semvec/pypi-packages huggingface dataset:
mrsr 0.0.5
A simple implementation of the multiresponse sparse regression (MRSR) algorithm.
License: MIT

# mrsr

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`mrsr` is a Python module implementing the [Multiresponse Sparse Regression algorithm][1] clustering algorithm.

## instalation
the `mrsr` package is available in [PyPI](https://pypi.org/project/mrsr/). to install, simply type the following command:
```
pip install mrsr
```

## how to cite mrsr package
if you use `mrsr` package in your paper, please cite it in your publication.
```
@misc{mrsr,
    author       = "Madson Luiz Dantas Dias",
    year         = "2019",
    title        = "mrsr: a Python module implementing the Multiresponse Sparse Regression algorithm.",
    url          = "https://github.com/omadson/mrsr",
    institution  = "Federal University of Cear\'{a}, Department of Computer Science" 
}
```

## contributing

this project is open for contributions. here are some of the ways for you to contribute:
 - bug reports/fix
 - features requests
 - use-case demonstrations

to make a contribution, just fork this repository, push the changes in your fork, open up an issue, and make a pull request!

## contributors
 - [Madson Dias](https://github.com/omadson)

[1]: https://doi.org/10.1109/IJCNN.2006.246933
[2]: http://scikit-learn.org/
vbtools 0.1.0
A pipeline for analyzing fungal genomic data
License: MIT
Keywords: bioinformatics

# vbtools: a variant benchmark tool to compare VCFs with a consensus set
## Install
Before installation, make sure [conda](https://docs.conda.io/en/latest/miniconda.html) is under your `PATH`. Conda installation [here](https://docs.conda.io/en/latest/miniconda.html).

```sh
# clone this repo
git clone git@github.com:broadinstitute/vbtools.git

# setup conda environment
cd vbtools

conda env create -f env.yml # this will take a few minutes
conda list  # verify new environment was installed correctly

# activate environment
conda activate vbtools

# deactivate the environment when done
conda deactivate

# completely remove the virtual environment
conda remove -name vbtools --all
```

## Usage
You can use following command to benchmark a VCF against a reference/consensus VCF.
```sh
vcfbench.py -v <input.vcf> -b <reference.vcf>
```
`--prefix` is an option to define prefix to the output files.

Currently, only haploid VCF is supported in the analysis. Diploid VCF will be standardized into haploid before comparison. Input VCF should follow [VCF spec v4.2](https://samtools.github.io/hts-specs/VCFv4.2.pdf).

Following pre-processing steps are performed on the input VCF before the analysis:
1) remove unused alleles
2) remove monomorphic sites
3) remove sites with heterozygous genotypes
4) remove non-SNP sites
5) remove sites with asterisk marks
6) change diploid to haploid VCF

The script will output:
1) Site level comparison:
    - a tsv file including number of unique and shared sites.
2) Sample level comparision:
    - The sample level comparison functionality will be added to the script soon.