Microsoft Computational Biology Tools

New Post: HLA Completion - small typo

delordson — Mon, 14 Sep 2009 05:20:17 GMT

Hi,

There is a small but significant typo in the summary info on the HLA Completion tool. Where it states:

"For example, an allele may be identified as A6801/6802 or simply A02."

This should actually be A28, as A*6801 and A*6802 are both alleles of A28 not A02 (even though A02 is closely related in sequence and reactivity).

Delordson Kallon

HLA Bioinformatics Specialist

National Blood Service, England

New Post: HLA Completion Result Sort Order

delordson — Sat, 12 Sep 2009 08:45:16 GMT

Just heard you and Dot Net Rocks (www.dotnetrocks.com) so I came over here to have a look. The HLA completion tool looks very interesting. I'll play it against some of our data and let you know how it goes.

Can I suggest that if possible, the result s be sorted in decreasing order of probability. I tested it with A*0101 A*0201 B*0801 B*4402 C*0501 C*0701 in a European population and almost dismissed the tool when I saw the results until I took a closer look at the probabilities.

Delordson Kallon

HLA Bioinformatics Specialist

National Blood Service, England

Updated Wiki: False Discovery Rate

guyshani — Thu, 21 May 2009 21:23:21 GMT

False Discovery Rate for 2X2 Contingency Tables

This tool estimates the False Discovery Rate (FDR) for 2X2 Contingency Tables, based on the Fisher statistics.

Overview

When testing a large number of hypotheses, it can be helpful to
estimate or control the false discovery rate (FDR), the expected
proportion of tests called significant that are truly null. We use Fisher's exact test to calculate the exact null distribution over a set of 2X2 contingency tables.
Using these statistics we compute pooled pvalues, estimate the ratio of true nulls, and compute qvalues.

Application

We provide two versions of the application; A command line interface (FalseDiscoveryRate.exe) and a graphic user interface (FalseDiscoveryRateUI.exe). For a full description of the available options, please refer to the techincal report.

The graphic user interface supports the following options:

Input file - a tab delimited input file containing the description of all the tables. Each line in this file must contain one table, except for the first line that may cotnain column headers.
Output file - the results of the computation will be saved as a tab delimited text file.
Data properties
- First row contains column headers - use this option to ignore the first line of the input file.
- Table counts start at column - use this to ignore a number of columns before the table counts, such as the description of the table.
Operation properties
- Filter irrelvant tables - use this option to ignore tables with marginals that cannot possibly achieve a significant p-value.
- PI evaluation method - the method used to evaluate the ratio of true nulls in the test set. We support the following options:

PI = 1 - do not evaluate PI
Sum observed p-values / expected - estimate PI using the ratio between the number of observed p-values among the test set and the expected number of test with the specific p-value under the null hypothesis. When filtering is selected - this is the only valid option.
2 X avg(p-value) - estiamte PI using twice the average p-value.

Compute Positive FDR (pFDR) - use this option to compute the positive false discovery rate.
Use sampling - use this option when the set of table is too large. The computation will be executed only over a sample of the input tables, and then the mapping between p-value and q-value will be applied to all tables. You can either specify the sample size, or select Automated sampling, which will start with a small sample and grow the sample size until no significant difference in the p-value to q-value mapping has been detected.
Huge dataset mode - use this mode to aggregate tables with identical counts. This reduces memory consumption at the cost of slower computation.

Output properties
- Report progress while running - when this option is selected, a dialog reporting the progress of the computation will be displayed.
- Ouptut all the computed statistics - when this option is selected, all the computed statistics will be saved to the output file. Otherwise, only the input data and the q-values will be written to the output file.
- Output only tables with q-value less than - use this to restrict the output only to tables with q-value below the specified q-value.
The command line application supports similar options. Run the program without any parameters to see the avialble options

References
Jonathan Carlson and David Heckerman and Guy Shani. False Discovery Rate for 2X2 Contingency Tables. Techincal report, Microsoft Research, 2009.

