Comments (1)
Hi @saralinker, sorry for the slow response - I was on medical leave last quarter.
In terms of a tutorial for training genomics models, I think this notebook by Ziga Avsec is a good place to start; it trains a very simple model with 1 convolutional layer, but hopefully it's enough to give you a grounding: https://colab.research.google.com/github/Avsecz/DL-genomics-exercise/blob/master/Simulated.ipynb. Note that colab notebooks currently default to tensorflow version 2, and if you want to force an earlier version of tensorflow you need to execute the command %tensorflow_version 1.x
at the beginning of the notebook.
When you say your "weights are not correct", can you be more specific? In case you were running into an hdf5 error with reading the model weights, this was because the model weights were saved with an earlier version of the h5py library; you have to use h5py < 3.0.0 for reading the weights to work. I have updated the example colab notebook in the deeplift repo to reflect this: https://colab.research.google.com/github/kundajelab/deeplift/blob/master/examples/genomics/genomics_simulation.ipynb
In terms of interpretation, if you have trouble using this particular deeplift repository, then you might have more luck using the DeepSHAP implementation (DeepSHAP is an extension of deeplift, and the implementation is done in a more flexible way such that it works with a wider array of models). I have an example notebook using DeepSHAP here: https://colab.research.google.com/github/AvantiShri/shap/blob/5fdad0651176cdbf1acd6c697604a71529695211/notebooks/deep_explainer/Tensorflow%20DeepExplainer%20Genomics%20Example%20With%20Hypothetical%20Importance%20Scores.ipynb. I also have detailed slides from a lab meeting I gave on using DeepSHAP, in case those are helpful: https://docs.google.com/presentation/d/1JCLMTW7ppA3Oaz9YA2ldDgx8ItW9XHASXM1B3regxPw/edit?usp=sharing
from deeplift.
Related Issues (20)
- categorial variables HOT 2
- adjustment for softmax HOT 2
- KeyError: 'batch_input_shape' while using deeplift on keras
- KeyError: 'zeropadding2d' HOT 1
- Question regarding version 0.6.11.0 that is not anymore available. HOT 2
- bpnet/deepexplain issue
- DeepLIFT with the RevealCancel rule
- Deeplift with Cifar10 HOT 3
- how do I download deeplift version of 0.5.1-theano HOT 2
- How to use deeplift for regression HOT 1
- Does DeepLIFT support to use deep residual? I have a model with deep residual, and want to use DeepLIFT to interpret it too. Thanks! HOT 1
- can deeplift explain text classification? HOT 2
- Sequential model input layer convert HOT 3
- Aggregating contribution scores
- keras2_mnist_cnn_allconv.h5 of MNIST demo can't be decoded
- Dimension error in a multi-input, multi-channel CNN HOT 2
- AttributeError: module 'tensorflow' has no attribute 'placeholder'
- deepLIFT scores always central to genomic sequence
- Dinucleotide shuffling does not shuffle
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from deeplift.