Microbial 'omics

Brought to you by

anvi-trnaseq [program]

A program to process raw tRNA-seq dataset, which is the sequencing of tRNA transcripts in a given sample, to generate an anvi'o tRNA-seq database.

See program help menu or go back to the main page of anvi’o programs and artifacts.

Table of Contents

Can provide


Can consume



The input for this program is a properly formatted trnaseq-fasta, containing sequences from a tRNA-seq sample or split.

The program identifies tRNA among the input sequences, profiles the tRNA primary sequence and secondary structure, and filters single nucleotide variants from modified nucleotides.

The primary output of the program is a trnaseq-db. Supplemental files are also produced: an analysis summary file, a tab-separated file of unique sequences not identified as tRNA, and a tab-separated file showing the range of 5’ and 3’ variants trimmed from tRNA sequences.

We encourage you to read the list of options in the anvi-trnaseq --help menu to understand how the user can manipulate the multifaceted analyses performed by the program.

The program can generate a .ini file for tRNA feature parameterization using an alternate command, anvi-trnaseq --default-feature-param-file <param.ini>. The default parameterizations in the file can be modified by the user, and the file can be used as the --feature-param-file argument in the main mode of the program. anvi-trnaseq --print-default-feature-params can also be used to quickly and neatly display the defaults in the terminal.

Create a tRNA-seq database from a FASTA file, using 16 cores

anvi-trnaseq -f trnaseq-fasta \ -S example_sample_name \ -o example_empty_output_directory_path \ -T 16

Create a tRNA-seq database from a sample identified as a demethylase split, overwriting the output directory if it already exists

anvi-trnaseq -f trnaseq-fasta \ -S example_sample_name \ -o example_empty_output_directory_path \ -T 16 \ --treatment demethylase \ -W

Edit this file to update this information.

Additional Resources

Are you aware of resources that may help users better understand the utility of this program? Please feel free to edit this file on GitHub. If you are not sure how to do that, find the __resources__ tag in this file to see an example.