Web Version
http://research.microsoft.com/en-us/um/redmond/projects/MSCompBio/
Pre-Compiled Programs for Windows
- To install the program
  - Go to http://www.codeplex.com/MSCompBio/Release/ProjectReleases.aspx
  - Then click "FalseDiscoveryRate.msi"
Source Code Files
(To download see Source Code tab above)
- Solution file: FalseDiscoveryRate\FalseDiscoveryRate.sln
- Build directory: FalseDiscoveryRate\bin\Release
Compiling the project requires
- Visual Studio 2008 SP1

Updated Wiki: False Discovery Rate

guyshani — Thu, 21 May 2009 21:22:23 GMT

False Discovery Rate for 2X2 Contingency Tables

This tool estimates the False Discovery Rate (FDR) for 2X2 Contingency Tables, based on the Fisher statistics.

Overview

Application

Input file - a tab delimited input file containing the description of all the tables. Each line in this file must contain one table, except for the first line that may cotnain column headers.
Output file - the results of the computation will be saved as a tab delimited text file.
Data properties
- First row contains column headers - use this option to ignore the first line of the input file.
- Table counts start at column - use this to ignore a number of columns before the table counts, such as the description of the table.
Operation properties
- Filter irrelvant tables - use this option to ignore tables with marginals that cannot possibly achieve a significant p-value.
- PI evaluation method - the method used to evaluate the ratio of true nulls in the test set. We support the following options:

PI = 1 - do not evaluate PI
Sum observed p-values / expected - estimate PI using the ratio between the number of observed p-values among the test set and the expected number of test with the specific p-value under the null hypothesis. When filtering is selected - this is the only valid option.
2 X avg(p-value) - estiamte PI using twice the average p-value.

Compute Positive FDR (pFDR) - use this option to compute the positive false discovery rate.
Use sampling - use this option when the set of table is too large. The computation will be executed only over a sample of the input tables, and then the mapping between p-value and q-value will be applied to all tables. You can either specify the sample size, or select Automated sampling, which will start with a small sample and grow the sample size until no significant difference in the p-value to q-value mapping has been detected.
Huge dataset mode - use this mode to aggregate tables with identical counts. This reduces memory consumption at the cost of slower computation.

Output properties
- Report progress while running - when this option is selected, a dialog reporting the progress of the computation will be displayed.
- Ouptut all the computed statistics - when this option is selected, all the computed statistics will be saved to the output file. Otherwise, only the input data and the q-values will be written to the output file.
- Output only tables with q-value less than - use this to restrict the output only to tables with q-value below the specified q-value.
The command line application supports similar options. Run the program without any parameters to see the avialble options

References
Jonathan Carlson and David Heckerman and Guy Shani. False Discovery Rate for 2X2 Contingency Tables. Techincal report, Microsoft Research, 2009.

Web Version
http://research.microsoft.com/en-us/um/redmond/projects/MSCompBio/
Pre-Compiled Programs for Windows
- To install the program
  - Go to http://www.codeplex.com/MSCompBio/Release/ProjectReleases.aspx
  - Then click "FalseDiscoveryRate.msi"
Source Code Files
(To download see Source Code tab above)
- Solution file: FalseDiscoveryRate\FalseDiscoveryRate.sln
- Build directory: FalseDiscoveryRate\bin\Release
Compiling the project requires
- Visual Studio 2008 SP1

Updated Release: V2 RC2 (Oct 31, 2008)

guyshani — Fri, 01 May 2009 13:46:10 GMT

HlaCompletion, version 2
CreateEpitome, version 1.0.0.1
False DiscoveryRate, version 1.0.0.1

See "RC1" (version 1) for the best release of the other tools.

Released: V2 RC2 (Oct 31, 2008)

Fri, 01 May 2009 13:46:10 GMT

HlaCompletion, version 2
CreateEpitome, version 1.0.0.1
False DiscoveryRate, version 1.0.0.1

See "RC1" (version 1) for the best release of the other tools.

Updated Wiki: False Discovery Rate

guyshani — Fri, 01 May 2009 13:40:23 GMT

False Discovery Rate for 2X2 Contingency Tables

This tool estimates the False Discovery Rate (FDR) for 2X2 Contingency Tables, based on the Fisher statistics.

