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DATABASES.md

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Database formatting instructions

Some sections are not filled out yet. Contributions in the form of pull requests are welcome for instructions.

The easy button

If you don't really want to read any of this, then there is a script for you. This script downloads and formats for Kraken1 and Kraken2.

bash bin/downloadTaxonomy.sh
bash bin/filterTaxonomy.sh # optional, reduces footprint
bash bin/downloadKalamari.sh

If you want to know more details, move onto the next section.

Init

Start off with a few environmental variables, regardless of your target database.

# assuming source folder is "Kalamari", where you downloaded all fasta files
VERSION=$(downloadKalamari.pl --version)
CPUS=4       # Define how many threads to use
# The folder where fasta files were downloaded
sharedir=Kalamari/share/kalamari-$VERSION
SRC="$sharedir/kalamari"
TAXDIR="$sharedir/taxonomy/filtered"

# Find a test fasta file for querying if you don't have one already
FASTA=$(find $SRC -name '*.fasta' | head -n 1) 
# Make a fake fastq file if you don't already have a test fastq file
FASTQ="$FASTA.fastq.gz"
head -n 2 $FASTA | perl -e '$id=<>; $seq=<>; chomp($id, $seq); $qual="I" x length($seq); $id=~s/^>/@/; print "$id\n$seq\n+\n$qual\n";' | gzip -c > $FASTQ

Different databases

Please follow the Init section before continuing. These instructions assume that you have already downloaded the Kalamari fasta files.

Kraken with Kalamari (Steamed Kalamari)

Build

bash bin/buildKraken1.sh

Query

DB="$sharedir/kalamari-kraken1"
# fasta input
kraken --db kraken -output kraken.raw --fasta-input $FASTA
# fastq input
kraken --db kraken -output kraken.raw --fastq-input $FASTQ --gzip-compressed

Kraken2 with Kalamari (Fried Kalamari)

Build

bash bin/buildKraken2.sh

Query

DB="$sharedir/kalamari-kraken2"
# Same command for either fasta or fastq
kraken2 --db $DB --report kraken2.report --use-mpa-style --output kraken2.raw $FASTA
kraken2 --db $DB --report kraken2.report --use-mpa-style --output kraken2.raw $FASTQ

Sepia Kalamari

Build

DB=$sharedir/kalamari-sepia
# Create the Sepia references file with two columns: path, taxonomy
python3 bin/generate_sepia_reference.py --taxonomy src/taxonomy -o sepia.ref.tsv --fastadir ./Kalamari src/chromosomes.tsv src/plasmids.tsv
sepia build --index $DB --refs sepia.ref.tsv --kmer 41 --minimizer 31 --batch 300 --gamma 5.0 --threads $CPUS 
ls -lhS $DB # view a directory representing the database

Query

sepia classify --index $DB --prefix test_kalamari --query $FASTQ
# View the summary:
# First column is the classification, second read count and third average kmer similarity
sort -k2,2nr test_kalamari_summary.txt | head -n 20 | column -t

# View taxonomic classification results per read
zcat test_kalamari_classification.gz | head

ColorID with Kalamari

Mashed Kalamari

Using Mash version 2

DB=$sharedir/kalamari.msh

find $SRC -name '*.fasta' -exec mash sketch {} \;
find $SRC -name '*.msh' > $DB.fofn
mash paste $DB -l $DB.fofn

BLASTed Kalamari

Build

DB=$sharedir/Kalamari-blast
mkdir $DB

find $SRC -name '*.fasta' -exec cat {} \; > $DB/kalamari.fasta
makeblastdb -dbtype nucl -in $DB

Query

blastn -query $FASTA -db Kalamari.blast/kalamari.fasta

ANI Kalamari

Build

# Can use the same folder; just add file of filename
DB=$sharedir/reference.fofn
find $SRC -name '*.fasta' > $DB

Query

fastANI --rl $DB -q $FASTA /dev/stdout

mm Kalamari (mmSeqs2)

Build

DB=$sharedir/kalamari-mmseqs2
Kalamari]$ find $SRC -name '*.fasta' | xargs -n 100 gzip -c > $SRC.cat.gz
mmseqs createdb Kalamari.cat.gz $DB

Query

# need to create database out of your query fasta file
mmseqs createdb $FASTA $FASTA.mmseqs2
# The actual query:
mmseqs search --threads 4 $FASTA.mmseqs2 $DB mmseqs2.out mmseqs2.tmp

MIDAS

See this ongoing issue for more information. #12