Je, a versatile suite to handle multiplexed NGS libraries with unique molecular identifiers

Area of Science:

• Genomics
• Bioinformatics
• Molecular Biology

Background:

• Next-generation sequencing yields have surged, necessitating sample multiplexing.
• Barcodes identify samples, while Unique Molecular Identifiers (UMIs) distinguish PCR duplicates from true transcript abundance, crucial for scRNA-seq.
• Complex barcoding strategies, including paired-end and composite barcodes, are increasingly common in sequencing libraries.

Purpose of the Study:

• To address the limitations of existing tools in handling complex barcoding configurations.
• To introduce Je, a software suite designed for advanced barcode extraction and UMI identification.
• To improve the accuracy of read duplicate filtering by incorporating UMI information.

Main Methods:

• Development of Je, a Java-based software suite utilizing the Picard API.
• Implementation of algorithms to extract UMIs from various complex barcoding strategies.
• Application of Je to analyze publicly available single-cell RNA sequencing (scRNA-seq) and iCLIP data.

Main Results:

• Je successfully accommodates complex barcoding strategies, including those with UMIs.
• The software effectively extracts UMIs and filters read duplicates based on UMI information.
• Analysis using Je led to an increase in unique reads by up to 36% compared to analyses ignoring UMIs.

Conclusions:

• Je provides a robust solution for analyzing data with complex barcoding and UMIs.
• The tool enhances data accuracy by correctly identifying and utilizing UMIs.
• Je is freely available and integrates with platforms like Galaxy, facilitating its adoption in research.