Overview

Application

Input file - a tab delimited input file containing the description of all the tables. Each line in this file must contain one table, except for the first line that may cotnain column headers.
Output file - the results of the computation will be saved as a tab delimited text file.
Data properties
- First row contains column headers - use this option to ignore the first line of the input file.
- Table counts start at column - use this to ignore a number of columns before the table counts, such as the description of the table.
Operation properties
- Filter irrelvant tables - use this option to ignore tables with marginals that cannot possibly achieve a significant p-value.
- PI evaluation method - the method used to evaluate the ratio of true nulls in the test set. We support the following options:

PI = 1 - do not evaluate PI
Sum observed p-values / expected - estimate PI using the ratio between the number of observed p-values among the test set and the expected number of test with the specific p-value under the null hypothesis. When filtering is selected - this is the only valid option.
2 X avg(p-value) - estiamte PI using twice the average p-value.

Compute Positive FDR (pFDR) - use this option to compute the positive false discovery rate.
Use sampling - use this option when the set of table is too large. The computation will be executed only over a sample of the input tables, and then the mapping between p-value and q-value will be applied to all tables. You can either specify the sample size, or select Automated sampling, which will start with a small sample and grow the sample size until no significant difference in the p-value to q-value mapping has been detected.
Huge dataset mode - use this mode to aggregate tables with identical counts. This reduces memory consumption at the cost of slower computation.

Output properties
- Report progress while running - when this option is selected, a dialog reporting the progress of the computation will be displayed.
- Ouptut all the computed statistics - when this option is selected, all the computed statistics will be saved to the output file. Otherwise, only the input data and the q-values will be written to the output file.
- Output only tables with q-value less than - use this to restrict the output only to tables with q-value below the specified q-value.
The command line application supports similar options. Run the program without any parameters to see the avialble options

References
Jonathan Carlson and David Heckerman and Guy Shani. False Discovery Rate for 2X2 Contingency Tables. Techincal report, Microsoft Research, 2009.

Web Version
http://research.microsoft.com/en-us/um/redmond/projects/MSCompBio/
Pre-Compiled Programs for Windows
- To install the program
  - Go to http://www.codeplex.com/MSCompBio/Release/ProjectReleases.aspx
  - Then click "FalseDiscoveryRate.msi"
Source Code Files
(To download see Source Code tab above)
- Solution file: FalseDiscoveryRate\FalseDiscoveryRate.sln
- Build directory: FalseDiscoveryRate\bin\Release
Compiling the project requires
- Visual Studio 2008 SP1

Updated Wiki: False Discovery Rate

guyshani — Fri, 01 May 2009 13:31:13 GMT

False Discovery Rate for 2X2 Contingency Tables

This tool estimates the False Discovery Rate (FDR) for 2X2 Contingency Tables, based on the Fisher statistics.

Overview

Application

We provide two versions of the application; A command line interface (FalseDiscoveryRateCommandLine.exe) and a graphic user interface (FalseDiscoveryRateUI.exe). For a full description of the available options, please refer to the techincal report.

The graphic user interface supports the following options:

Input file - a tab delimited input file containing the description of all the tables. Each line in this file must contain one table, except for the first line that may cotnain column headers.
Output file - the results of the computation will be saved as a tab delimited text file.
Data properties
- First row contains column headers - use this option to ignore the first line of the input file.
- Table counts start at column - use this to ignore a number of columns before the table counts, such as the description of the table.
Operation properties
- Filter irrelvant tables - use this option to ignore tables with marginals that cannot possibly achieve a significant p-value.
- PI evaluation method - the method used to evaluate the ratio of true nulls in the test set. We support the following options:

PI = 1 - do not evaluate PI
Sum observed p-values / expected - estimate PI using the ratio between the number of observed p-values among the test set and the expected number of test with the specific p-value under the null hypothesis. When filtering is selected - this is the only valid option.
2 X avg(p-value) - estiamte PI using twice the average p-value.

Compute Positive FDR (pFDR) - use this option to compute the positive false discovery rate.
Use sampling - use this option when the set of table is too large. The computation will be executed only over a sample of the input tables, and then the mapping between p-value and q-value will be applied to all tables. You can either specify the sample size, or select Automated sampling, which will start with a small sample and grow the sample size until no significant difference in the p-value to q-value mapping has been detected.
Huge dataset mode - use this mode to aggregate tables with identical counts. This reduces memory consumption at the cost of slower computation.

