PyCogent: A toolkit for making sense from sequence

Rob Knight; Peter Maxwell; Amanda Birmingham; Jason Carnes; J. Gregory Caporaso; Brett C. Easton; Michael Eaton; Micah Hamady; Helen Lindsay; Zongzhi Liu; Catherine Lozupone; Daniel McDonald; Michael Robeson; Raymond Sammut; Sandra Smit; Matthew J. Wakefield; Jeremy Widmann; Shandy Wikman; Stephanie Wilson; Hua Ying; Gavin A. Huttley

doi:10.1186/gb-2007-8-8-r171

PyCogent: A toolkit for making sense from sequence

Rob Knight, Peter Maxwell, Amanda Birmingham, Jason Carnes, J. Gregory Caporaso, Brett C. Easton, Michael Eaton, Micah Hamady, Helen Lindsay, Zongzhi Liu, Catherine Lozupone, Daniel McDonald, Michael Robeson, Raymond Sammut, Sandra Smit, Matthew J. Wakefield, Jeremy Widmann, Shandy Wikman, Stephanie Wilson, Hua YingGavin A. Huttley

Electrical Engineering and Computer Science

Research output: Contribution to journal › Article

135 Scopus citations

Abstract

We have implemented in Python the COmparative GENomic Toolkit, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics. PyCogent includes connectors to remote databases, built-in generalized probabilistic techniques for working with biological sequences, and controllers for third-party applications. The toolkit takes advantage of parallel architectures and runs on a range of hardware and operating systems, and is available under the general public license from http://sourceforge.net/projects/pycogent.

Original language	English (US)
Article number	R171
Journal	Genome biology
Volume	8
Issue number	8
DOIs	https://doi.org/10.1186/gb-2007-8-8-r171
State	Published - Aug 21 2007

ASJC Scopus subject areas

Ecology, Evolution, Behavior and Systematics
Genetics
Cell Biology

Access to Document

10.1186/gb-2007-8-8-r171

Fingerprint Dive into the research topics of 'PyCogent: A toolkit for making sense from sequence'. Together they form a unique fingerprint.

Cite this

Knight, R., Maxwell, P., Birmingham, A., Carnes, J., Caporaso, J. G., Easton, B. C., Eaton, M., Hamady, M., Lindsay, H., Liu, Z., Lozupone, C., McDonald, D., Robeson, M., Sammut, R., Smit, S., Wakefield, M. J., Widmann, J., Wikman, S., Wilson, S., ... Huttley, G. A. (2007). PyCogent: A toolkit for making sense from sequence. Genome biology, 8(8), [R171]. https://doi.org/10.1186/gb-2007-8-8-r171

PyCogent : A toolkit for making sense from sequence. / Knight, Rob; Maxwell, Peter; Birmingham, Amanda; Carnes, Jason; Caporaso, J. Gregory; Easton, Brett C.; Eaton, Michael; Hamady, Micah; Lindsay, Helen; Liu, Zongzhi; Lozupone, Catherine; McDonald, Daniel; Robeson, Michael; Sammut, Raymond; Smit, Sandra; Wakefield, Matthew J.; Widmann, Jeremy; Wikman, Shandy; Wilson, Stephanie; Ying, Hua; Huttley, Gavin A.

In: Genome biology, Vol. 8, No. 8, R171, 21.08.2007.

Research output: Contribution to journal › Article

Knight, R, Maxwell, P, Birmingham, A, Carnes, J, Caporaso, JG, Easton, BC, Eaton, M, Hamady, M, Lindsay, H, Liu, Z, Lozupone, C, McDonald, D, Robeson, M, Sammut, R, Smit, S, Wakefield, MJ, Widmann, J, Wikman, S, Wilson, S, Ying, H & Huttley, GA 2007, 'PyCogent: A toolkit for making sense from sequence', Genome biology, vol. 8, no. 8, R171. https://doi.org/10.1186/gb-2007-8-8-r171

