hiReadsProcessor
hiReadsProcessor processes Linear Amplification-Mediated PCR (LM-PCR) sequencing data to demultiplex samples, trim adaptors, identify genomic products, perform quality control, and quantify product abundance for genomics and molecular biology analyses.
Key Features:
- Demultiplexing Automation: Automates demultiplexing using input files such as Excel or text documents containing parameters and sample metadata.
- Adaptor Trimming and Genomic Product Identification: Trims adaptors from reads and identifies genomic LM-PCR products for downstream analysis.
- Quality Control (QC) Processing: Performs quality-control processing of processed genomic products to retain high-fidelity data.
- Abundance Quantification: Quantifies the abundance of identified genomic products from sequencing data.
- Sequencing Platform Compatibility: Integrates with data from various sequencing platforms for LM-PCR workflows.
- Bioconductor Interoperability: Interfaces with Bioconductor (R) for downstream bioinformatic and statistical analysis.
Scientific Applications:
- LM-PCR product processing and characterization: Preparation and characterization of LM-PCR-derived sequences for quantitative and qualitative analyses.
- Gene expression profiling: Quantification of product abundance to support gene expression studies.
- Mutation detection: Processing and QC of LM-PCR sequencing data to support detection of sequence variants.
- High-throughput sequencing preprocessing: Preprocessing LM-PCR sequencing data to generate inputs for downstream genomic analyses and statistical workflows.
Methodology:
Demultiplexing from Excel/text metadata files; adaptor trimming; identification of genomic LM-PCR products; quality-control processing; abundance quantification; interoperability with Bioconductor (R) for downstream analyses.
Topics
Collections
Details
- License:
- GPL-3.0
- Tool Type:
- command-line tool, library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 1/17/2017
- Last Updated:
- 11/25/2024
Operations
Data Inputs & Outputs
Data handling
Publications
Huber W, Carey VJ, Gentleman R, Anders S, Carlson M, Carvalho BS, Bravo HC, Davis S, Gatto L, Girke T, Gottardo R, Hahne F, Hansen KD, Irizarry RA, Lawrence M, Love MI, MacDonald J, Obenchain V, Oleś AK, Pagès H, Reyes A, Shannon P, Smyth GK, Tenenbaum D, Waldron L, Morgan M. Orchestrating high-throughput genomic analysis with Bioconductor. Nature Methods. 2015;12(2):115-121. doi:10.1038/nmeth.3252. PMID:25633503. PMCID:PMC4509590.