Analysis tool for metataxonomics using 16S-23S rRNA operon region.
With the advancement of long-read sequencing technologies, the field of metataxonomics has entered a new phase. Analyzing the 16S-23S rRNA operon region (~4,300 bp) for bacterial community profiling provides more taxonomic information than analyzing only partial 16S rRNA gene sequences using short-read sequencing, allowing for species-level analysis. MIrROR provides a curated database and analysis tool for metaxonomics using 16S-23S rRNA operon region.
# For dependencies
conda install -c bioconda minimap2 # long-read mapper
conda install -c bioconda krona rename # Krona plot
pip install pandas matplotlib # Stacked bar plot
# Getting Started
git clone https://github.com/seoldh/MIrROR.git
cd MIrROR
./MIrROR.py -h
# Download 16S-23S rRNA operon database
mkdir DBDIR
wget -P DBDIR http://mirror.egnome.co.kr/media/ToolsDatabase/2021_06/MIrROR_DB_r01.mmi
wget -P DBDIR http://mirror.egnome.co.kr/media/ToolsDatabase/2021_06/MIrROR_DB_r01.tsv
# Usage examples
./MIrROR.py -K -d DBDIR -o result_BC01 ./sample_data/BC01.fastq # for single FASTQ file with Krona plot
./MIrROR.py -V -d DBDIR -o result_paf ./sample_data/list_PAF.txt # for alignment files with Krona and stacked bar plot
MIrROR uses a 16S-23S rRNA operon database curated over several steps.
See MIrROR Website for more information.
MIrROR uses long-read mapper, Minimap2. Please make sure that Minimap2 added to the path.
For visualizations, MIrROR has the following dependencies:
- KronaTools
- Python packages
The program can be executed without installation.
git clone http://github.com/seoldh/MIrROR.git
cd MIrROR
./MIrROR.py -hUsage: MIrROR.py [options] (-d DBDIR) INPUTFILE
MIrROR: a tool for metataxonomics with 16S-23S rRNA operon region.
INPUTFILE: FASTA/FASTQ/PAF | SAMPLELIST
Main options:
-d DBDIR, --db_dir=DBDIR
directory containing MIrROR database [required]
-o OUTDIR, --output_dir=OUT_DIR
specify directory to output files (default : ./Result)
-t INT, --threads=INT
number of threads (default : 4)
Mapping option:
this option control for Mapping
-M NUM, --minibatch=NUM
number of query bases loaded to the memory at once. K/M/G/k/m/g suffix is accepted. (default : 500M)
Threshold options:
these options control for Threshold
-m INT, --residuemaches=INT
number of residue matches (default : 2500)
-b INT, --blocklength=INT
alignment block length (default : 3500)
-n, --Normalization
normalize by 16S-23S rRNA operon copy number
Visualization options:
these options control for Visualization
-K, --Krona
create a Krona plot. Requires KronaTools to be installed.
-S, --Stacked_plot
create a stacked bar plot. Requires Python packages to be installed.
-V, --visualized
perform all visualization tasks (Same as: -K -S)
Help:
-h, --help show this help message and exit
-v, --version show version number and exit
MIrROR requires a FASTA/FASTQ/PAF file or a sample list as input. The mapping process is skipped if the user only provides PAF file(s).
The sample list can contain one or more group information (tab-delimited). Also, it can contain PAF and FASTA/FASTQ files together.
more list.txt
Sample Status Smoke
BC01.fastq Healthy smoker
BC02.fastq Healthy non-smoker
BC03.paf Sick smoker
BC04.paf Sick non-smoker
The database path must be specified, and you can download the latest release from here. In DBDIR, there are two requirements:
- MIrROR_DB_r01.mmi (minimap2 index)
- MIrROR_DB_r01.tsv (taxonomy,
accession<tab>taxonomy)
cd DBDIR
ls
MIrROR_DB_r01.mmi MIrROR_DB_r01.tsv
All output files are located in the directory specified by OUT_DIR.
| Directory | Output file name | Description |
|---|---|---|
| ./ | ||
| RESULT.log | log file | |
| ./mapping | ||
| SAMPLE.paf | result of minimap2 | |
| SAMPLE.paf.log | log file for mapping | |
| ./classification | ||
| SAMPLE.txt | classification result for each sample | |
| ./OTUtable | ||
| OUTPUT_std.txt | abundance table (standard version) | |
| OUTPUT_std_type2.txt | abundance table (standard version) | |
| OUTPUT_mpa.txt | abundance table (MetaPhlAn version) | |
| ./visualization | ||
| stacked_phylum.png | stacked bar plot for phylum level | |
| ··· | ··· | |
| stacked_species.png | stacked bar plot for species level | |
| ./visualization/krona | ||
| SAMPLE.html | krona plot for each sample | |
| SAMPLE.tsv | percent information for krona |
MIrROR provides abundance tables in two forms.
vi OUTPUT_std.txt
Name BC01 BC02 BC03 BC04
status Healthy Healthy Sick Sick
smoke smoker non-smoker smoker non-smoker
p__Firmicutes;c__Clostridia;o__Clostridiales;f__Lachnospiraceae;g__Butyrivibrio;s__Butyrivibrio_fibrisolvens 51 19 49 13
p__Firmicutes;c__Clostridia;o__Clostridiales;f__Ruminococcaceae;g__Faecalibacterium;s__Faecalibacterium_prausnitzii 25 24 30 7
vi OUTPUT_mpa.txt
Name BC01 BC02 BC03 BC04
status Healthy Healthy Sick Sick
smoke smoker non-smoker smoker non-smoker
p__Firmicutes; 99 78 60 76
p__Firmicutes;c__Clostridia; 15 8 16 7
Please cite this paper when using MIrROR for your publications.
Microbial Identification Using rRNA Operon Region: Database and Tool for Metataxonomics with Long-Read Sequence.
Microbiology Spectrum, 10(2):e02017-21 (2022). https://doi.org/10.1128/spectrum.02017-21
Donghyeok Seol, Jin Soo Lim, Samsun Sung, Young Ho Lee, Misun Jung, Seoae Cho, Woori Kwak, and Heebal Kim.