rRNASelector

Running rRNASelector locally is an efficient way to process metagenomic and metatranscriptomic sequences to identify phylogenetic markers without relying on web servers. The software identifies ribosomal RNA sequences using Hidden Markov Models (HMMs) trained on well-curated databases.

Setting up a local environment for this involves specific prerequisites. Step 1: System and Software Prerequisites

Before running rRNASelector, ensure you have the following installed on your Linux or macOS system:

HMMER: Because rRNASelector relies heavily on Hidden Markov Models, you will need to install the hmmer package (typically version 3.0 or higher).

Perl: The wrapper scripts for rRNASelector are written in Perl.

Java: Often required if you are utilizing downstream pipelines or wrapped interfaces. Step 2: Download and Extract the Software

Navigate to the official download source or repository for rRNASelector (historically provided by the EzBioCloud/ChunLab team).

Download the source code archive (e.g., rRNASelector.tar.gz).

Extract the tarball in your desired local directory by running:tar -zxf rRNASelector.tar.gz Navigate into the newly created directory:cd rRNASelector Step 3: Compile and Prepare

If the source files contain C/C++ components or require compilation, follow standard GNU installation steps: ./configure make

make install (or ensure the executable paths are appended to your system’s PATH variable so you don’t have to write the full path each time). Step 4: Configure the Databases

rRNASelector works by scanning your sequence data against established databases of known ribosomal RNA signatures.

Download the reference rRNA profile HMM databases (usually included in the main software distribution or downloaded separately from the official release page).

Place these files in a dedicated db/ or data/ folder within your local installation directory. Step 5: Running rRNASelector

Once the environment and databases are properly configured, you can process your metagenomic or metatranscriptomic shotgun sequences. The basic command syntax generally follows this structure:

perl rRNASelector.pl -i input_sequences.fasta -o output_directory/ -d path/to/rRNA_database.hmm

-i: Specifies your input sequence file (usually in FASTA format).

-o: Specifies the directory where the detected rRNA genes will be saved.

-d: Points the program to the Hidden Markov Model database you downloaded in Step 4. Step 6: Post-Processing

After the script finishes execution, it will generate output files detailing which reads or contigs code for rRNA (e.g., 5S, 16S, 23S, or 26S regions). The non-rRNA sequences separated in the output directory can then be carried forward for protein-based or functional annotation. If you are planning a local setup, please tell me:

What operating system are you using (Linux, macOS, Windows)?

Are you looking to process massive high-throughput FASTQ files, or are you focusing on already assembled FASTA contigs? RNA Analyzer 3 Tutorial