A Mamba installs

A.1 Mamba installation and environment

Mamba is a reimplementation of conda. It is a great tool for installing bioinformatic packages including R packages.

Mamba github: https://github.com/mamba-org/mamba

The best way to use Mamba is to install Miniforge. It has both Conda and Mamba commands.

Miniforge installation: https://github.com/conda-forge/miniforge

Mamba guide: https://mamba.readthedocs.io/en/latest/user_guide/mamba.html

To create the mamba environment shotgun_meta run the below commands in your bash. You will need to have installed mamba first.

#shotgun_meta
mamba create -n shotgun_meta
mamba activate shotgun_meta
#Install packages
mamba install -c bioconda fastqc trim-galore multiqc bowtie2 kraken2 \
krona bracken lefse flash megahit quast metabat2 prokka bbmap bakta circos
#Update krona taxonomy database
ktUpdateTaxonomy.sh
#Install GenoVi via pip
pip install genovi

You will need to install the Bakta database as well. This requires you have a directory to store the database. In the below example you will need a directory with the path ~/databases/bakta_db, of course feel free to use a different location you have.

bakta_db download --output ~/databases/bakta --type full

Install MinPath via git. I suggest creating a directory called "git_installs" in your home directory and running this code there.

#git_installs directory
mkdir ~/git_installs
cd ~/git_installs
#MinPath
git clone https://github.com/mgtools/MinPath

To run MinPath in your own machines you will need to use the full path of the python file. If you installed these in your "~/git_installs" examples are below.

#MinPath help page
python ~/git_installs/Minpath/MinPath.py -h

To create the mamba environment cocopye run the below commands in your bash. You will need to have installed mamba first.

#checkm
mamba create -n cocopye
mamba activate checkm2
mamba install bioconda::checkm2=1.1.0
#Download required databases
checkm2 database --download

To create the mamba environment biobakery3.9 run the below commands in your bash. You will need to have installed mamba first.

#biobakery3
mamba create -n biobakery3.9
mamba activate biobakery3.9
#Add required channels
conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge
conda config --add channels biobakery
#Install huamnn3.9
mamba install -c biobakery humann=3.9
#Install hclust2 and matplotlib
mamba install bioncda::hclust2=1.0.0 conda-forge::matplotlib=3.7.3

Next you will need to install the HUMAnN and MetaPhlAn databases.

#Ensure you have biobakery3 mamba environment activated
#Update HUMAnN databases
humann_databases --download chocophlan full /path/to/databases --update-config yes
humann_databases --download uniref uniref90_diamond /path/to/databases --update-config yes
humann_databases --download utility_mapping full /path/to/databases --update-config yes
#Install MetaPhlAn databases
metaphlan --install --index mpa_vOct22_CHOCOPhlAnSGB_202403

Installing the MetaPhlAn databases may not work with the command above. If not follow the below instructions.

Go to the following link: http://cmprod1.cibio.unitn.it/biobakery4/metaphlan_databases/
Download the following files (or the most recent vOct22 files):
Put these in the MetaPhlAn databases directory. This will be in your mamba environment directory.
- E.g.: ~/mambaforge/envs/biobakery3.9/lib/python3.7/site-packages/metaphlan/metaphlan_databases
- Note: this may not be your exact path.
Run metaphlan --install --index mpa_vOct22_CHOCOPhlAnSGB_202403 again.
Untar the CHOCOPhlan tar file
- Change directory to your MetaPhlAn database directory.
- tar -xvf mpa_vOct22_CHOCOPhlAnSGB_202403.tar

Once the databses are all setup you can test HUMAnN.

humann_test

B Next steps

Below are some good links to start with before carrying out your own projects.

KrakenTools: A suite of scripts to be used alongside the Kraken, KrakenUniq, Kraken 2, or Bracken programs.
- https://github.com/jenniferlu717/KrakenTools
A review of computational tools for generating metagenome-assembled genomes from metagenomic sequencing data
- https://www.sciencedirect.com/science/article/pii/S2001037021004931
A review paper on metagenome assembly approaches
- Genome-resolved metagenomics using environmental and clinical samples: https://academic.oup.com/bib/advance-article/doi/10.1093/bib/bbab030/6184411
bioBakery tools for meta'omic profiling
- https://github.com/biobakery/biobakery
Assessing the performance of different approaches for functional and taxonomic annotation of metagenomes
- https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-019-6289-6
MicrobeAnnotator: Easy-to-use pipeline for the comprehensive metabolic annotation of microbial genomes.
- https://github.com/cruizperez/MicrobeAnnotator
MetaEuk: Functional annotation of eukaryotic metagenome
- https://github.com/soedinglab/metaeuk _ Methods for Metagenomic data visualisation and analysis
- https://www.researchgate.net/publication/318252633_Methods_for_The_Metagenomic_Data_Visualization_and_Analysis
Visualizing metagenomic and metatranscriptomic data: A comprehensive review
- https://www.sciencedirect.com/science/article/pii/S2001037024001430

