Commit d7f1d10b authored by Ryan Gutenkunst's avatar Ryan Gutenkunst
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Add citations and GPU info to manual

parent 8ee92168
......@@ -15,19 +15,19 @@ As we do our own research, dadi is constantly improving. Our philosophy is to in
### Citations
If you find dadi useful in your research, please cite:
RN Gutenkunst, RD Hernandez, SH Williamson, CD Bustamante "Inferring the joint demographic history of multiple populations from multidimensional SNP data" PLoS Genetics 5:e1000695 (2009)
[RN Gutenkunst, RD Hernandez, SH Williamson, CD Bustamante "Inferring the joint demographic history of multiple populations from multidimensional SNP data" PLoS Genetics 5:e1000695 (2009)](http://doi.org/10.1371/journal.pgen.1000695).
If you find the Godambe Information Matrix methods useful, please cite:
AJ Coffman, P Hsieh, S Gravel, RN Gutenkunst "Computationally efficient composite likelihood statistics for demographic inference" Molecular Biology and Evolution 33:591 (2016)
[AJ Coffman, P Hsieh, S Gravel, RN Gutenkunst "Computationally efficient composite likelihood statistics for demographic inference" Molecular Biology and Evolution 33:591 (2016)](http://doi.org/10.1093/molbev/msv255).
If you find the DFE inference methods useful, please cite:
BY Kim, CD Huber, KE Lohmueller "Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples" Genetics 206:345 (2017)
[BY Kim, CD Huber, KE Lohmueller "Inference of the Distribution of Selection Coefficients for New Nonsynonymous Mutations Using Large Samples" Genetics 206:345 (2017)](https://doi.org/10.1534/genetics.116.197145).
If you find the triallelic methods useful, please cite:
AP Ragsdale, AJ Coffman, P Hsieh, TJ Struck, RN Gutenkunst "Triallelic population genomics for inferring correlated fitness effects of same site nonsynonymous mutations" Genetics 203:513 (2016)
[AP Ragsdale, AJ Coffman, P Hsieh, TJ Struck, RN Gutenkunst "Triallelic population genomics for inferring correlated fitness effects of same site nonsynonymous mutations" Genetics 203:513 (2016)](http://doi.org/10.1534/genetics.115.184812).
If you find the two-locus methods useful, please cite:
AP Ragsdale, RN Gutenkunst "Inferring demographic history using two-locus statistics" Genetics 206:1037 (2017)
[AP Ragsdale, RN Gutenkunst "Inferring demographic history using two-locus statistics" Genetics 206:1037 (2017)](http://doi.org/10.1534/genetics.117.201251).
### Suggested workflow
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......@@ -5,13 +5,13 @@ dadi can be sped up substantially by running on a CUDA-enabled Nvidia GPU.
### Installation
To enable GPU computing, you will first need to install the [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads).
After install the Toolkit, you will then need to install PyCUDA and scikit-cuda.
After installing the Toolkit, you will then need to install [PyCUDA](https://documen.tician.de/pycuda/) and [scikit-cuda](https://scikit-cuda.readthedocs.io/).
Both of these can be installed from the Python Package Index using pip, `python3 -m pip install pycuda` and `python3 -m pip install scikit-cuda`.
### Usage
GPU computing is implemented for integration of population spectra, `phi`.
To enable GPU computing, run the command `dadi.cuda_enabled(True)` in your script (generally near the top).
To enable GPU computing, run the command `dadi.cuda_enabled(True)` in your script, before you carry out any model simulations or optimizations.
To disable GPU computing, run the command `dadi.cuda_enabled(False)` in your script.
### RAM limitations
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