Knight, Rob ; Maxwell, Peter ; Birmingham, Amanda ; Carnes, Jason ; Caporaso, J. Gregory ; Easton, Brett C. ; Eaton, Michael ; Hamady, Micah ; Lindsay, Helen ; Liu, Zongzhi ; Lozupone, Catherine ; McDonald, Daniel ; Robeson, Michael ; Sammut, Raymond ; Smit, Sandra ; Wakefield, Matthew J. ; Widmann, Jeremy ; Wikman, Shandy ; Wilson, Stephanie ; Ying, Hua ; Huttley, Gavin A. / PyCogent : A toolkit for making sense from sequence. In: Genome biology. 2007 ; Vol. 8, No. 8.

@article{bab22850d7ac4c51bd71844ac609c593,

title = "PyCogent: A toolkit for making sense from sequence",

abstract = "We have implemented in Python the COmparative GENomic Toolkit, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics. PyCogent includes connectors to remote databases, built-in generalized probabilistic techniques for working with biological sequences, and controllers for third-party applications. The toolkit takes advantage of parallel architectures and runs on a range of hardware and operating systems, and is available under the general public license from http://sourceforge.net/projects/pycogent.",

author = "Rob Knight and Peter Maxwell and Amanda Birmingham and Jason Carnes and Caporaso, {J. Gregory} and Easton, {Brett C.} and Michael Eaton and Micah Hamady and Helen Lindsay and Zongzhi Liu and Catherine Lozupone and Daniel McDonald and Michael Robeson and Raymond Sammut and Sandra Smit and Wakefield, {Matthew J.} and Jeremy Widmann and Shandy Wikman and Stephanie Wilson and Hua Ying and Huttley, {Gavin A.}",

year = "2007",

month = aug,

day = "21",

doi = "10.1186/gb-2007-8-8-r171",

language = "English (US)",

volume = "8",

journal = "Genome Biology",

issn = "1474-7596",

publisher = "BioMed Central",

number = "8",

}

TY - JOUR

T1 - PyCogent

T2 - A toolkit for making sense from sequence

AU - Knight, Rob

AU - Maxwell, Peter

AU - Birmingham, Amanda

AU - Carnes, Jason

AU - Caporaso, J. Gregory

AU - Easton, Brett C.

AU - Eaton, Michael

AU - Hamady, Micah

AU - Lindsay, Helen

AU - Liu, Zongzhi

AU - Lozupone, Catherine

AU - McDonald, Daniel

AU - Robeson, Michael

AU - Sammut, Raymond

AU - Smit, Sandra

AU - Wakefield, Matthew J.

AU - Widmann, Jeremy

AU - Wikman, Shandy

AU - Wilson, Stephanie

AU - Ying, Hua

AU - Huttley, Gavin A.

PY - 2007/8/21

Y1 - 2007/8/21

N2 - We have implemented in Python the COmparative GENomic Toolkit, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics. PyCogent includes connectors to remote databases, built-in generalized probabilistic techniques for working with biological sequences, and controllers for third-party applications. The toolkit takes advantage of parallel architectures and runs on a range of hardware and operating systems, and is available under the general public license from http://sourceforge.net/projects/pycogent.

AB - We have implemented in Python the COmparative GENomic Toolkit, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics. PyCogent includes connectors to remote databases, built-in generalized probabilistic techniques for working with biological sequences, and controllers for third-party applications. The toolkit takes advantage of parallel architectures and runs on a range of hardware and operating systems, and is available under the general public license from http://sourceforge.net/projects/pycogent.

UR - http://www.scopus.com/inward/record.url?scp=34748893838&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34748893838&partnerID=8YFLogxK

U2 - 10.1186/gb-2007-8-8-r171

DO - 10.1186/gb-2007-8-8-r171

M3 - Article

C2 - 17708774

AN - SCOPUS:34748893838

VL - 8

JO - Genome Biology

JF - Genome Biology

SN - 1474-7596

IS - 8

M1 - R171

ER -