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.