Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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✓DOI references
Found 8 DOI reference(s) in README -
○Academic publication links
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✓Committers with academic emails
3 of 6 committers (50.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (11.5%) to scientific vocabulary
Repository
mixed sample analysis
Basic Info
- Host: GitHub
- Owner: balabanmetin
- Language: Python
- Default Branch: master
- Size: 90.8 KB
Statistics
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 1
- Releases: 0
Metadata Files
README.md
Summary
MISA stands for MIxed Sample Analysis tool and addresses the problem of phylogenetic double placement of mix (of two) DNA sequences into an already existing reference tree. MISA is a command-line tool and it can run on Linux, Mac OSX, and Windows.
Publication
- Balaban, Metin, and Siavash Mirarab. “Phylogenetic double placement of mixed samples.” Bioinformatics (Oxford, England) vol. 36,Supplement_1 (2020): i335-i343. https://doi.org/10.1093/bioinformatics/btaa489
Requirements
- Python: Version >= 3.0
Installation on Linux, Mac OSX, or Windows
Install MISA using the following command in the command-line:
pip install misa
Getting Started with MISA
For listing all options, run the following command:
run_misa.py -h
Input & Output Specification
Input reference (backbone) tree must be in newick format. MISA can perform placements based on a distance table. Distance table between the query and reference sequences can be computed using https://github.com/shahab-sarmashghi/Skmer. These distances can be based on assemblies or unassembled bag of reads (genome skims).
Input a distance matrix
The format for distance matrix is a tab delimited csv file with column and row headers. Rows should represent query sequences and columns should represent reference sequences. You can find an example reference dataset with backbone phylogenetic tree under data/backbone.nwk and distance matrix for one query mixed sequence under data/dist.mat. After cloning this repository, you can run MISA on the example distance matrix and backbone tree by running the following command:
run_misa.py -d <path_to_this_repo>/data/dist.mat -t <path_to_this_repo>/data/backbone.nwk
Output
Output is a jplace file containing placement results for all queries. For more information about jplace files, please refer to Matsen et. al. (2012) https://doi.org/10.1371/journal.pone.0031009. The output file can be specified using -o command. When output file is not specified, the result will be printed to the standard output.
! IMPORTANT NOTE !
Backbone tree provided to MISA has to have its branch lengths estimated using a distance based method such as minimum evolution. This is a requirement for getting good results. We recommend FastTree2 for re-estimating branch lengths if the backbone tree is estimated using Maximum Likelihood based methods (e.g. RAxML, PASTA). Until we support re-estimation of branch lengths within MISA, we are expecting the user to run the following FastTree2 command explicitly before performing any placement:
FastTreeMP -nosupport -nt -nome -noml -log tree.log -intree backbone.nwk < ref.fa > minimum_evo_backbone.nwk
Then perform placement on the new tree:
run_misa.py -d dist.mat -t minimum_evo_backbone.nwk
(Alternative) Installation from github
If you want to install MISA from the github repository, MISA has the following dependencies which can be retrieved from pip:
treeswiftnumpyscipy
To install a dependency, for example scipy, run pip3 install scipy.
Clone the repository and change directory:
git clone https://github.com/balabanmetin/misa.git && cd misa
Data resources used in the publication
The data used in our publication is available on GitHub https://github.com/balabanmetin/misa-data
Owner
- Login: balabanmetin
- Kind: user
- Repositories: 53
- Profile: https://github.com/balabanmetin
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Committers
Last synced: almost 3 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Metin Balaban | b****n@t****u | 9 |
| Metin Balaban | m****n@M****m | 7 |
| Metin Balaban | m****n@M****l | 6 |
| Metin Balaban | m****a@c****r | 3 |
| Metin Balaban | m****n@w****u | 2 |
| balabanmetin | b****n@u****u | 2 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 1
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 1
- Total pull request authors: 0
- Average comments per issue: 1.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- smirarab (1)
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 36 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 1
- Total maintainers: 1
pypi.org: misa
MISA: a mixed samples analysis tool
- Homepage: https://github.com/balabanmetin/misa
- Documentation: https://misa.readthedocs.io/
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Latest release: 1.0.0
published almost 6 years ago
Rankings
Maintainers (1)
Dependencies
- numpy *
- scipy *
- treeswift *