Output properties
- Report progress while running - when this option is selected, a dialog reporting the progress of the computation will be displayed.
- Ouptut all the computed statistics - when this option is selected, all the computed statistics will be saved to the output file. Otherwise, only the input data and the q-values will be written to the output file.
- Output only tables with q-value less than - use this to restrict the output only to tables with q-value below the specified q-value.
References
D. Yerly, D. Heckerman, T. Allen, T. Suscovich, N. Jojic, C. Kadie, W. Pichler, A. Cerny, C. Brander. Design, expression and processing of epitomized HCV encoded CTL epitopes. J. Immunol, to appear.

D. Nickle, N. Jojic, D. Heckerman, V. Jojic, D. Kirovski, M. Rolland, S. Pond, J. Mullins. Comparison of immunogen designs that optimize peptide coverage: Reply to Fischer et al., PLoS Computational Biology, 4(1):e25, January 2008.

D. Nickle, M. Rolland, M. Jensen, S. Pond, W. Deng, M. Seligman, D. Heckerman, J. Mullins, and N. Jojic. Coping with viral diversity in HIV vaccine design, PLoS Computational Biology, 3(4): e75, April 2007.

N. Jojic, V. Jojic, B. Frey, C. Meek, and D. Heckerman. Using epitomes to model genetic diversity: Rational design of HIV vaccine cocktails. NIPS 2005.

Web Version
http://atom.research.microsoft.com/EpitomeCreator/
Pre-Compiled Programs for Windows
- To install the program
  - Go to http://www.codeplex.com/MSCompBio/Release/ProjectReleases.aspx
  - Then click "CreateEpitome.msi"
Interactive Version
- Run by selecting "Start" and "Create Epitome"
Command-Line Exe's:
- How to run CreateEpitome, the command-line exe
  - Regression test
Source Code Files
(To download see Source Code tab above)
- Solution file: CreateEpitome\CreateVaccine\CreateEpitome.sln
- Build directory: CreateEpitome\CreateVaccine\CreateEpitome\bin\Release
Compiling the project requires
- Visual Studio 2008 SP1
- Silverlight Tools for VS 2008 SP1
- Microsoft Parallel Extensions to .NET Framework 3.5, June 2008 Community Technology Preview. The Parallel Extensions library enables the program to use multiple processors at the cost of just a few lines of code.
Some source code features of possible interest:
- Builds both Silverlight and .NET versions from the same C# code in the same Visual Studio solution.
- Includes installer that installs both versions including setting up the Silverlight version to run locally.
- The Silverlight version resizes the Silverlight control on the web page.
- The Silverlight version shows results interactively as they are produced. It allows the run to be paused and continued. It plots the performance of the algorithm.
- The command-line version runs multi-core, if available.
- The Silverlight control appears in an HTML table and is visable to both IE and Firefox.
- The code uses the HashSet data structure. For Silverlight, where HashSet is not available automatically, a mini version is provided.

How to run regression tests

Updated Wiki: False Discovery Rate

guyshani — Fri, 01 May 2009 13:30:44 GMT

False Discovery Rate for 2X2 Contingency Tables

This tool estimates the False Discovery Rate (FDR) for 2X2 Contingency Tables, based on the Fisher statistics.

Overview

Application

Input file - a tab delimited input file containing the description of all the tables. Each line in this file must contain one table, except for the first line that may cotnain column headers.
Output file - the results of the computation will be saved as a tab delimited text file.
Data properties
- First row contains column headers - use this option to ignore the first line of the input file.
- Table counts start at column - use this to ignore a number of columns before the table counts, such as the description of the table.
Operation properties
- Filter irrelvant tables - use this option to ignore tables with marginals that cannot possibly achieve a significant p-value.
- PI evaluation method - the method used to evaluate the ratio of true nulls in the test set. We support the following options:

PI = 1 - do not evaluate PI
Sum observed p-values / expected - estimate PI using the ratio between the number of observed p-values among the test set and the expected number of test with the specific p-value under the null hypothesis. When filtering is selected - this is the only valid option.
2\avg(p-value) - estiamte PI using twice the average p-value.