C Manuals

Conda: https://conda.io/projects/conda/en/latest/user-guide/getting-started.html

FastQC: https://www.bioinformatics.babraham.ac.uk/projects/fastqc/

MultiQC: https://multiqc.info/

Trim Galore: https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/

Bowtie2: http://bowtie-bio.sourceforge.net/bowtie2/manual.shtml

samtools: http://www.htslib.org/

BBTools: https://jgi.doe.gov/data-and-tools/bbtools/

Kraken2: https://github.com/DerrickWood/kraken2/wiki/Manual

Krona: https://github.com/marbl/Krona/wiki/KronaTools

Bracken: https://ccb.jhu.edu/software/bracken/index.shtml?t=manual

LEfSe: https://huttenhower.sph.harvard.edu/lefse/

HUMAnN 3.0: https://huttenhower.sph.harvard.edu/humann/

MetaPhlAn 4.0: https://github.com/biobakery/MetaPhlAn/wiki/MetaPhlAn-4

Biobakery: https://github.com/biobakery/biobakery

hclust2: https://github.com/SegataLab/hclust2

MegaHit: https://github.com/voutcn/megahit

BWA: https://github.com/lh3/bwa

minimap2: https://github.com/lh3/minimap2

MetaBAT2: https://bitbucket.org/berkeleylab/metabat/src/master/

CoCoPyE: https://github.com/gobics/cocopye

PhyloPhlAn: https://github.com/biobakery/phylophlan/wiki

Prokka: https://github.com/tseemann/prokka

MinPath: https://github.com/mgtools/MinPath/blob/master/readme

MetaCyc: https://metacyc.org/

D Obtaining Read Data

The following commands can be used to obtain the sequence data used in this practical, directly from the EBI metagenomics site. It is worth noting that these are the full set of data, not like the miniaturised version you have used in the tutorial.

wget -O K1_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505102/ERR505102_1.fastq.gz
wget -O K1_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505102/ERR505102_2.fastq.gz
wget -O K2_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505104/ERR505104_1.fastq.gz
wget -O K2_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505104/ERR505104_2.fastq.gz
wget -O K3_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505095/ERR505095_1.fastq.gz
wget -O K3_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505095/ERR505095_2.fastq.gz
wget -O K4_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505096/ERR505096_1.fastq.gz
wget -O K4_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505096/ERR505096_2.fastq.gz
wget -O K5_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505097/ERR505097_1.fastq.gz
wget -O K5_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505097/ERR505097_2.fastq.gz
wget -O K6_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505098/ERR505098_1.fastq.gz
wget -O K6_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505098/ERR505098_2.fastq.gz
wget -O K7_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505099/ERR505099_1.fastq.gz
wget -O K7_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505099/ERR505099_2.fastq.gz
wget -O K8_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505100/ERR505100_1.fastq.gz
wget -O K8_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505100/ERR505100_2.fastq.gz
wget -O K9_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505101/ERR505101_1.fastq.gz
wget -O K9_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505101/ERR505101_2.fastq.gz
wget -O K10_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505103/ERR505103_1.fastq.gz
wget -O K10_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505103/ERR505103_2.fastq.gz
wget -O K11_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505105/ERR505105_1.fastq.gz
wget -O K11_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505105/ERR505105_2.fastq.gz
wget -O K12_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505106/ERR505106_1.fastq.gz
wget -O K12_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505106/ERR505106_2.fastq.gz
wget -O W1_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505090/ERR505090_1.fastq.gz
wget -O W1_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505090/ERR505090_2.fastq.gz
wget -O W2_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505088/ERR505088_1.fastq.gz
wget -O W2_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505088/ERR505088_2.fastq.gz
wget -O W3_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505084/ERR505084_1.fastq.gz
wget -O W3_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505084/ERR505084_2.fastq.gz
wget -O W4_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505085/ERR505085_1.fastq.gz
wget -O W4_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505085/ERR505085_2.fastq.gz
wget -O W5_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505086/ERR505086_1.fastq.gz
wget -O W5_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505086/ERR505086_2.fastq.gz
wget -O W6_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505087/ERR505087_1.fastq.gz
wget -O W6_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505087/ERR505087_2.fastq.gz
wget -O W7_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505089/ERR505089_1.fastq.gz
wget -O W7_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505089/ERR505089_2.fastq.gz
wget -O W8_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505091/ERR505091_1.fastq.gz
wget -O W8_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505091/ERR505091_2.fastq.gz
wget -O W9_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505092/ERR505092_1.fastq.gz
wget -O W9_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505092/ERR505092_2.fastq.gz
wget -O W10_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505093/ERR505093_1.fastq.gz
wget -O W10_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505093/ERR505093_2.fastq.gz
wget -O W11_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505094/ERR505094_1.fastq.gz
wget -O W11_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505094/ERR505094_2.fastq.gz
wget -O W12_R1.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505083/ERR505083_1.fastq.gz
wget -O W12_R2.fastq.gz ftp://ftp.sra.ebi.ac.uk/vol1/fastq/ERR505/ERR505083/ERR505083_2.fastq.gz