MEAGA - Revision history

Alextsoi at 01:37, 5 March 2015

2015-03-05T01:37:25Z

← Older revision		Revision as of 21:37, 4 March 2015
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	"interestedregionsgenes" is an one-column file with each row represents one unique locus, and the associated genes within the locus are separated by the semi-colon. "0" represents the difference between the number of function/pathway- overlapping genes and the number of function/pathway- overlapping loci we want.		"interestedregionsgenes" is an one-column file with each row represents one unique locus, and the associated genes within the locus are separated by the semi-colon. "0" represents the difference between the number of function/pathway- overlapping genes and the number of function/pathway- overlapping loci we want.

			== Citation ==


			[http://www.ncbi.nlm.nih.gov/pubmed/25480373 Lam C. Tsoi, James T. Elder, Gonçalo R. Abecasis. (2015) Graphical algorithm for integration of genetic and biological data: proof of principle using psoriasis as a model. Bioinformatics]



	== Contact ==		== Contact ==
	If you have any questions, please contact [[mailto:tsoi.teen@gmail.com Alex Lam C Tsoi]].		If you have any questions, please contact [[mailto:tsoi.teen@gmail.com Alex Lam C Tsoi]].

Alextsoi: /* Plot */

2014-11-12T16:02:09Z

Plot

← Older revision		Revision as of 12:02, 12 November 2014
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	== Plot ==		== Plot ==
	If you want to visualize the shortest paths between the genes from the associated regions in a particular function/pathway, we provide a python function (it requires the ~~lllmatplotliblll~~ module from python) to generate plot (genes from associated regions are in '''red'''; other genes present in the shortest paths are in '''blue'''):		If you want to visualize the shortest paths between the genes from the associated regions in a particular function/pathway, we provide a python function (it requires the '''matplotlib''' module from python) to generate plot (genes from associated regions are in '''red'''; other genes present in the shortest paths are in '''blue'''):

	./bin/plotFunIntPPI.py -a ./db/gene2fun.txt -s ./db/splitFun_fungenesSP_BioGrid/R/REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -p REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -m ./example/marker2gene.txt -i ./example/intmarkers -o ./test/testMEAGA_plot		./bin/plotFunIntPPI.py -a ./db/gene2fun.txt -s ./db/splitFun_fungenesSP_BioGrid/R/REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -p REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -m ./example/marker2gene.txt -i ./example/intmarkers -o ./test/testMEAGA_plot

Alextsoi: /* Plot */

2014-11-12T16:01:51Z

Plot

← Older revision		Revision as of 12:01, 12 November 2014
Line 162:		Line 162:

	== Plot ==		== Plot ==
	If you want to visualize the shortest paths between the genes from the associated regions in a particular function/pathway, we provide a python function (it requires the ~~matplotlib~~ module from python) to generate plot (genes from associated regions are in '''red'''; other genes present in the shortest paths are in '''blue'''):		If you want to visualize the shortest paths between the genes from the associated regions in a particular function/pathway, we provide a python function (it requires the lllmatplotliblll module from python) to generate plot (genes from associated regions are in '''red'''; other genes present in the shortest paths are in '''blue'''):

	./bin/plotFunIntPPI.py -a ./db/gene2fun.txt -s ./db/splitFun_fungenesSP_BioGrid/R/REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -p REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -m ./example/marker2gene.txt -i ./example/intmarkers -o ./test/testMEAGA_plot		./bin/plotFunIntPPI.py -a ./db/gene2fun.txt -s ./db/splitFun_fungenesSP_BioGrid/R/REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -p REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -m ./example/marker2gene.txt -i ./example/intmarkers -o ./test/testMEAGA_plot

Alextsoi: /* Plot */

2014-11-12T16:01:36Z

Plot

← Older revision		Revision as of 12:01, 12 November 2014
Line 162:		Line 162:

	== Plot ==		== Plot ==
	If you want to visualize the shortest paths between the genes from the associated regions in a particular function/pathway, we provide a python function to generate plot (genes from associated regions are in '''red'''; other genes present in the shortest paths are in '''blue'''):		If you want to visualize the shortest paths between the genes from the associated regions in a particular function/pathway, we provide a python function (it requires the matplotlib module from python) to generate plot (genes from associated regions are in '''red'''; other genes present in the shortest paths are in '''blue'''):

	./bin/plotFunIntPPI.py -a ./db/gene2fun.txt -s ./db/splitFun_fungenesSP_BioGrid/R/REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -p REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -m ./example/marker2gene.txt -i ./example/intmarkers -o ./test/testMEAGA_plot		./bin/plotFunIntPPI.py -a ./db/gene2fun.txt -s ./db/splitFun_fungenesSP_BioGrid/R/REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -p REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -m ./example/marker2gene.txt -i ./example/intmarkers -o ./test/testMEAGA_plot

Alextsoi: /* Introduction */

2014-11-12T03:14:27Z

Introduction

← Older revision		Revision as of 23:14, 11 November 2014
Line 4:		Line 4:
	The latest version of MEAGA could be obtained in here:		The latest version of MEAGA could be obtained in here:

	* [[ Media: MEAGA_1.1.tar.gz \| MEAGA_1.~~1.tar.gz ]]~~		* [[ Media: MEAGA_1.2.tar.gz \| MEAGA_1.2.tar.gz ]]
	* [[ Media: MEAGA_1.1_noSP.tar.gz \| MEAGA_1.1_noSP.tar.gz ]]

