pyScaf 0.12a4

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Table of Contents

• pyScaf

  • Scaffolding modes

    • NGS-based scaffolding

    • Scaffolding based on long reads

    • Reference-based scaffolding

  • Usage

    • Dependencies

    • Parameters

    • Test run

  • Proof of concept

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

Dependencies

• LAST v700+

• FastaIndex

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.