BiRG - Recent changes [en]

Metabolink Documentation

2012-05-11T19:03:53Z

O-PLS:

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	#: M - Used to create a customized external plot		#: M - Used to create a customized external plot
	# Running O-PLS		# Running O-PLS
-	After loading your data, selecting the appropriate options, and clicking run, you will be presented with a screen that looks like the following:	+	#:After loading your data, selecting the appropriate options, and clicking run, you will be presented with a screen that looks like the following:
	#: [[Image:metabolink_opls_results.png\|800px]]		#: [[Image:metabolink_opls_results.png\|800px]]

File:Metabolink opls results.png

2012-05-11T19:03:14Z

uploaded "[[File:Metabolink opls results.png]]"

Metabolink Documentation

2012-05-11T19:03:02Z

Looking for differences between groups:

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	#: L - Here is where you can customize the plot that is created by clicking on the plot button.		#: L - Here is where you can customize the plot that is created by clicking on the plot button.
	#: M - Used to create a customized external plot		#: M - Used to create a customized external plot
		+	# Running O-PLS
		+	After loading your data, selecting the appropriate options, and clicking run, you will be presented with a screen that looks like the following:
		+	#: [[Image:metabolink_opls_results.png\|800px]]

Software

2012-05-11T18:57:09Z

Step 2:

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	==== Step 1 ====		==== Step 1 ====
	You must install the MATLAB runtime environment before you are able to run this program. This only needs to be done once. The download depends on the operating system that you are running:		You must install the MATLAB runtime environment before you are able to run this program. This only needs to be done once. The download depends on the operating system that you are running:
-	* [http://stono.cs.cofc.edu/~andersonp/MCRInstaller.exe MCR-PC]	+	* [http://stono.cs.cofc.edu/~andersonp/MCRInstaller.exe Windows (32 bit) MCR-PC]
		+	* [http://stono.cs.cofc.edu/~andersonp/MCRInstaller_64bit.exe Windows (64 bit) MCR-PC]
	* [http://stono.cs.cofc.edu/~andersonp/MCRInstaller.zip MCR-Mac]		* [http://stono.cs.cofc.edu/~andersonp/MCRInstaller.zip MCR-Mac]

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	# If you are interested in automatically syncing the programs included in Metabolink, then you can request automatic distribution using Google Drive by e-mailing [mailto:pauleanderson@gmail.com Dr. Paul Anderson].		# If you are interested in automatically syncing the programs included in Metabolink, then you can request automatic distribution using Google Drive by e-mailing [mailto:pauleanderson@gmail.com Dr. Paul Anderson].
	# Or you can download a current snapshot of the software:		# Or you can download a current snapshot of the software:
-	## [http://stono.cs.cofc.edu/~andersonp/metabolink/pc.zip Windows]	+	## [http://stono.cs.cofc.edu/~andersonp/metabolink/pc_32bit.zip Windows (32 bit)]
		+	## [http://stono.cs.cofc.edu/~andersonp/metabolink/pc_64bit.zip Windows (64 bit)]
	## [http://stono.cs.cofc.edu/~andersonp/metabolink/mac.zip Mac]		## [http://stono.cs.cofc.edu/~andersonp/metabolink/mac.zip Mac]

Metabolink Documentation

2012-05-11T18:06:22Z

O-PLS:

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	# A map of the interface		# A map of the interface
	#: [[Image:metabolink_opls_map.png\|800px]]		#: [[Image:metabolink_opls_map.png\|800px]]
		+	#: A - (Required) You can load your data by clicking this button. We currently support the tab delimited files described at the beginning of this document.
		+	#: B - Once your data is loaded, you have the option of selecting two or more groups of data to create the model.
		+	#: C - You also have the option of ignoring certain samples or groups of samples.
		+	#: D - (Required) You can then specify how you would like the data grouped for visualization purposes. This may be different or identical to the model selection.
		+	#: E - You also have the option of pairing your samples together.
		+	#: F - This is where the scores plot of the model will be displayed.
		+	#: G - The validation section allows you to specific k-fold cross-validation, leave-one-out cross-validation or bootstrapping.
		+	#: H - You may also specify an alpha value for the significance of the model.
		+	#: I - You may also select the number of permutations to use when validating with a randomization test.
		+	#: J - (Required) Once you have selected your options, you can then run the model
		+	#: K - Once the results are available, there are several different views available.
		+	#: L - Here is where you can customize the plot that is created by clicking on the plot button.
		+	#: M - Used to create a customized external plot

