BP4RNAseq

BP4RNAseq processes raw RNA sequencing (RNA-seq) reads to automate and standardize gene- and transcript-level quantification using integrated alignment-based and alignment-free workflows.


Key Features:

  • Automated Workflow: Automates end-to-end processing of raw RNA-seq reads through a standardized pipeline.
  • Minimal Input Requirements: Operates from two inputs: taxa name and NCBI accession codes for RNA-seq samples.
  • Integration of Quantification Workflows: Integrates alignment-based and alignment-free quantification workflows to enhance sensitivity and accuracy.
  • Comprehensive Output: Produces six formatted gene expression quantifications at both gene and transcript levels.
  • Versatility in Application: Processes raw reads from both public (NCBI) and newly sequenced datasets and supports bulk and single-cell RNA-seq analyses.
  • Reproducibility: Provides standardized automated processing to promote reproducible RNA-seq quantification.

Scientific Applications:

  • Gene expression studies: Generates gene- and transcript-level expression quantifications for gene expression analysis.
  • Comparative genomics/transcriptomics: Enables comparison of expression profiles across taxa or conditions using NCBI and newly generated datasets.
  • Retrospective bulk RNA-seq analysis: Processes public NCBI RNA-seq datasets for retrospective bulk transcriptomic studies.
  • Single-cell RNA-seq analysis: Supports gene- and transcript-level quantification for single-cell RNA-seq datasets.

Methodology:

Automated pipeline processes raw RNA-seq reads from public (NCBI) and newly sequenced datasets, accepts taxa name and NCBI accession codes as inputs, and applies integrated alignment-based and alignment-free quantification workflows to produce six formatted gene- and transcript-level expression quantifications.

Topics

Details

Tool Type:
library, workflow
Programming Languages:
R, Python
Added:
1/18/2021
Last Updated:
2/6/2021

Operations

Publications

Sun S, Xu L, Zou Q, Wang G. BP4RNAseq: a babysitter package for retrospective and newly generated RNA-seq data analyses using both alignment-based and alignment-free quantification method. Bioinformatics. 2020;37(9):1319-1321. doi:10.1093/bioinformatics/btaa832. PMID:32976573.

PMID: 32976573
Funding: - National Key R&D Program of China: 2018YFC0910405 - National Natural Science Foundation of China: 61771165, 61922020, 91935302