Add H5 GenomicFeatures support for more flexible target datatypes #200
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
…taset batches function
…an be generalized from the methylation specific code
…ts_path in both sampler classes
…x-indexed BED file
…made and saved to the output dir
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
This PR adds support for a new target type. Previously Selene only supports sampling of binary targets, but GenomicFeaturesH5 is a class supporting the querying of genomic coordinate rows in a tabix-indexed BED file and an HDF5 matrix of corresponding labels for training. Changes in other files are used to support this new functionality, for example compression/decompression of sequence one-hot encoding only as opposed to both sequences & targets which was the default implementation, support of Spearman's and Pearson's correlation computation in PerformanceMetrics, and the like.