LACA: Long Amplicon Consensus Analysis

LACA is a reproducible and scalable workflow for Long Amplicon Consensus Analysis, e.g., 16S rRNA gene. Using snakemake as the job controller, LACA is wrapped into a python package for development and mainteniance. LACA provides an end-to-end solution from bascecalled reads to the final count matrix.

Important: LACA is only tested in Linux systems, i.e., Ubuntu.

preprint on bioRxiv

Docker image

The easiest way to use LACA is to pull the docker image from Docker Hub for cross-platform support.

docker pull yanhui09/laca

To use the docker image, you need to mount your data directory, e.g., pwd, to the /home in the container.

docker run -it -v `pwd`:/home --privileged yanhui09/laca

Installation from GitHub repository

Conda is the only required dependency prior to installation. Miniconda is enough for the whole pipeline.

1. Clone the Github repository and create an isolated conda environment

git clone https://github.com/yanhui09/laca.git
cd laca
conda env create -n laca -f env.yaml 

You can speed up the whole process if mamba is installed.

mamba env create -n laca -f env.yaml 

2. Install LACA with pip

To avoid inconsistency, we suggest installing LACA in the above conda environment

conda activate laca
pip install --editable .

At this moment, LACA uses a compiled but tailored guppy for barcode demultiplexing (in our lab).
Remember to prepare the barcoding files in guppy if new barcodes are introduced.Click me

Example

laca init -b /path/to/basecalled_fastqs -d /path/to/database # init config file and check
laca run all # start analysis

Usage

Usage: laca [OPTIONS] COMMAND [ARGS]...
LACA: a reproducible and scaleable workflow for Long Amplicon Consensus
Analysis. To follow updates and report issues, see:
https://github.com/yanhui09/laca.
Options:
-v, --version Show the version and exit.
-h, --help Show this message and exit.
Commands:
init Prepare the config file.
run Run LACA workflow.

LACA is easy to use. You can start a new analysis in two steps using laca init and laca run .

Remember to activate the conda environment if LACA is installed in a conda environment.

conda activate laca

1. Intialize a config file with laca init

laca init will generate a config file in the working directory, which contains the necessary parameters to run LACA.

Usage: laca init [OPTIONS]
Prepare config file for LACA.
Options:
-b, --bascdir PATH Path to a directory of the basecalled fastq
files. Option is mutually exclusive with
'merge', 'merge_parent', 'demuxdir'.
-x, --demuxdir PATH Path to a directory of demultiplexed fastq
files. Option is mutually exclusive with
'merge', 'merge_parent', 'bascdir'.
--merge PATH Path to the working directory of a completed
LACA run [Mutiple]. Runs will be combined
if --merge_parent applied. Option is
mutually exclusive with 'bascdir',
'demuxdir'.
--merge-parent PATH Path to the parent of the working
directories of completed LACA runs. Runs
will be combined if --merge applied. Option
is mutually exclusive with 'bascdir',
'demuxdir'.
-d, --dbdir PATH Path to the taxonomy databases. [required]
-w, --workdir PATH Output directory for LACA. [default: .]
--demuxer [guppy|minibar] Demultiplexer. [default: guppy]
--fqs-min INTEGER Minimum number of reads for the
demultiplexed fastqs. [default: 1000]
--no-pool Do not pool the reads for denoising.
--subsample Subsample the reads.
--no-chimera-filt Do not filter chimeric reads.
--no-primer-check Do not check primer pattern.
--cluster [isONclust|umapclust|meshclust]
Cluster approaches. [Mutiple] [default:
isONclust, meshclust]
--consensus [kmerCon|miniCon|isoCon|umiCon]
Consensus methods. [Mutiple] [default:
kmerCon]
--quant [seqid|minimap2] Create abundance matrix by sequence id or
minimap2. [Mutiple] [default: seqid]
--uchime Filter chimeras by uchime-denovo in vsearch.
--jobs-min INTEGER Number of jobs for common tasks. [default:
2]
--jobs-max INTEGER Number of jobs for threads-dependent tasks.
[default: 6]
--ont Use config template for ONT reads. Option is
mutually exclusive with 'isoseq'.
--isoseq Use config template for PacBio CCS reads.
Option is mutually exclusive with 'ont'.
--longumi Use primer design from longumi paper (https:
//doi.org/10.1038/s41592-020-01041-y).
Option is mutually exclusive with
'simulate'.
--simulate Use config template for in silicon test.
Option is mutually exclusive with 'longumi'.
--clean-flags Clean flag files.
-h, --help Show this message and exit.

2. Start analysis with laca run

laca run will trigger the full workflow or a specfic module under defined resource accordingly. Get a dry-run overview with -n. Snakemake arguments can be appened to laca run as well.

Usage: laca run [OPTIONS] {demux|qc|clust|kmerCon|miniCon|isoCon|umiCon|quant|
taxa|tree|all|merge|initDB|simulate} [SNAKE_ARGS]...
Run LACA workflow.
Options:
-w, --workdir PATH Working directory for LACA. [default: .]
-c, --configfile FILE Config file for LACA. Use config.yaml in working
directory if not specified.
-j, --jobs INTEGER Maximum jobs to run in parallel. [default: 6]
-m, --maxmem FLOAT Specify maximum memory (GB) to use. Memory is
controlled by profile in cluster execution.
--profile TEXT Snakemake profile for cluster execution.
-n, --dryrun Dry run.
-h, --help Show this message and exit.