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Computational synthetic biology: Predicting DNA edits for bioengineering

Home Page: http://20n.com

License: GNU General Public License v3.0

Scala 16.91% Java 78.35% Arduino 0.07% Shell 0.58% Python 2.41% R 1.30% FreeMarker 0.19% PLpgSQL 0.03% JavaScript 0.14% HTML 0.02% CSS 0.01%
synthetic-biology deep-learning bioengineering data-mining computational-synthetic-biology fermentation acetaminophen biochemistry reaction-operators enzyme-function

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act's Issues

file ending of '01' ??

Thanks for publishing this code! It looks very interesting and I wanted to try it.

I installed TensorFlow, python, and all the other dependencies with conda on MacOSX, cloned the repo, and was able to run python bucketed_differential_deep.py -h successfully, so I assume TensorFlow, keras etc. is functioning.

I moved the faahKO data, which is in netCDF format, to the a lcms_datadirectory I made in the act/reachables/src/main/python/DeepLearningLcmsPeak directory, and then tried this:

python bucketed_differential_deep.py --control lcms_data/KO/ko15.CDF --experimental lcms_data/WT/wt15.CDF  --outputDirectory faahko_out/ --lcmsDirectory lcms_data

The result is something I don't completely understand about the proper ending of file names?

(20n) curt@DN2lk5k46:~/20n/act/reachables/src/main/python/DeepLearningLcmsPeak$ python bucketed_differential_deep.py --control lcms_data/KO/ko15.CDF --experimental lcms_data/WT/wt15.CDF  --outputDirectory faahko_out/ --lcmsDirectory lcms_data
Using TensorFlow backend.
/Users/curt/20n/act/reachables/src/main/python/DeepLearningLcmsPeak/bucketed_peaks/modules/lcms_autoencoder.py:174: UserWarning: Update your `Dense` call to the Keras 2 API: `Dense(units=70, activation="linear")`
  encoded = Dense(output_dim=first_layer_dim, activation="linear")(input_layer)
/Users/curt/20n/act/reachables/src/main/python/DeepLearningLcmsPeak/bucketed_peaks/modules/lcms_autoencoder.py:175: UserWarning: Update your `Dense` call to the Keras 2 API: `Dense(units=30, activation="linear")`
  encoded = Dense(output_dim=second_layer_dim, activation="linear")(encoded)
/Users/curt/20n/act/reachables/src/main/python/DeepLearningLcmsPeak/bucketed_peaks/modules/lcms_autoencoder.py:178: UserWarning: Update your `Dense` call to the Keras 2 API: `Dense(units=10, activation="linear")`
  encoded = Dense(output_dim=self.encoding_size, activation="linear")(encoded)
/Users/curt/20n/act/reachables/src/main/python/DeepLearningLcmsPeak/bucketed_peaks/modules/lcms_autoencoder.py:188: UserWarning: Update your `Model` call to the Keras 2 API: `Model(outputs=Tensor("de..., inputs=Tensor("in...)`
  encoder = Model(input=input_layer, output=encoded)
Traceback (most recent call last):
  File "bucketed_differential_deep.py", line 150, in <module>
    row_matrix1 = merge_lcms_replicates(experimental_samples)
  File "bucketed_differential_deep.py", line 110, in merge_lcms_replicates
    scans = [autoencoder.process_lcms_scan(lcms_directory, scan) for scan in samples]
  File "/Users/curt/20n/act/reachables/src/main/python/DeepLearningLcmsPeak/bucketed_peaks/modules/lcms_autoencoder.py", line 123, in process_lcms_scan
    "was {}".format(scan_file_name)
AssertionError: This module only processes MS1 data which should always have a file ending of '01'.  Your supplied file was lcms_data/WT/wt15.CDF
(20n) curt@DN2lk5k46:~/20n/act/reachables/src/main/python/DeepLearningLcmsPeak$

What is the right format for the filenames I want to supply to this code?

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