Step3_FromContigToChromosomeAssembly

# Step3
# As the output is gfa format which is not supported by RagTag(a sofeware maps contigs to reference genome to get right path) 
# for get the fasta output
awk '/^S/{print ">"$2; printf "%s", $3 | "fold -w 80"; close("fold -w 80"); print ""}' in.gfa > out.fa
# If you want to include GFA tags in fasta header line
awk '/^S/{header=">"$2; for(i=4; i<=NF; i++) {header=header" "$i}; print header; printf "%s", $3 | "fold -w 80"; close("fold -w 80"); print ""}' in.gfa > out.fa
#close() is required to prevent the headers and sequences from getting out of sync or being skipped 
#when sequences are very long.

# Sometimes, one may need join contigs/segments together before exporting to fasta you should use a scaffolding tool such as:
# # #GraphUnzip (Detangles graph, can be used before scaffolding)
# # #DENTIST
# # #SAMBA
# # #ntLINK
# # #SLR
# # #SGTK
#However these is not necessary when you already have a reference genome of the same speices.

# A very good choice is too amplify a crossing population, especially in plants, construction of linkage maps will help you know the relative position of each contig
#If karyotype is known, better using FISH-or GISH to verify it by karyotype. Then the Unknow chromosome will be assign into right chromosome.

# some time the hifi read is not enough to generated high quality whole genome sequences that we can only get long contigs
# The RagTag could help, if the some other reference genomes are avaliable within the same species.
# RagTag is a conda package, make sure you have following depencies: 
# Minimap2, Unimap or Nucmer and Python 3

#Installation
conda install -c bioconda ragtag

# correct a query assembly
ragtag.py correct ref.fasta query.fasta
# scaffold a query assembly
ragtag.py scaffold ref.fasta query.fasta
# scaffold with multiple references/maps
ragtag.py scaffold -o out_1 ref1.fasta query.fasta
ragtag.py scaffold -o out_2 ref2.fasta query.fasta
ragtag.py merge query.fasta out_*/*.agp other.map.agp
# use Hi-C to resolve conflicts
ragtag.py merge -b hic.bam query.fasta out_*/*.agp other.map.agp
# make joins and fill gaps in target.fa using sequences from query.fa
ragtag.py patch target.fa query.fa