Special section: Statistical methods for next-generation gene sequencing data

TL;DR

This collection of articles presents tailored statistical methods for various gene sequencing data types, emphasizing integrated analysis of multiple data types to uncover biological insights that are difficult to detect otherwise.

Contribution

The papers introduce novel statistical approaches for analyzing diverse gene sequencing data types and their integration to enhance biological discovery.

Findings

Methods enable analysis of multiple data types simultaneously

New insights into gene sequencing data achieved through statistical integration

Approaches tailored to specific data types improve biological interpretation

Abstract

This issue includes six articles that develop and apply statistical methods for the analysis of gene sequencing data of different types. The methods are tailored to the different data types and, in each case, lead to biological insights not readily identified without the use of statistical methods. A common feature in all articles is the development of methods for analyzing simultaneously data of different types (e.g., genotype, phenotype, pedigree, etc.); that is, using data of one type to inform the analysis of data from another type.