Confidence intervals for Markov chain transition probabilities based on next generation sequencing reads data.

ABSTRACT:

Background

Markov chains (MC) have been widely used to model molecular sequences. The estimations of MC transition matrix and confidence intervals of the transition probabilities from long sequence data have been intensively studied in the past decades. In next generation sequencing (NGS), a large amount of short reads are generated. These short reads can overlap and some regions of the genome may not be sequenced resulting in a new type of data. Based on NGS data, the transition probabilities of MC can be estimated by moment estimators. However, the classical asymptotic distribution theory for MC transition probability estimators based on long sequences is no longer valid.

Methods

In this study, we present the asymptotic distributions of several statistics related to MC bas

SUBMITTER: Wan L 

PROVIDER: S-EPMC8277151 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature