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- GitHub - WGLab LIQA: Long-read Isoform Quantification and Analysis
LIQA (Long-read Isoform Quantification and Analysis) is an Expectation-Maximization based statistical method to quantify isoform expression and detect differential alternative splicing (DAS) events using long-read RNA-seq data
- LIQA: long-read isoform quantification and analysis
We present LIQA to quantify isoform expression and detect differential alternative splicing (DAS) events using long-read direct mRNA sequencing or cDNA sequencing data
- liqa · PyPI
LIQA (Long-read Isoform Quantification and Analysis) is an Expectation-Maximization based statistical method to quantify isoform expression and detect differential alternative splicing (DAS) events using long-read RNA-seq data
- LIQA™
Access guides, product docs, API reference, FAQs and more
- LIQA: long-read isoform quantification and analysis - PMC
LIQA is a robust and effective computational tool to estimate isoform-specific gene expression from long-read RNA-seq data With the increasing adoption of long-read RNA-seq in biomedical research, we believe LIQA will be well-suited for various transcriptomics studies and offer additional insights beyond gene expression analysis in the future
- LIQA: Long-read Isoform Quantification and Analysis - bioRxiv
LIQA is a robust and effective computational tool to estimate isoform-specific gene expression from long-read RNA-seq data With the increasing adoption of long-read RNA-seq in biomedical research, we believe LIQA will be well- suited for various transcriptomics studies and offer additional insights beyond gene expression analysis in the future
- GitHub - WGLab LIQA2
LIQA2 is a computational tool for detecting and quantifying isoform expression (including novel isoforms) from long read sequencing The tool uses a meta-regression model to quantify differential alternative splicing and incorporates a targeted approach to correct for 3' and 5' biases
- (PDF) LIQA: long-read isoform quantification and analysis
We present LIQA to quantify isoform expression and detect differential alternative splicing (DAS) events using long-read direct mRNA sequencing or cDNA sequencing data
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