qrqc

qrqc analyzes high-throughput sequencing reads to produce statistical summaries and diagnostics for quality control of genomic sequencing data.

Key Features:

• Statistical Analysis: Scans sequencing reads to compute base frequencies, quality score distributions, and read length distributions for quality assessment.
• K-mer Analysis: Analyzes k-mers by position across reads to detect positional biases and patterns indicative of sequencing errors or biological variation.
• Frequent Sequence Identification: Identifies frequent sequences to aid detection of repetitive elements or potential contaminants.
• Graphical Output: Generates graphical outputs of the collected statistics for visual interpretation.
• HTML Quality Report: Produces an optional HTML report summarizing key quality-control metrics.
• S4 SequenceSummary Objects: Leverages S4 SequenceSummary objects to represent sequence summaries and enable customizable tests and downstream analyses.

Scientific Applications:

• Genomics and Molecular Biology QC: Performs quality control on high-throughput sequencing datasets used in genomics and molecular biology research.
• Contaminant and Repeat Detection: Detects frequent sequences and k-mer positional patterns to identify contaminants and repetitive elements.
• Bioconductor Workflow Integration: Supports development and integration of scientific software and workflows within the Bioconductor ecosystem.

Methodology:

Implemented in R and developed according to Bioconductor principles; leverages S4 SequenceSummary objects; subjected to formal initial review and continuous automated testing.