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 incorporates base-pair quality score and isoform-specific read length information to assign different weights across reads instead of summarizing isoform-specific read counts directly. Moreover, LIQA can detect DAS events between conditions using isoform usage estimates.
Computational pipeline of LIQA
Inputs of LIQA
The input of LIQA is long-read RNA-seq read data in BAM format together with a refrence isoform annotation file.
Installation
Please refer to Installation for how to install LIQA.
Usage
Please refere to Usage for how to use LIQA.
Examples of isoform analysis using LIQA.
Please refer to Demo and Examples for examples of how to use LIQA.
Contact
If you have any questions/issues/bugs, please post them on GitHub. They would also be helpful to other users.
Citation
Yu Hu, Li Fang, Xuelian Chen, Jiang F. Zhong, Mingyao Li, Kai Wang. LIQA: Long-read Isoform Quantification and Analysis. 2020. bioRxiv doi: https://doi.org/10.1101/2020.09.09.289793
1 maintainer
Metadata
1 maintainer
Release files for liqa 1.3.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| liqa-1.3.4.tar.gz | 14.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| liqa-1.3.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 46.3 kB
Release files / liqa-1.3.4.tar.gz
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| Size | 14.1 kB |
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| Tags | Python 3 |
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