Modeling and Predicting Differential Alternative Splicing Events and Applications Thereof
OwnerPeng Yu, Chad A. Shawinventors
Life of this patent
Estimating the term…
Abstract
The present disclosure includes a method for predicting differential alternative splicing events from ribonucleic acid (RNA) sequencing data that includes receiving RNA sequence reads for two or more samples; generating directed acyclic graphs from the RNA sequence reads, wherein each directed acyclic graph represents at least a portion of a gene model; extracting count data from the directed acyclic graphs; and generating differential alternative splicing event information from the count data using a Dirichlet multinomial (DMN) regression.
Claims10
A method for predicting differential alternative splicing events from RNA comprising:
- a) sequencing at least one said RNA sample to produce RNA sequence data reads per sample;
- b) generating one or more directed acyclic graphs from the RNA sequence reads, wherein each directed acyclic graph represents at least a portion of a gene model;
- c) extracting count data from the directed acyclic graphs;
- and
- d) generating differential alternative splicing information from the count data using a Dirichlet multinomial (DMN) regression.
A method for predicting differential alternative splicing events from ribonucleic acid (RNA) sequence data, comprising:
- a) sequencing at least one said RNA sample to produce RNA sequence data reads per sample;
- b) generating one or more directed acyclic graphs from the RNA sequence reads, wherein each directed acyclic graph represents at least a portion of a gene model;
- c) extracting count data from the directed acyclic graphs;
- d) generating differential alternative splicing information from the count data using a Dirichlet multinomial (DMN) regression;
- and
- e) using said alternative splicing information to create antisense RNA sequence which correspond to said alternative splicing information.
A method for treating a subject with a disease comprising:
- a) sequencing at least one said RNA sample from at least one diseased tissue and at least one control sample to produce RNA sequence data reads per sample;
- b) generating one or more directed acyclic graphs from the RNA sequence reads, wherein each directed acyclic graph represents at least a portion of a gene model;
- c) extracting count data from the directed acyclic graphs;
- d) generating differential alternative splicing information from the count data using a Dirichlet multinomial (DMN) regression;
- e) using said alternative splicing information to create antisense RNA sequences which correspond to said alterative splicing information relevant to said diseased tissue sample;
- and
- f) treating said subject with said antisense RNA sequence corresponding to said diseased tissue sample RNA sequence variants so as to alieviate at least one symptom of said disease.
A method for predicting differential alternative splicing events from ribonucleic acid (RNA) sequence data, comprising:
- Receiving RNA sequence reads for two or more samples;
- Generating one or more directed acyclic graphs from the RNA sequence reads, wherein each directed acyclic graph represents at least a portion of a gene model;
- Extracting count data from the directed acyclic graphs;
- and Generating differential alternative splicing information from the count data using a Dirichlet multinomial (DMN) regression.
Dependencies are inferred from the claim text.