based scaffolding options (EXPERIMENTAL!):

    -n LONGREADS, --longreads LONGREADS
     

    FastQ/FastA file(s) with PacBio/ONT reads

  • NGS-based scaffolding options (!NOT IMPLEMENTED!):

    -i FASTQ, --fastq FASTQ
     

    FASTQ PE/MP files

    -j JOINS, --joins JOINS
     

    min pairs to join contigs [5]

    -a LINKRATIO, --linkratio LINKRATIO
     

    max link ratio between two best contig pairs [0.7]

    -l LOAD, --load LOAD
     

    align subset of reads [0.2]

    -q MAPQ, --mapq MAPQ
     

    min mapping quality [10]

Test run

To perform reference-based assembly, provide assembled contigs and reference genome in FastA format. Dotplots of below runs can be found in [docs](/docs). If you wish to skip dotplot generation (ie. no X11 on your system), provide –dotplot ‘’ parameter.

# scaffold homogenised assembly (reduced contigs)
./pyScaf.py -f test/contigs.reduced.fa -r test/ref.fa -o test/contigs.reduced.ref.fa

# scaffold reduced contigs using global mode (no norearrangements allowed)
./pyScaf.py -f test/contigs.reduced.fa -r test/ref.fa -o test/contigs.reduced.ref.global.fa --norearrangements

# scaffold heterozygous assembly (de novo assembled contigs)
./pyScaf.py -f test/contigs.fa -r test/ref.fa -o test/contigs.ref.fa

# scaffold reduced contigs using long reads
## pacbio
./pyScaf.py -f test/contigs.reduced.fa -n test/pacbio.fq.gz -o test/contigs.reduced.pacbio.fa
## nanopore
./pyScaf.py -f test/contigs.reduced.fa -n test/nanopore.fa.gz -o test/contigs.reduced.nanopore.fa

# generate dotplot
lastdb test/ref.fa
lastal -f TAB test/ref.fa test/contigs.reduced.pacbio.fa | last-dotplot - test/contigs.reduced.pacbio.fa.ref.png
lastal -f TAB test/ref.fa test/contigs.reduced.nanopore.fa | last-dotplot - test/contigs.reduced.nanopore.fa.ref.png

# clean-up
#rm test/contigs.{,reduced.}fa.* test/ref.fa.* test/*.{nanopore,pacbio,ref}* test/*.log

Proof of concept

pyScaf is under heavy development right now. Nevertheless, the reference-based mode is functional and produces meaningful assemblies. Moverover, it has been implemented in Redundans.

For more info, have a look in workbook.

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