localScore-package: localScore: Package for Sequence Analysis by Local Score

In localScore: Package for Sequence Analysis by Local Score

localScore: Package for Sequence Analysis by Local Score

Description

Provides functionalities for:

• calculating the local score

• calculating statistical relevance (p-value) to find a local Score in a sequence of given distribution

Given a sequence of numerical score X_1,\dots,X_n, the local score is defined : H_n = \max_{1 \leq i \leq j \leq n} \sum_{l = i}^j X_l This package find the value local score and the associated sub-sequence, and also sub-optimal local scores and segments. The complexity is linear with n. It can be viewed as a generalization of a sliding window method, considering all windows size. In order to be pertinent, the expectation of the scores X_i should be negative. Most of the methods concerning statistical relevance implemented in this package only applied on integer scores.

Details

Please refer to the vignette of this package or the manual for details on how to use this package.

Author(s)

Maintainer: David Robelin [e-mail]

Authors:

• Sebastian Simon

• Chris Verschelden

• Charly Marty

• Sabine Mercier [e-mail]

• Sebastien Dejean [e-mail]

Other contributors:

• The authors of Eigen the library for the included version of Eigen [copyright holder]

References

• An Improved Approximation For Assessing The Statistical Significance of molecular Sequence Features, Mercier and al 2003

• Exact distribution for the local score of one i.i.d. random sequence, Sabine Mercier and JJ Daudin, 2001

• Limit Distributions of Maximal Segmental Score among Markov-Dependent Partial Sums, Karlin and Dembo 1992

• Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes, Karlin and al 1990

• Detection de courts segments inverses dans les genomes: methodes et applications, David Robelin 2005

• A Linear Time Algorithm for Finding All Maximal Scoring Subsequences, Constable and Bates 1985

localScore documentation built on April 3, 2025, 5:26 p.m.