Compute Positive FDR (pFDR) - use this option to compute the positive false discovery rate.

Use sampling - use this option when the set of table is too large. The computation will be executed only over a sample of the input tables, and then the mapping between p-value and q-value will be applied to all tables. You can either specify the sample size, or select Automated sampling, which will start with a small sample and grow the sample size until no significant difference in the p-value to q-value mapping has been detected.

Huge dataset mode - use this mode to aggregate tables with identical counts. This reduces memory consumption at the cost of slower computation.
Output properties
Report progress while running - when this option is selected, a dialog reporting the progress of the computation will be displayed.

Ouptut all the computed statistics - when this option is selected, all the computed statistics will be saved to the output file. Otherwise, only the input data and the q-values will be written to the output file.

Output only tables with q-value less than - use this to restrict the output only to tables with q-value below the specified q-value.

References
D. Yerly, D. Heckerman, T. Allen, T. Suscovich, N. Jojic, C. Kadie, W. Pichler, A. Cerny, C. Brander. Design, expression and processing of epitomized HCV encoded CTL epitopes. J. Immunol, to appear.

D. Nickle, N. Jojic, D. Heckerman, V. Jojic, D. Kirovski, M. Rolland, S. Pond, J. Mullins. Comparison of immunogen designs that optimize peptide coverage: Reply to Fischer et al., PLoS Computational Biology, 4(1):e25, January 2008.

D. Nickle, M. Rolland, M. Jensen, S. Pond, W. Deng, M. Seligman, D. Heckerman, J. Mullins, and N. Jojic. Coping with viral diversity in HIV vaccine design, PLoS Computational Biology, 3(4): e75, April 2007.

N. Jojic, V. Jojic, B. Frey, C. Meek, and D. Heckerman. Using epitomes to model genetic diversity: Rational design of HIV vaccine cocktails. NIPS 2005.

Web Version
http://atom.research.microsoft.com/EpitomeCreator/
Pre-Compiled Programs for Windows

To install the program
Go to http://www.codeplex.com/MSCompBio/Release/ProjectReleases.aspx

Then click "CreateEpitome.msi"

Interactive Version

Run by selecting "Start" and "Create Epitome"

Command-Line Exe's:

How to run CreateEpitome, the command-line exe
Regression test

Source Code Files
(To download see Source Code tab above)
Solution file: CreateEpitome\CreateVaccine\CreateEpitome.sln

Build directory: CreateEpitome\CreateVaccine\CreateEpitome\bin\Release

Compiling the project requires
Visual Studio 2008 SP1

Silverlight Tools for VS 2008 SP1

Microsoft Parallel Extensions to .NET Framework 3.5, June 2008 Community Technology Preview. The Parallel Extensions library enables the program to use multiple processors at the cost of just a few lines of code.

Some source code features of possible interest:
Builds both Silverlight and .NET versions from the same C# code in the same Visual Studio solution.

Includes installer that installs both versions including setting up the Silverlight version to run locally.

The Silverlight version resizes the Silverlight control on the web page.

The Silverlight version shows results interactively as they are produced. It allows the run to be paused and continued. It plots the performance of the algorithm.

The command-line version runs multi-core, if available.

The Silverlight control appears in an HTML table and is visable to both IE and Firefox.

The code uses the HashSet data structure. For Silverlight, where HashSet is not available automatically, a mini version is provided.

How to run regression tests

Updated Wiki: False Discovery Rate

guyshani — Fri, 01 May 2009 13:09:59 GMT

!False Discovery Rate for 2X2 Contingency Tables
!!Overview
This tool estimates the False Discovery Rate (FDR) for 2X2 Contingency Tables, based on the Fisher statistics.<br/>
When testing a large number of hypotheses, it can be helpful to
estimate or control the false discovery rate (FDR), the expected
proportion of tests called significant that are truly null. We use Fisher's exact test to calculate the exact null distribution over a set of 2X2 contingency tables.
Using these statistics we compute pooled pvalues, estimate the ratio of true nulls, and compute qvalues.

