ArchTEx: Accurate extraction and visualization of next-generation sequence data

William K.M. Lai; Jonathan E. Bard; Michael J. Buck

doi:10.1093/bioinformatics/bts063

ArchTEx: Accurate extraction and visualization of next-generation sequence data

William K.M. Lai, Jonathan E. Bard, Michael J. Buck

Biochemistry & Molecular Biology

Research output: Contribution to journal › Article › peer-review

14 Scopus citations

Abstract

Motivation: The extension of mapped sequence tags is a common step in the analysis of single-end next-generation sequencing (NGS) data from protein localization and chromatin studies. The optimal extension can vary depending on experimental and technical conditions. Improper extension of sequence tags can obscure or mislead the interpretation of NGS results. We present an algorithm, ArchTEx (Architectural Tag Extender), which identifies the optimal extension of sequence tags based on the maximum correlation between forward and reverse tags and extracts and visualizes sites of interest using the predicted extension.

Original language	English (US)
Article number	bts063
Pages (from-to)	1021-1023
Number of pages	3
Journal	Bioinformatics
Volume	28
Issue number	7
DOIs	https://doi.org/10.1093/bioinformatics/bts063
State	Published - Apr 2012

All Science Journal Classification (ASJC) codes

Statistics and Probability
Biochemistry
Molecular Biology
Computer Science Applications
Computational Theory and Mathematics
Computational Mathematics

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10.1093/bioinformatics/bts063

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abstract = "Motivation: The extension of mapped sequence tags is a common step in the analysis of single-end next-generation sequencing (NGS) data from protein localization and chromatin studies. The optimal extension can vary depending on experimental and technical conditions. Improper extension of sequence tags can obscure or mislead the interpretation of NGS results. We present an algorithm, ArchTEx (Architectural Tag Extender), which identifies the optimal extension of sequence tags based on the maximum correlation between forward and reverse tags and extracts and visualizes sites of interest using the predicted extension.",

author = "Lai, {William K.M.} and Bard, {Jonathan E.} and Buck, {Michael J.}",

note = "Funding Information: Funding: National Science Foundation (grant IIS1016929 to M.J.B.)",

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AU - Bard, Jonathan E.

AU - Buck, Michael J.

N1 - Funding Information: Funding: National Science Foundation (grant IIS1016929 to M.J.B.)

PY - 2012/4

Y1 - 2012/4

N2 - Motivation: The extension of mapped sequence tags is a common step in the analysis of single-end next-generation sequencing (NGS) data from protein localization and chromatin studies. The optimal extension can vary depending on experimental and technical conditions. Improper extension of sequence tags can obscure or mislead the interpretation of NGS results. We present an algorithm, ArchTEx (Architectural Tag Extender), which identifies the optimal extension of sequence tags based on the maximum correlation between forward and reverse tags and extracts and visualizes sites of interest using the predicted extension.

AB - Motivation: The extension of mapped sequence tags is a common step in the analysis of single-end next-generation sequencing (NGS) data from protein localization and chromatin studies. The optimal extension can vary depending on experimental and technical conditions. Improper extension of sequence tags can obscure or mislead the interpretation of NGS results. We present an algorithm, ArchTEx (Architectural Tag Extender), which identifies the optimal extension of sequence tags based on the maximum correlation between forward and reverse tags and extracts and visualizes sites of interest using the predicted extension.

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ArchTEx: Accurate extraction and visualization of next-generation sequence data

Abstract

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