File:Metabolink opls map.png

2012-05-11T17:56:13Z

uploaded "[[File:Metabolink opls map.png]]"

Metabolink Documentation

2012-05-11T17:55:44Z

O-PLS:

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	# Starting the program		# Starting the program
	#: In Windows you can start the program by clicking opls.exe, and on a Mac you may click on the opls application.		#: In Windows you can start the program by clicking opls.exe, and on a Mac you may click on the opls application.
-	#: [[Image:metabolink_contents.png]]	+	#: [[Image:metabolink_contents.png\|800px]]
	# A map of the interface		# A map of the interface
		+	#: [[Image:metabolink_opls_map.png\|800px]]

File:Metabolink contents.png

2012-05-11T17:45:53Z

uploaded "[[File:Metabolink contents.png]]"

Metabolink Documentation

2012-05-11T17:45:41Z

O-PLS:

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	You can create this document in Excel, but you must save it as a tab-delimited file. This file is referred to as a collection. Here is a template that you can modify to meet your needs: [[File:collection_1_template.txt]].		You can create this document in Excel, but you must save it as a tab-delimited file. This file is referred to as a collection. Here is a template that you can modify to meet your needs: [[File:collection_1_template.txt]].
		+
		+	= Looking for differences between groups =
		+	== O-PLS ==
		+	# Starting the program
		+	#: In Windows you can start the program by clicking opls.exe, and on a Mac you may click on the opls application.
		+	#: [[Image:metabolink_contents.png]]
		+	# A map of the interface

File:Collection 1 template.txt

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uploaded "[[File:Collection 1 template.txt]]"

Metabolink Documentation

2012-05-10T18:53:14Z

Data Format:

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	9.2 1.22 3.41		9.2 1.22 3.41
	9.1 3.49 5.13		9.1 3.49 5.13
-	9.0 5.38 1.67	+	9.0 5.38 1.67</nowiki>
-	</nowiki>	+

	You can add additional information as you desire.		You can add additional information as you desire.
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	9.2 1.22 3.41		9.2 1.22 3.41
	9.1 3.49 5.13		9.1 3.49 5.13
-	9.0 5.38 1.67	+	9.0 5.38 1.67</nowiki>
-	</nowiki>	+
		+	You can create this document in Excel, but you must save it as a tab-delimited file. This file is referred to as a collection. Here is a template that you can modify to meet your needs: [[File:collection_1_template.txt]].

Software

2012-05-10T17:36:32Z

Contributed to the project:

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	Click [[Metabolink Documentation\|here]] for documentation.		Click [[Metabolink Documentation\|here]] for documentation.

-	=== ~~Contributed~~ to the project ===	+	=== Contribute to the project ===
	The source code for the project is hosted at GitHub. You can contribute at https://github.com/BirgPublicizer/Metabolomics-Analysis-Toolbox.		The source code for the project is hosted at GitHub. You can contribute at https://github.com/BirgPublicizer/Metabolomics-Analysis-Toolbox.

Metabolink Documentation

2012-05-10T17:35:51Z

Created page with "= Data Format = The software is designed to handle a dynamic set of metadata fields, which are specific at the top of a tab delimited file. Here is a minimal example of a valid i..."

