https://github.com/kussell-lab/mcorr
Tip revision: 4816f2a300d7bbae1084b1940959ea35973104e1 authored by Mingzhi Lin on 23 August 2017, 14:12:59 UTC
add nucl_cov_test
add nucl_cov_test
Tip revision: 4816f2a
README.md
# mcorr
Infer recombination rates from bacterial sequence data using correlated mutations.
## Requirments
* [Git](https://git-scm.com/);
* [Go](https://golang.org/);
* Python with numpy, lmfit, tqdm and matplotlib packages.
## Installation
```sh
go get -u github.com/mingzhi/mcorr/cmd/mcorr-xmfa
go get -u github.com/mingzhi/mcorr/cmd/mcorr-bam
```
## Usage
The inference requires two steps:
1. calculate mutation correlation using `mcorr-xmfa` from gene alignments or `mcorr-bam` from read alignments:
```sh
mcorr-xmfa <input XMFA file)> <output CSV file>
```
or
```sh
mcorr-bam <GFF3 file> <input BAM file> <output (CSV file)>
```
**Note**: the XMFA files should contain only *coding* sequences.
The description of XMFA file can be found [here](http://darlinglab.org/mauve/user-guide/files.html).
2. fit the correlation results using `FitP2.py`:
```sh
python $GOPATH/src/github.com/mingzhi/mcorr/cmd/fitting/FitP2.py <input (mcorr output file)> <output prefix>
```
The resulted files:
* `<output_prefix>_best_fit.svg` -- the correlation profile, fitting, and residual plots;
* `<output_prefix>_fit_results.csv` -- table of the best-fitted parameters.
Example data can be found [here](https://github.com/mingzhi/mcorr_examples).