VEME-metagenomics-2024

VEME 2024 NGS Taxonomic assignment Tutorial

Carla Mavian

https://github.com/cmavian/VEME-metagenomics-2024

Background

We collected Aedes aegypti mosquitoes from different locations across the state of Florida, in the United States, and we want to understand what is the composition of their microbiome. We extracted the RNA from the abdomen of the mosquitoes, and performed shotgun sequencing with Illumina. Our reads are 100bp single-read. You can read more about this study here: https://journals.asm.org/doi/10.1128/msphere.00316-20

Metagenomic Workflow:

In this tutorial we will learn how to taxonomically classify and visualize our metagenomic reads obtained with Illumina using the following programs:

1. Kraken2 Manual
2. Bracken (Bayesian Reestimation of Abundance with KrakEN)
3. Krona Wiki

1. Connecting to the server to run the analysis:

Using MobaXterm connect to Host:

ssh veme@bagre.minas.fiocruz.br

Password: J@k_bio24

Then we connect to the virtual machine:

user35

Password: J@k_bio24

Now let's activate the virtual machine:

conda activate veme

2. Setting up our folder for the analysis:

1. going into home directory

ls

2. let's make a working folder

mkdir metagenomics

3. go in the folder and copy the files

cd metagenomics

3. Kraken2:

Kraken is a taxonomic sequence classifier that assigns taxonomic labels to DNA sequences. Kraken examines the k-mers within a query sequence and uses the information within those k-mers to query a database. That database maps k-mers to the lowest common ancestor (LCA) of all genomes known to contain a given k-mer.

To get a full list of options, use kraken2 --help.

Standard Kraken Output Format

• --use-names replaces the taxonomy ID column with the scientific name and the taxonomy ID in parenthesis (e.g., "Bacteria (taxid 2)").
• --report option writes out the sample report in tab-delimited format

Kraken 2's output contains:

1. "C"/"U": a one letter code indicating that the sequence was either classified or unclassified. A rank code, indicating (U)nclassified, (R)oot, (D)omain, (K)ingdom, (P)hylum, (C)lass, (O)rder, (F)amily, (G)enus, or (S)pecies.
2. The sequence ID, obtained from the FASTA/FASTQ header.
3. The taxonomy ID Kraken 2 used to label the sequence; this is 0 if the sequence is unclassified.
4. The length of the sequence in bp.
5. A space-delimited list indicating the LCA mapping of each k-mer in the sequence.

Running Kraken

this is the command from the manual: kraken2 --use-names --db $KRAKEN_DB seqs.fa --report kreport

Running a for loop on all fastq files for the code:

for infile in /databases/reads/*.fastq.gz
	do
		base=$(basename ${infile} .fastq.gz)
		kraken2 --use-names --db /databases/kraken_db/ --report ${base}.kreport --output ${base}.kraken2 ${infile} 
        done

4. Bracken:

Bracken (Bayesian Reestimation of Abundance with KrakEN) is a highly accurate statistical method that computes the abundance of species in DNA sequences from a metagenomics sample. Braken uses the taxonomy labels assigned by Kraken2 to estimate the number of reads originating from each species present in a sample.

Bracken Output File Format

Bracken output file; tab-delimited columns

Name Taxonomy ID Level ID (S=Species, G=Genus, O=Order, F=Family, P=Phylum, K=Kingdom) Kraken Assigned Reads Added Reads with Abundance Reestimation Total Reads after Abundance Reestimation Fraction of Total Reads

Running Bracken

Bracken can be run using either the bracken shell script or the est_abundance python script.

bracken -i input.kreport -d $KRAKEN_DB/ -r ${READ_LEN} -o output.bracken

${READ_LEN} default = 100

Our reads are 1x100bp so we do not need to specify. If you are using the pyhon script, you need to speficy the kmer distribution database corresponding to the Kraken database previously used and your read length.

python script alternative: python est_abundance.py -i input.kreport -k $KRAKEN_DB/database$READ_LENmers.kmer_distrib -o output.bracken

Running a for loop on all fastq files for the code:

for infile in *.kreport
	do
		base=$(basename ${infile} .kreport)
		bracken -i ${infile} -d /databases/kraken_db/ -o ${base}.bracken 
        done

5. KRONA

Report convertion

kreport2krona.py converts a Kraken-style report into Krona-compatible format (https://github.com/jenniferlu717/KrakenTools/blob/master/kreport2krona.py) this is the command from the manual: python kreport2krona.py -r mysample_bracken.kreport -o mysample.krona

Running a for loop on all fastq files for the code:

for infile in *_bracken_species.kreport
	 do
		base=$(basename ${infile} _bracken_species.kreport)
		kreport2krona.py -r ${infile} -o ${base}.krona
        done

Krona chart

Use ktImportText to create a chart based on a txt file that lists values and wedge hierarchies to add them to (https://github.com/marbl/Krona/wiki/Importing-text-and-XML-data):

ktImportText mysample.krona -o mysample.html

Running a for loop on all fastq files for the code:

for infile in *.krona
	do
		base=$(basename ${infile} .krona)
		ktImportText ${infile} -o ${base}.html
        done

In MobaXterm, you can easily access the data.

Saving Files:

After saving the files in the /database/user directory within the VM, they will appear in the /veme24 folder (server).

cp *.html /database/users
cd /database/users
ls -l
exit

Downloading Files:

Open a new terminal Example: To download the sample.txt file from the /veme24 folder using MobaXterm, run the following command:

Via SSH:

rsync -aP -e "ssh" veme@bagre.minas.fiocruz.br:/veme24/ /drives/c/Users/Administrator/Desktop
Password: J@k_bio24

Use the rsync command to download the files or install an FTP client (such as FileZilla or WinSCP) on your local desktop.

To access the data, use the /veme24 directory on the Bagre server:

Via FTP Client:(e.g., FileZilla, MobaXterm):

Host: bagre.minas.fiocruz.br

Username: veme

Password: J@k_bio24

Remote Directory: /veme24

Alternative Option:

Another option is to use the Windows Subsystem for Linux (WSL). It allows you to run a GNU/Linux environment directly on Windows without the need to install additional transfer tools like PuTTY or others.