New page

= Data Format =
The software is designed to handle a dynamic set of metadata fields, which are specific at the top of a tab delimited file. Here is a minimal example of a valid input file with two samples:
<nowiki>
Collection ID 1
Description <string>
Processing log <string>
Any field name Value for Y1 Value for Y2
X Y1 Y2
9.2 1.22 3.41
9.1 3.49 5.13
9.0 5.38 1.67
</nowiki>

You can add additional information as you desire.
<nowiki>
Collection ID 1
Description <string>
Processing log <string>
Time 24 48
Dose 50 mg/kg 50 mg/kg
X Y1 Y2
9.2 1.22 3.41
9.1 3.49 5.13
9.0 5.38 1.67
</nowiki>

Software

2012-05-10T17:28:22Z

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	= Metabolomics Software =		= Metabolomics Software =
	== Metabolink ==		== Metabolink ==
		+	The metabolomics analysis toolbox (Metabolink) is a collection of software developed by the Bioinformatics Research Groups at the College of Charleston and Wright State University to help in metabolomics research. It consists of GUI software to help in various phases of the analysis of the complex NMR spectra produced by biofluids (blood, urine, cerebrospinal fluid, tissue homogenates, etc).
		+
	=== Download ===		=== Download ===
-	~~https~~://~~docs~~.~~google~~.com/~~folder~~/d/~~0B9ezel2UVnBpQ2FWR0t5bGxrV0U~~/~~edit~~	+	==== Step 1 ====
		+	You must install the MATLAB runtime environment before you are able to run this program. This only needs to be done once. The download depends on the operating system that you are running:
		+	* [http://stono.cs.cofc.edu/~andersonp/MCRInstaller.exe MCR-PC]
		+	* [http://stono.cs.cofc.edu/~andersonp/MCRInstaller.zip MCR-Mac]
		+
		+	==== Step 2 ====
		+	There are two ways to download Metabolink:
		+	# If you are interested in automatically syncing the programs included in Metabolink, then you can request automatic distribution using Google Drive by e-mailing [mailto:pauleanderson@gmail.com Dr. Paul Anderson].
		+	# Or you can download a current snapshot of the software:
		+	## [http://stono.cs.cofc.edu/~andersonp/metabolink/pc.zip Windows]
		+	## [http://stono.cs.cofc.edu/~andersonp/metabolink/mac.zip Mac]

	=== Generalized Model For Metabolomic Analysis ===		=== Generalized Model For Metabolomic Analysis ===
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	For more information click [[Dynamic Adaptive Binning\|here]].		For more information click [[Dynamic Adaptive Binning\|here]].
		+
		+	=== Documentation ===
		+	Click [[Metabolink Documentation\|here]] for documentation.
		+
		+	=== Contributed to the project ===
		+	The source code for the project is hosted at GitHub. You can contribute at https://github.com/BirgPublicizer/Metabolomics-Analysis-Toolbox.

	== SCALE ==		== SCALE ==
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	Ajith Ranabahu, Paul Anderson, and Amit Sheth. (2011). The Cloud Agnostic e-Science Analysis Platform, IEEE Internet Computing, vol. 15, no. 6, pp. 85-89, Nov./Dec. 2011, doi:10.1109/MIC.2011.159		Ajith Ranabahu, Paul Anderson, and Amit Sheth. (2011). The Cloud Agnostic e-Science Analysis Platform, IEEE Internet Computing, vol. 15, no. 6, pp. 85-89, Nov./Dec. 2011, doi:10.1109/MIC.2011.159

-	== GenoStat ==	+	= GenoStat =
	GenoStat is a forensic DNA analysis java-based application that generates DNA profile match statistics (RMP, CPI and things like sibling match probabilities) as well performing mixture resolution (separating mixtures into their contributor components).		GenoStat is a forensic DNA analysis java-based application that generates DNA profile match statistics (RMP, CPI and things like sibling match probabilities) as well performing mixture resolution (separating mixtures into their contributor components).

	[http://www.bioforensics.com/genostat/index.html For more information]		[http://www.bioforensics.com/genostat/index.html For more information]

