Skip to main content

A statistical tool to quantify isoform-specific expression using long-read RNA-seq

Project description

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.

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

liqa-1.1.13.tar.gz (12.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

liqa-1.1.13-py3-none-any.whl (34.0 kB view details)

Uploaded Python 3

File details

Details for the file liqa-1.1.13.tar.gz.

File metadata

  • Download URL: liqa-1.1.13.tar.gz
  • Upload date:
  • Size: 12.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.3

File hashes

Hashes for liqa-1.1.13.tar.gz
Algorithm Hash digest
SHA256 c7d4e166c2751a49d4e93b9754f4e55d984750b1de2d7cadf91fd4a5cbb6519d
MD5 3d679f304da3a863bf264b0026cf2ce7
BLAKE2b-256 4b76338f983aaa8e02b66483b6ee57a8e246c4525e2c35d94374174133149754

See more details on using hashes here.

File details

Details for the file liqa-1.1.13-py3-none-any.whl.

File metadata

  • Download URL: liqa-1.1.13-py3-none-any.whl
  • Upload date:
  • Size: 34.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.3.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.3

File hashes

Hashes for liqa-1.1.13-py3-none-any.whl
Algorithm Hash digest
SHA256 819b8ca766d1345be95d123057166e53edbdea38f1b665adec27a6d35c0805a5
MD5 9706ce6414872da9369174840e499477
BLAKE2b-256 bd26c4909121690147246b5567a5265ca23975e737f8244646449cd81652a0eb

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page