THE MANGUL LAB AT USC
The mission of Mangul lab is to design, develop and apply novel and robust data-driven computational approaches that will accelerate the diffusion of genomics and biomedical data into translational research and education. We believe that important biological, translational and clinical discoveries are possible through developing better bioinformatics methods and by applying those methods across the largest most complex and heterogeneous datasets. We are committed to converting the biomedical data deluge into systematized knowledge to help us understand the molecular basis of disease and enable therapeutic discovery.
Bioinformatics algorithms are now crucial for processing high-throughput-omics data and deriving meaningful interpretations in most biomedical and life science research domains. Bioinformatics-related training and research mostly take place in nations with higher income economies and resource-rich institutions that offer adequate training and administrative support. Indeed, some aspects of science (for example, wet labs) require significant resources to establish and maintain. However, today’s availability of low-cost computing allows any individual with sufficient training and cloud access to develop novel computational methods and perform in silico analyses—key aspects of many modern scientific endeavors.
Quantifying the Microbiome
High-throughput RNA-sequencing (RNA-seq) technologies provide an unprecedented opportunity to explore the individual transcriptome. Unmapped reads are a large and often overlooked output of standard RNA-seq analyses. Here, we present Read Origin Protocol (ROP), a tool for discovering the source of all reads originating from complex RNA molecules. We apply ROP to samples across 2630 individuals from 54 diverse human tissues. Our approach can account for 99.9% of 1 trillion reads of various read length. Additionally, we use ROP to investigate the functional mechanisms underlying connections between the immune system, microbiome, and disease. ROP is freely available at https://github.com/smangul1/rop/wiki .
Producing Genomic Tools
The rapid advancement of genomics and sequencing technologies has led to an overwhelming amount and diversity of new analytical algorithms packaged as software tools . Such computational tools have helped life science and medical researchers analyze increasingly complex data, solve difficult biological problems, and lay groundwork essential for novel clinical translation. Indeed, all phases of sequencing data analysis rely on bioinformatics tools , from the initial sequencing of the human genome to modern analyses of high-throughput sequencing data.