-		+	= Cloud-based Laboratory Informatics Management System =
-	== Cloud-based Laboratory Informatics Management System ==	+
	The emergence of informatics as a field of study has brought about tremendous advances in the life sciences - the sequencing of the human genome; inferring the structure of proteins; identifying the activity of microRNA; and the list goes on. And yet, a remarkable characteristic of some of this pioneering work is that it is not “collaboration” at all in the traditional sense of the term. In the old model, scientists with a common interest would team up and address a problem together. But this sort of one-to-one collaboration is rapidly being replaced by something far more exciting. In the age of informatics experimental results from tens of thousands of similar experiments conducted by scientists worldwide are available in online libraries. These repositories serve as much more than simple archives. They are the digital playgrounds for computational scientists with innovative ideas for data visualization, analysis, and management.		The emergence of informatics as a field of study has brought about tremendous advances in the life sciences - the sequencing of the human genome; inferring the structure of proteins; identifying the activity of microRNA; and the list goes on. And yet, a remarkable characteristic of some of this pioneering work is that it is not “collaboration” at all in the traditional sense of the term. In the old model, scientists with a common interest would team up and address a problem together. But this sort of one-to-one collaboration is rapidly being replaced by something far more exciting. In the age of informatics experimental results from tens of thousands of similar experiments conducted by scientists worldwide are available in online libraries. These repositories serve as much more than simple archives. They are the digital playgrounds for computational scientists with innovative ideas for data visualization, analysis, and management.

O-PLS

2012-05-09T18:21:04Z

Downloading:

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	= Documentation =		= Documentation =
	Coming soon		Coming soon
-
-	~~= Downloading =~~
-	~~== Step 1 ==~~
-	~~You must install the MATLAB runtime environment before you are able to run this program. This only needs to be done once. The download depends on the operating system that you are running:~~
-	* [https://drive.google.com/uc?id=0B9ezel2UVnBpTmduNDExYnVIQ0E&export=download MCR-PC]
-	* [https://drive.google.com/uc?id=0B9ezel2UVnBpV0daNVhQNVZqUUE&export=download MCR-Mac]
-	~~I'm using Google Drive to host the files, so it will tell you that it cannot scan a file this size for viruses. Click download anyway.~~
-
-	~~== Step 2 ==~~
-	~~There are two ways to download Metabolink:~~
-	# If you are interested in automatically syncing the programs included in Metabolink, then you can request automatic distribution using Google Drive by e-mailing [mailto:pauleanderson@gmail.com Dr. Paul Anderson].
-	~~# Or you can download individual programs by browsing [https://docs.google.com/open?id=0B9ezel2UVnBpS1psVnlzWTBRYlE here].~~

Software

2012-05-09T18:20:46Z

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-	== Metabolomics Software ==	+	= Metabolomics Software =
		+	== Metabolink ==
		+	=== Download ===
		+	https://docs.google.com/folder/d/0B9ezel2UVnBpQ2FWR0t5bGxrV0U/edit
		+
	=== Generalized Model For Metabolomic Analysis ===		=== Generalized Model For Metabolomic Analysis ===
	==== [[O-PLS\|O-PLS]] ====		==== [[O-PLS\|O-PLS]] ====
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	Anderson, P. E., Ranabahu, A. H., Mahle, D.A., Sheth, A. P., and DelRaso, N. J. (2012). Cloud-based Map-Reduce NMR Spectral Deconvolution: Adjacent Deconvolution. In press BIOCOMP 2012.		Anderson, P. E., Ranabahu, A. H., Mahle, D.A., Sheth, A. P., and DelRaso, N. J. (2012). Cloud-based Map-Reduce NMR Spectral Deconvolution: Adjacent Deconvolution. In press BIOCOMP 2012.