Updated Wiki: Home

guyshani — Fri, 01 May 2009 13:08:26 GMT

Project Description
Computational biology tools from Microsoft Research's Machine Learning and Applied Statistics group: PhyloD (Phylogeny-Based Association Analysis), Epitope Prediction, HLA Assignment, HLA Completion

The Tools

PhyloD
Pathogens live and reproduce inside the human host, whose immune system continually tries to rid the body of these pathogens. This leads to a tug-of-war between the pathogen and the human host, where the pathogen tries to adapt so as to “escape” the immune system, while the immune system learns to recognize and eliminate new foreign pathogens. A set of key players for the immune system are the HLA proteins, each of which can recognize specific short fragments of foreign (e.g. HIV) proteins, called epitopes, in infected cells and then alert the immune system to their presence. For rapidly evolving pathogens like HIV, a key defense mechanism is to evolve mutations that prevent the HLA proteins from recognizing the viral DNA. This evolution takes place anew in each patient, as each patient has a different set of HLA proteins that recognize different epitopes. PhyloD is a statistical tool that can identify HIV mutations that defeat the function of the HLA proteins in certain patients, thereby allowing the virus to escape elimination by the immune system. By applying this tool to large studies of infected patients, researchers are now able to start decoding the complex rules that govern the HIV mutations, in the hope of one day creating a vaccine to which the virus is unable to develop resistance.

Epitope Prediction
This tool computes the probability that a given kmer is a T-cell epitope restricted to a given HLA allele. The tool can scan for 8, 9, 10, and 11mer epitopes and over all common HLA alleles.

HLA Completion
HLA sequence typing sometimes yields uncertain results. For example, an allele may be identified as A6801/6802 or simply A02. This tool takes as input HLA typing data (loci A,B,C) and probabilistically resolves the typing ambiguities (i.e., probabilistically “completes” the data to 4-digit resolution).

HLA Assignment
One way to find epitopes is to do lab studies such as ELISPOT. One problem with this approach is that, if you see a reaction in a patient, you don’t know which of the patient’s HLA genes is responsible for the reaction. This tool takes lab data from a series of patients and determines (probabilistically) which HLA genes are responsible for the reaction.

Create Epitome
This tool takes, as input, a weighted list of amino acid sequences. It creates epitomes of all lengths.

False Discovery Rate
Estimate the false discovery rate for 2X2 contingency tables, based on Fisher's statistics.

Web Versions of the Tools
http://atom.research.microsoft.com/bio/
http://research.microsoft.com/en-us/um/redmond/projects/MSCompBio/

Pre-Compiled Programs for Windows
http://www.codeplex.com/MSCompBio/Release/ProjectReleases.aspx

Microsoft Research's eScience Research Group

Group web page http://research.microsoft.com/research/eScience/

General Practical Information

Downloading and compiling source code

Why 32-bit

Source code checked in, #27246

guyshani — Thu, 30 Apr 2009 21:47:49 GMT
Adding FalseDiscoveryRate

Source code checked in, #27245

guyshani — Thu, 30 Apr 2009 21:45:12 GMT

Source code checked in, #27244

guyshani — Thu, 30 Apr 2009 21:00:14 GMT

Source code checked in, #27243

guyshani — Thu, 30 Apr 2009 18:41:11 GMT

New Post: Epitome Creator: Silverlight for Science

CarlK — Fri, 14 Nov 2008 01:04:33 GMT

Greetings,

We've release a new biology tool (and web toy). It's "Create Epitome". The web version is http://atom.research.microsoft.com/EpitomeCreator/. It can also be run as an off-line web page (via Silverlight) and a command-line app (via .NET).

Along with using it to create HIV vaccines, you can also play with it as a little web toy. If you paste in

Twinkle, twinkle, little star; How I wonder what you are.