	== How it works ==		== How it works ==

Alextsoi: /* Pre-calculated shortest path distance */

2014-10-15T19:54:45Z

Pre-calculated shortest path distance

← Older revision		Revision as of 15:54, 15 October 2014
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	== Pre-calculated shortest path distance ==		== Pre-calculated shortest path distance ==
	The construction of Steiner trees is time consuming. The Kou’s algorithm requires the shortest distances and their paths to be first computed between genes. For effective performance, we pre-computed all shortest paths between genes in each function/pathway gene-set using data downloaded from different data sources and stored them in database to be readily retrieved when performing the Kou’s algorithm. ~~Users could email the authors if they would like a copy~~ of the compiled ~~database~~ of shortest paths for interaction data obtained BioGrid (http://thebiogrid.org/), HPRD (http://www.hprd.org/), and STRING (http://string-db.org/).		The construction of Steiner trees is time consuming. The Kou’s algorithm requires the shortest distances and their paths to be first computed between genes. For effective performance, we pre-computed all shortest paths between genes in each function/pathway gene-set using data downloaded from different data sources and stored them in database to be readily retrieved when performing the Kou’s algorithm. We provide users copies of the compiled databases of shortest paths for interaction data obtained BioGrid (http://thebiogrid.org/), HPRD (http://www.hprd.org/), and STRING (http://string-db.org/).

	If user wants '''MEAGA''' do perform enrichment test using the custom-interactome data (e.g. from other PPI source, or interaction data obtained from co-expression or text-mining analysis), we also provide a function to pre-compute all shortest paths for the custom data:		If user wants '''MEAGA''' do perform enrichment test using the custom-interactome data (e.g. from other PPI source, or interaction data obtained from co-expression or text-mining analysis), we also provide a function to pre-compute all shortest paths for the custom data:

Alextsoi: /* Introduction */

2014-10-15T19:53:11Z

Introduction

← Older revision		Revision as of 15:53, 15 October 2014
Line 4:		Line 4:
	The latest version of MEAGA could be obtained in here:		The latest version of MEAGA could be obtained in here:

	[[ Media: MEAGA_1.1.tar.gz \| MEAGA_1.1.tar.gz ]]		* [[ Media: MEAGA_1.1.tar.gz \| MEAGA_1.1.tar.gz ]]
	[[ Media: MEAGA_1.1_noSP.tar.gz \| MEAGA_1.1_noSP.tar.gz ]]		* [[ Media: MEAGA_1.1_noSP.tar.gz \| MEAGA_1.1_noSP.tar.gz ]]

	== How it works ==		== How it works ==

Alextsoi: /* Introduction */

2014-10-15T19:52:55Z

Introduction

← Older revision		Revision as of 15:52, 15 October 2014
Line 4:		Line 4:
	The latest version of MEAGA could be obtained in here:		The latest version of MEAGA could be obtained in here:

	[[ Media: ~~MEAGA~~ 1.~~0 noSP~~.~~zip~~ \| MEAGA_1.~~0_noSP~~.~~zip~~ ]]		[[ Media: MEAGA_1.1.tar.gz \| MEAGA_1.1.tar.gz ]]
			[[ Media: MEAGA_1.1_noSP.tar.gz \| MEAGA_1.1_noSP.tar.gz ]]
	~~Please contact the authors if you want to obtain a copy of MEAGA with the compiled database of each function's shortest path distances (see below)~~

	== How it works ==		== How it works ==

Alextsoi: /* Plot */

2014-10-14T21:14:38Z

Plot

← Older revision		Revision as of 17:14, 14 October 2014
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	If you want to visualize the shortest paths between the genes from the associated regions in a particular function/pathway, we provide a python function to generate plot (genes from associated regions are in '''red'''; other genes present in the shortest paths are in '''blue'''):		If you want to visualize the shortest paths between the genes from the associated regions in a particular function/pathway, we provide a python function to generate plot (genes from associated regions are in '''red'''; other genes present in the shortest paths are in '''blue'''):

	./bin/plotFunIntPPI.py -a ./db/gene2fun.txt -s ./db/~~splitFun_fungenesSP~~/R/REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -p REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -m ./example/marker2gene.txt -i ./example/intmarkers -o ./test/testMEAGA_plot		./bin/plotFunIntPPI.py -a ./db/gene2fun.txt -s ./db/splitFun_fungenesSP_BioGrid/R/REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -p REGULATION_OF_RESPONSE_TO_BIOTIC_STIMULUS -m ./example/marker2gene.txt -i ./example/intmarkers -o ./test/testMEAGA_plot

	This will generate a figure for the function "regulation of response to biotic stimulus":		This will generate a figure for the function "regulation of response to biotic stimulus":

Alextsoi: /* Tutorial */

2014-10-14T21:14:05Z

Tutorial

← Older revision		Revision as of 17:14, 14 October 2014
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	An example script for running MEAGA is also provided in ./example/testscript (run under the ./example directory)		An example script for running MEAGA is also provided in ./example/testscript (run under the ./example directory)

	../bin/MEAGA.py -s marker2gene.txt -g ../db/gene2fun.txt -i intmarkers -d ../db/~~splitFun_fungenesSP~~/ -o ../test/test -a 2 -m 5 -M 500 -t 10 -n 5000		../bin/MEAGA.py -s marker2gene.txt -g ../db/gene2fun.txt -i intmarkers -d ../db/splitFun_fungenesSP_BioGrid/ -o ../test/test -a 2 -m 5 -M 500 -t 10 -n 5000

	The result files of the above scripts are stored in ../test/ with prefix "test".		The result files of the above scripts are stored in ../test/ with prefix "test".