Mango_EDA

Mango_EDA enables scalable processing and interactive exploratory analysis of large-scale sequencing datasets to support quality control and multi-sample genomic investigations.

Key Features:

• Apache Spark-based distribution: Uses Apache Spark to distribute data processing across multi-node compute clusters for scalable computation on sequencing data.
• Distributed multi-node processing: Executes analysis across compute clusters to handle terabyte-scale and larger genomic datasets.
• Interactive exploration capability: Supports interactive exploration of extensive sequencing datasets to facilitate exploratory data analysis at scale.
• Large-data management: Manages and analyses terabytes of sequencing data, including demonstrated processing of 10 terabytes of samples.
• Quality control analyses: Performs quality control analyses on high-coverage sequencing samples, as applied to real-world datasets.
• Demonstrated dataset: Applied to 10 terabytes of high-coverage sequencing samples from the Simons Genome Diversity Project.

Scientific Applications:

• Quality control of sequencing data: Enables QC analyses on terabyte-scale, high-coverage sequencing datasets.
• Exploratory data analysis: Facilitates interactive exploratory analyses of multi-sample genomic datasets at scale.
• Scalable multi-sample investigations: Supports analyses that compare or aggregate across many samples in large cohorts or projects.

Methodology:

Leverages Apache Spark to distribute data processing across multi-node compute clusters to process and enable interactive exploration of large sequencing datasets; applied to quality control on 10 terabytes of high-coverage sequencing samples from the Simons Genome Diversity Project.