GMD: measuring the distance between histograms with applications on high-throughput sequencing reads

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Standard

GMD : measuring the distance between histograms with applications on high-throughput sequencing reads. / Zhao, Xiaobei; Sandelin, Albin Gustav.

In: Bioinformatics, Vol. 28, No. 8, 2012, p. 1164-1165.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Zhao, X & Sandelin, AG 2012, 'GMD: measuring the distance between histograms with applications on high-throughput sequencing reads', Bioinformatics, vol. 28, no. 8, pp. 1164-1165. https://doi.org/10.1093/bioinformatics/bts087

APA

Zhao, X., & Sandelin, A. G. (2012). GMD: measuring the distance between histograms with applications on high-throughput sequencing reads. Bioinformatics, 28(8), 1164-1165. https://doi.org/10.1093/bioinformatics/bts087

Vancouver

Zhao X, Sandelin AG. GMD: measuring the distance between histograms with applications on high-throughput sequencing reads. Bioinformatics. 2012;28(8):1164-1165. https://doi.org/10.1093/bioinformatics/bts087

Author

Zhao, Xiaobei ; Sandelin, Albin Gustav. / GMD : measuring the distance between histograms with applications on high-throughput sequencing reads. In: Bioinformatics. 2012 ; Vol. 28, No. 8. pp. 1164-1165.

Bibtex

@article{c3cc97d0b44641779ae5a993b5f9b152,
title = "GMD: measuring the distance between histograms with applications on high-throughput sequencing reads",
abstract = "GMD (generalized minimum distance of distributions) is an R package to assess the similarity between spatial distributions of read-based sequencing data such as ChIP-seq and RNA-seq. GMD calculates the optimal distance between pairs of normalized signal distributions, optionally sliding one distribution over the other to 'align' the distributions. GMD also provides graphical and downstream clustering tools.",
author = "Xiaobei Zhao and Sandelin, {Albin Gustav}",
year = "2012",
doi = "10.1093/bioinformatics/bts087",
language = "English",
volume = "28",
pages = "1164--1165",
journal = "Computer Applications in the Biosciences",
issn = "1471-2105",
publisher = "Oxford University Press",
number = "8",

}

RIS

TY - JOUR

T1 - GMD

T2 - measuring the distance between histograms with applications on high-throughput sequencing reads

AU - Zhao, Xiaobei

AU - Sandelin, Albin Gustav

PY - 2012

Y1 - 2012

N2 - GMD (generalized minimum distance of distributions) is an R package to assess the similarity between spatial distributions of read-based sequencing data such as ChIP-seq and RNA-seq. GMD calculates the optimal distance between pairs of normalized signal distributions, optionally sliding one distribution over the other to 'align' the distributions. GMD also provides graphical and downstream clustering tools.

AB - GMD (generalized minimum distance of distributions) is an R package to assess the similarity between spatial distributions of read-based sequencing data such as ChIP-seq and RNA-seq. GMD calculates the optimal distance between pairs of normalized signal distributions, optionally sliding one distribution over the other to 'align' the distributions. GMD also provides graphical and downstream clustering tools.

U2 - 10.1093/bioinformatics/bts087

DO - 10.1093/bioinformatics/bts087

M3 - Journal article

C2 - 22345619

VL - 28

SP - 1164

EP - 1165

JO - Computer Applications in the Biosciences

JF - Computer Applications in the Biosciences

SN - 1471-2105

IS - 8

ER -

ID: 37969455