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# read2tree

read2tree is a software tool that allows to obtain alignment matrices for tree inference. For this purpose it makes use of the OMA DB and a set of reads. Its strength lies in the fact that it bipasses the several standard steps when obtaining such a matrix in regular analysis. These steps are read filtereing, assembly, gene prediction, gene annotation, all vs all comparison, orthology prediction, alignment and concatination. All this steps are included.

## Getting Started

read2tree was build and tested with python 3.5.1. To set up read2tree on your local machine please follow the instructions below.
```
git clone https://github.com/dvdylus/read2tree.git
python setup.py install
```
### Prerequisites

read2tree integrates multiple software tools and allows to infer a phylogenetic tree skipping several steps of a usual pipeline such as assembly, annotation and orthology prediction. It offers a fast alternative to usual tree inference pipelines.

* [mafft](http://mafft.cbrc.jp/alignment/software/) - Multiple sequence alignment software
* [fasttree](http://www.microbesonline.org/fasttree/) - Dependency Management
* [ngmlr](https://github.com/philres/ngmlr) - Long read mapper for ONT or PacBio read data
* [ngm](https://github.com/Cibiv/NextGenMap) - Short read mapper for paired end reads
* [pyopa](...) - Implementation of Smith Waterman alignment algorithm in python
* [pyoma](...) - Library for retrieval of nucleotide sequences from oma run
* [pyham](...) - Library to work with HOGs
* [samtools](http://www.htslib.org/download/) - Set of programs to interact with high-throughput sequencing data

### Installing
    
For mafft, fasttree, ngmlr, ngm and samtools please follow the instructions provided by the individual packages.
Make sure that executables are in PATH. Or you can just follow the instructions below, since all the packages are available under conda.

#### CONDA

1. Install [miniconda](https://conda.io/miniconda.html)
2. Setup [bioconda](https://bioconda.github.io/) channels
```
    conda config --add channels defaults
    conda config --add channels conda-forge
    conda config --add channels bioconda
```
3. Install required tools
```
    conda install mafft
    conda install fasttree
    conda install ngmlr
    conda install nextgenmap
    conda install samtools
    conda install pysam
```

#### Python

1. Install the tool
```
    python setup.py install
```

#### Running the tests

Once successfully installed you can test the package using:
```
python -W ignore bin/read2tree --standalone_path tests/data/marker_genes/ --reads tests/data/mapper/test3/test_1a.fq tests/data/mapper/test3/test_2a.fq  --output_path test/output/

```
In the folder 'tests/data/output' you should be able to find the following folders:

| folder/file  | description           | 
| ------------- |-------------|
| 01_ref_ogs_aa | contains the selected OGs with amino acid data | 
| 01_ref_ogs_dna | contains the selected OGs with dna data |
| 02_ref_dna | contains the OGs reshuffeled by available species | 
| 03_align_aa | contains mafft alignment of aa data|
| 03_align_dna | contains codon replacement of aa alignments|
| 04_mapping_test_1b |contains the consensus sequences from the mapping|
| 05_ogs_map_test_1b_aa | contains the OGs with additional sequence test_1b|
| 05_ogs_map_test_1b_dna | contains the OGs with additional sequence test_1b|
| 06_align_test_1b_aa | contains the alignment with additional sequence test_1b|
| 06_align_test_1b_dna | contains the alignment with additional sequence test_1b|
| concat_test_1b_aa.phy | concatenated alignments from 06 amino acid folder|
| concat_test_1b_dna.phy| concatenated alignments from 06 dna folder|
| test_1b_all_cov.txt | summary of average numbers of reads used for selected sequences|
| test_1b_all_sc.txt | summary of average consensus length of reconstructed sequences|

## Running

To run read2tree two things are required as input:
1) The reads directly or as SRA or ENA submission index (submission scripts for lsf and sge are porvided (check the scripts folder))
2) As set of reference orthologous groups from the omabrowser that can be obtained with either the [All vs All](https://omabrowser.org/oma/export/) export or the [marker gene](https://omabrowser.org/oma/export_markers) export. This also means that some beforehand knowledge about the species to place or to add is required

#### Prerequisites

* Make sure that species names are clearly labeled by a 5 letter code (e.g. Amphiura filiformis = AMPFI)
* Needs either OMA standalone export or OMA marker gene export as reference input
* If you are using your own OMA run the formatting is crucial

#### Running on clusters

* Run the first step of read2tree such that folders 01, 02 and 03 are computed (this allows for mapping). This can be done using the '--reference' option.
* Since read2tree re-orders the OGs into the included species, it is possible to split the mapping step per species using multiple threads for the mapper. For this the '--single_mapping' option is available.

### LSF

### SGE

## Built With

* [pyCharm](https://www.jetbrains.com/pycharm) - Python IDE

## Contributing

Please read [CONTRIBUTING.md](https://gist.github.com/PurpleBooth/b24679402957c63ec426) for details on our code of conduct, and the process for submitting pull requests to us.

## Versioning

We use [SemVer](http://semver.org/) for versioning. For the versions available, see the [tags on this repository](https://github.com/your/project/tags).

## Authors

* **David Dylus** - *Initial work* - [dvddylus](https://github.com/dvdylus)

## License

This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details

## Acknowledgments

* Alex Warwick for help how to initiate such a package.
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