Anaquin

Anaquin provides quantitative analysis, modeling, and visualization of synthetic "sequin" RNA spike-in controls to standardize, calibrate, and correct biases in RNA sequencing (RNA-seq) experiments.

Key Features:

• Synthetic Sequencing Spike-In Controls (Sequins): Synthetic RNA standards that mimic full-length spliced mRNA isoforms and map to loci on an artificial in silico chromosome with no homology to natural reference genomes.
• Quantitative and Qualitative Reference: Sequins span a range of concentrations to emulate alternative splicing events and differential gene expression, providing quantitative and qualitative benchmarks and scaling factors for normalization.
• Comprehensive Transcriptome Analysis: Supports assembly of spliced isoforms and quantification of expressed genes to profile the transcriptome and identify limits of reliable transcript assembly and quantification in human RNA samples.
• Cancer Diagnosis Applications: Includes a specialized set of sequins representing fusion genes created by rearrangements on the in silico chromosome to aid detection of gene fusions.
• Normalization and Bias Correction: Measures and corrects technical biases in RNA-seq experiments and derives scaling factors to enable consistent normalization across samples.
• Open-source Analysis Library: Provides an open-source library for quantitative analysis, modeling, bias correction, transcript quantification, and visualization of sequin-containing RNA-seq datasets.

Scientific Applications:

• Transcriptome Profiling: Enabling assembly and quantification of spliced isoforms to generate a global profile of the transcriptome.
• Normalization of RNA-seq Data: Providing scaling factors and benchmarks to correct technical variation and allow accurate comparisons across samples.
• Cancer Research: Facilitating detection and evaluation of fusion genes using sequin-derived fusion constructs as references.
• Experimental Validation: Serving as qualitative and quantitative reference standards to validate RNA-seq experimental results and performance.

Methodology:

Design of artificial sequin sequences that align to gene loci on an in silico chromosome; incorporation of sequins into RNA-seq workflows for benchmarking; analysis using the anaquin open-source library focusing on bias correction, transcript quantification, and visualization.