HmmUFOtu is an HMM based Ultra-fast OTU assignment tool for baterial 16S and amplicon sequencing research, it has two core algorithms, the CSFM-index powered banded-HMM algorithm, and SEP local phylogenetic-placement based taxonomy assignment algorithm.

The main program 'hmmufotu' takes single or paired-end NGS FASTA/FASTQ reads and generate tab-delimited outputs of the taxonomy assignment results of every read. This program supports native multi-threading and SSE2 and up Vectorization.

HmmUFOtu supports all major DNA substitution models, including

• GTR
• TN93
• HKY85
• F81
• K80
• JC69

HmmUFOtu supports variable mutation rate phylogenetic evaluation using the Discrete Gamma (dΓ) models (Yang 1994).

Zheng, Q., Bartow-McKenney, C., Meisel, J. S., & Grice, E. A. (2018). HmmUFOtu: An HMM and phylogenetic placement based ultra-fast taxonomic assignment and OTU picking tool for microbiome amplicon sequencing studies. Genome biology, 19(1), 82. PubMed ID: 29950165

HmmUFOtu is written in pure C++98, and built with the GNU Autotools (autoconfig/automake), and can be easily installed under Linux, Windows and Mac OS X.

You can download the latest release from GitHub at: https://github.com/Grice-Lab/HmmUFOtu/releases. You can clone or fork and pull the source codes from GitHub at: https://github.com/Grice-Lab/HmmUFOtu.

HmmUFOtu depends on the popular head-only C++ libraries Boost and Eigen3. They are available and often pre-installed on most Linux distributions, and can be easily installed on Windows and Mac OS X. The ZLIB and Boost-IOSTREAMS libraries are optionally dependent for handling GZIP/GZIP2 compressed files, but are not required and can be disabled. The JSONCPP C++ library is optionally dependent for formatting HmmUFOtu's assignment output into standard .jplace output; if "jsoncpp" library is found or specified during the configuring step, an optional program hmmufotu-jplace will be installed.

1. Configure installation, by running the command

./configure

You may consider providing additional options, such as --prefix, --exec-prefix, --with-zlib, --with-boost, --with-jsoncpp, etc.

2. Compile and link, by running the command

make

Look for errors and try to resolve them yourself first (by Google). Contact us only if you are sure it is a bug in our programs.

3. (Optionally) Test, by running the command

make check

It may take a while depending on your processor's speed.

4. Install

make install

You may need root privilege to do it, such as using sudo.

The main program 'hmmufotu' generates tab-delimited tables (TSV files), and is self explanatory. One other major program 'hmmufotu-sum' generates TSV format OTU tables (Operational Taxonomic Tables), which is compatitable with 3rd party tools such as QIIME.

You need to build an HmmUFOtu database before assigning taxonomies to your 16S or other target-loci sequencing reads. You can build your own database using hmmufotu-build, or alternatively download the pre-built databases.

Core programs are fundamental tools for taxonomy assignment analysis of 16S and other target-amplicon sequencing data. Core programs include:

• hmmufotu-build build an HmmUFOtu database with indexed multiple-sequence alignment (MSA), trained HMM profile, and pre-evaluated phylogenetic tree from reference MSA and tree files
• hmmufotu perform HMM-alignment, phylogenetic-placement based taxonomy assignment for single or paired-end NGS reads
• hmmufotu-sum summarize and generate phylogeny-based OTUs and consensus/prior based OTU representatives by summarizing over multiple assignment results (samples)
• hmmufotu-inspect inspect an HmmUFOtu database, and optionally export its contents

HmmUFOtu distributions contain pre-trained DNA substitution models and Dirichlet density/mixture models required for buiding HmmUFOtu databases. However, the users can train their own models with customized datasets. Model training programs include:

• hmmufotu-train-dm train an HmmUFOtu prior model using Dirichlet Density/Mixture models with customized data
• hmmufotu-train-hmm train a Banded-HMM model with customized data
• hmmufotu-train-sm train a DNA Substitution Model with customized data

Beside its core functionality, HmmUFOtu can perform many additional analysis using the utility programs. Utility programs include:

• hmmufotu-anneal anneal primer sequences to an HmmUFOtu database and evaluate the primer efficiency
• hmmufotu-sim generate simulated single or paired-end NGS reads, aligned or un-aligned, using a pre-built HmmUFOtu database
• hmmufotu-subset subset (subsample) an OTUTable so every sample contains the same mimimum required reads, and prune the samples and OTUs if necessary
• hmmufotu-norm normalize an OTUTable so every sample contains the same number of reads, you can generate a relative abundance OTUTable using a constant of 1
• hmmufotu-merge merge two or more OTUTables, redundant OTUs and samples will be aggregated, an optional merged OTU-tree can also be generated providing the corresponding database
• hmmufotu-jplace format HmmUFOtu's assignment output into standard .jplace file for compatibility of third party tools