-	=== ~~SCALE~~ ===	+	=== Dynamic Adaptive Binning ===
		+	The interpretation of nuclear magnetic resonance (NMR) experimental results for metabolomics studies requires intensive signal processing and multivariate data analysis techniques. A key step in this process is the quantification of spectral features, which is commonly accomplished by dividing an NMR spectrum into several hundred integral regions or bins. Binning attempts to minimize effects from variations in peak positions caused by sample pH, ionic strength, and composition, while reducing the dimensionality for multivariate statistical analyses. Herein we develop an improved novel spectral quantification technique, dynamic adaptive binning. With this technique, bin boundaries are determined by optimizing an objective function using a dynamic programming strategy. The objective function measures the quality of a bin configuration based on the number of peaks per bin. This technique shows a significant improvement over both traditional uniform binning and other adaptive binning techniques. This improvement is quantified via synthetic validation sets by analyzing an algorithm’s ability to create bins that do not contain more than a single peak and that maximize the distance from peak to bin boundary. The validation sets are developed by characterizing the salient distributions in experimental NMR spectroscopic data. Further, dynamic adaptive binning is applied to a 1H NMR-based experiment to monitor rat urinary metabolites to empirically demonstrate improved spectral quantification.
		+
		+	Anderson, P. E., Raymer, M. L., Reo, N. V., DelRaso, N. J., and Doom, T. E. (2010). Dynamic Adaptive Binning: Dynamic quantification of nuclear magnetic resonance spectroscopic data. In press in the journal Metabolomics.Available online at http://dx.doi.org/10.1007/s11306-010-0242-7.
		+
		+	For more information click [[Dynamic Adaptive Binning\|here]].
		+
		+	== SCALE ==
	The recent flood of Web-enabled and Web-based tools for eScience has provided scientists with a wide array of new methods to collect, report, analyze and share their data. These Web-based technologies have demonstrated a great potential to enable broader collaboration and to facilitate the sharing and re-use of experimental data. The wide availability of quality data sets and tested process flows is indeed a welcome addition for an eScientist, yet there are a number of challenges to overcome. In scientific domains, such as bioinformatics, lack of standardization for scientific methods, algorithms, and data sharing can be seen as the greatest challenge for broader adoption.		The recent flood of Web-enabled and Web-based tools for eScience has provided scientists with a wide array of new methods to collect, report, analyze and share their data. These Web-based technologies have demonstrated a great potential to enable broader collaboration and to facilitate the sharing and re-use of experimental data. The wide availability of quality data sets and tested process flows is indeed a welcome addition for an eScientist, yet there are a number of challenges to overcome. In scientific domains, such as bioinformatics, lack of standardization for scientific methods, algorithms, and data sharing can be seen as the greatest challenge for broader adoption.

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	Ajith Ranabahu, Paul Anderson, and Amit Sheth. (2011). The Cloud Agnostic e-Science Analysis Platform, IEEE Internet Computing, vol. 15, no. 6, pp. 85-89, Nov./Dec. 2011, doi:10.1109/MIC.2011.159		Ajith Ranabahu, Paul Anderson, and Amit Sheth. (2011). The Cloud Agnostic e-Science Analysis Platform, IEEE Internet Computing, vol. 15, no. 6, pp. 85-89, Nov./Dec. 2011, doi:10.1109/MIC.2011.159
-
-	~~== Dynamic Adaptive Binning ==~~
-	The interpretation of nuclear magnetic resonance (NMR) experimental results for metabolomics studies requires intensive signal processing and multivariate data analysis techniques. A key step in this process is the quantification of spectral features, which is commonly accomplished by dividing an NMR spectrum into several hundred integral regions or bins. Binning attempts to minimize effects from variations in peak positions caused by sample pH, ionic strength, and composition, while reducing the dimensionality for multivariate statistical analyses. Herein we develop an improved novel spectral quantification technique, dynamic adaptive binning. With this technique, bin boundaries are determined by optimizing an objective function using a dynamic programming strategy. The objective function measures the quality of a bin configuration based on the number of peaks per bin. This technique shows a significant improvement over both traditional uniform binning and other adaptive binning techniques. This improvement is quantified via synthetic validation sets by analyzing an algorithm’s ability to create bins that do not contain more than a single peak and that maximize the distance from peak to bin boundary. The validation sets are developed by characterizing the salient distributions in experimental NMR spectroscopic data. Further, dynamic adaptive binning is applied to a 1H NMR-based experiment to monitor rat urinary metabolites to empirically demonstrate improved spectral quantification.
-
-	Anderson, P. E., Raymer, M. L., Reo, N. V., DelRaso, N. J., and Doom, T. E. (2010). Dynamic Adaptive Binning: Dynamic quantification of nuclear magnetic resonance spectroscopic data. In press in the journal Metabolomics.Available online at http://dx.doi.org/10.1007/s11306-010-0242-7.
-
-	~~For more information click [[Dynamic Adaptive Binning\|here]].~~

	== GenoStat ==		== GenoStat ==