TagDust

TagDust identifies and filters artifactual sequences generated during library preparation in high-throughput sequencing to improve the accuracy of downstream genomic analyses.

Key Features:

• Artifact Identification: Compares reads to known sequences used in library preparation and detects artifacts explained by combinations or partial matches to those reference sequences.
• User-Defined False Discovery Rate (FDR): Applies a user-specified FDR cutoff to control the stringency of artifact calling and balance sensitivity and specificity.
• Application on High-Throughput Platforms: Demonstrated compatibility with data generated on Illumina's Genome Analyzer.

Scientific Applications:

• Quality control: Identifies and removes artifactual reads to reduce background noise in sequencing libraries.
• Gene expression profiling and variant calling: Improves the accuracy of downstream analyses such as gene expression quantification and variant detection by removing artifactual sequences.
• Sequencing assay development: Aids assay validation by minimizing library-preparation–derived artifacts during development of novel sequencing assays.

Methodology:

Compares sequenced reads against a database of known library-preparation sequences, identifies reads explainable as combinations or partial matches to those references, flags them as potential artifacts, and applies a user-defined FDR cutoff to set calling stringency.