SanGro is a simple phylogenetics pipeline executed through nextflow designed to construct a phylogeny from single gene sequences such as Sanger sequencing results or viral genes. It accomplishes this by collating individual sequence files into a multiple sequence file with a custom python script (COLLATE), aligning the resulting file with mafft (MAFFT), masking the alignment for missing data with trimal (TRIMAL), and creating a ML phylogeny by iqtree2 (IQTREE).
- Automated through nextflow with minimal user input
- Designed for single sequences
- Scalable and customizeable for custom use
- Fast, often producing trees from sequences in <5 minutes
- Input: metadata file, shell script
- Output: ML phylogeny
A metadata .csv file is required to initiate SanGro. This file is structured in the following format:
id,gene
taxonA,/file/path/to/taxonA.fasta
taxonB,/file/path/to/taxonB.fasta
The id column represents the name of the taxon to be represented in the phylogeny and the gene column denotes a full path to the sequence file.
SanGro is initiated through a shell script that resembles the following:
nextflow run ../sangro/main.nf \
--input metadata.csv \
--publish_dir test_run/ \
--masking_threshold 0.4 \
-profile local, eight \
-resume
There are five possible parameters, which are listed below:
| parameter | description | is required? | input type |
|---|---|---|---|
| --input | a file path to the metadata file | yes | string |
| --publish-dir | a directory where output will be stored | yes | string |
| --masking_threshold | the percentage of missing data required for masking | no | value |
| --no_mafft | bypass the alignment step with mafft, off by default | no | boolean |
| --mask_data | mask missing data with trimal, defaults to no | no | boolean |
| -profile | a profile detailing computational requirements of job | yes | string |
| -resume | if pipeline is suspended and reinitiated, it will begin where it left off | no | N/A |
Configuration files located in sangro/config/local.conf are referenced by SanGro to determine the computational requirements of the pipeline. Two profiles exist, local, four which designates four cores to SanGro, and local, eight which designates eight. One must be chosen in the -probile parameter within the shell script to initiate SanGro.
SanGro requires nextflow and singularity to run. Clone github repository to install SanGro.
An example run of SanGro using Diptera COI sequences is provided in sangro/example_run. Sample sequences for this example are stored in sangro/example_run/sequence_data.
This dataset is designed to test the monophyly of Aedes, Anopheles, and Culex within Culicidae using two Dixidae specimens as outgroup taxa.
Metadata of sequences is provided below:
| id | organism | NCBI accession number |
|---|---|---|
| Daestiv | Dixella aestivalis | NC_029354.1 |
| Dsubmac | Dixa submaculata | KX453764.1 |
| Acinreus | Aedes cinreus | OP828905.1 |
| Avexans | Aedes vexans | KC855606.1 |
| Cspinosus | Culex spinosus | KM593059.1 |
| Cdeclarator | Culex declarator | KM593057.1 |
| Aneomac | Anopheles neomaculipalpus | KM592986.1 |
| Akleini | Anopheles kleini | KC855665.1 |
| Alesteri | Anopheles lesteri | KC855664.1 |
To run SanGro, execute the shell script provided in sangro/example_run/run_sangro.sh with the following command within the sangro/example_run directory:
sh run_sangro.sh
Upon initiation, the nextflow interface will appear and the pipeline will run to completion or exit due to an error.
Output of SanGro is stored in the directory created by the --publish-dir parameter within the run_sangro.sh shell script.
For this example, access results by navigating to test_run/project/publish/iqtree and downloading the trimal.treefile file inside it.
The phylogeny produced by SanGro may be vizualised by importing trimal.treefile into a program such as iTOL or FigTree. The resulting phylogeny, appropriately rooted upon the clade representing Dixidae, is shown below:
(image goes here)
The most commonly observed error is the termination of SanGro in the PARSE_METADATA step of the pipeline. This is often due to the incorrect input of data in the metadata.csv input file. If this occurs, ensure this file is correctly populated with sequence information and paths.
If other errors are encountered, please submit a comment in the Issues tab of this github page so that they may be promptly addressed and resolved.