You can watch it build up, one step at a time:

Method

AminoAcidLength

numComponents

coverage

Vaccine

Greedy

7

1

0.3

TWINKLE

Greedy

7

1

0.3

TWINKLE

Greedy

10

2

0.4

TWINKLE,HOW

Greedy

13

2

0.5

WHATWINKLE,HOW

Greedy

12

1

0.5

HOWHATWINKLE

Greedy

15

2

0.6

HOWHATWINKLE,YOU

Greedy

18

3

0.7

HOWHATWINKLE,YOU,ARE

Greedy

20

3

0.8

HOWHATWINKLE,YOU,STARE

Greedy

26

4

0.9

HOWHATWINKLE,YOU,STARE,LITTLE

Greedy

32

5

1

HOWHATWINKLE,YOU,STARE,LITTLE,WONDER

Silverlight is great for this kind of tool because

·         The port from .NET was easy.
·         Processing, which could be long, is on the user's machine not the web server
·         No user data need be transferred to our servers

·         Runs on Windows, Mac, or (soon) Unix
·         Users get rich interaction (including an animated plot) with web-like simplicity.

The .NET command-line version uses the Microsoft Parallel Extensions Library to run muti-core, leading to faster results.

The code is open source and available at:

http://www.codeplex.com/MSCompBio/Wiki/View.aspx?title=Create%20Epitome

Some source code features of possible interest:

·         Builds both Silverlight and .NET command-line versions from the same C# code in the same Visual Studio solution.
·         Includes installer that installs both versions, including setting up the Silverlight page to run off-line.
·         The Silverlight version resizes the Silverlight control on the web page.
·         The Silverlight version shows results interactively as they are produced. It allows the run to be paused and continued. It plots the performance of the algorithm.
·         The Silverlight control appears in an HTML table and is visible to both IE and Firefox.
·         The code uses the HashSet data structure. For Silverlight, where HashSet is not available automatically, a mini version is provided.

-          Carl

Carl Kadie
http://research.microsoft.com/~carlk

Updated Wiki: Create Epitome

CarlK — Mon, 03 Nov 2008 20:50:39 GMT

Create Epitome

"CreateEpitome" is an interactive program (created via Silverlight) and a command-line program for Windows.

Given a weighted set of amino-acid sequences, it creates a new amino-acid sequence that covers input sequences. It works step-by-step, producing an output line after each step. The possible steps include:

Combining two input sequences that overlap
Adding an input sequence to an output component with which it overlap
Combining two output components that overlap

To achieve reasonable efficiency, the program

Works in a heuristic, greedy fashion. It always takes the best next move without considering how that affects future moves.
Keeps up-to-date lists of all candidate moves and their value. When a move is made, it updates the list of candidates efficiently, avoiding complete regeneration.
Command-line version runs on multiple processors, if they are available.

References
D. Yerly, D. Heckerman, T. Allen, T. Suscovich, N. Jojic, C. Kadie, W. Pichler, A. Cerny, C. Brander. Design, expression and processing of epitomized HCV encoded CTL epitopes. J. Immunol, to appear.

D. Nickle, N. Jojic, D. Heckerman, V. Jojic, D. Kirovski, M. Rolland, S. Pond, J. Mullins. Comparison of immunogen designs that optimize peptide coverage: Reply to Fischer et al., PLoS Computational Biology, 4(1):e25, January 2008.

D. Nickle, M. Rolland, M. Jensen, S. Pond, W. Deng, M. Seligman, D. Heckerman, J. Mullins, and N. Jojic. Coping with viral diversity in HIV vaccine design, PLoS Computational Biology, 3(4): e75, April 2007.

N. Jojic, V. Jojic, B. Frey, C. Meek, and D. Heckerman. Using epitomes to model genetic diversity: Rational design of HIV vaccine cocktails. NIPS 2005.

Web Version
http://atom.research.microsoft.com/EpitomeCreator/
Pre-Compiled Programs for Windows

To install the program

Go to http://www.codeplex.com/MSCompBio/Release/ProjectReleases.aspx
Then click "CreateEpitome.msi"

Interactive Version

Run by selecting "Start" and "Create Epitome"

Command-Line Exe's:

How to run CreateEpitome, the command-line exe

Regression test

Source Code Files
(To download see Source Code tab above)

Solution file: CreateEpitome\CreateVaccine\CreateEpitome.sln
Build directory: CreateEpitome\CreateVaccine\CreateEpitome\bin\Release

Compiling the project requires

Visual Studio 2008 SP1
Silverlight Tools for VS 2008 SP1
Microsoft Parallel Extensions to .NET Framework 3.5, June 2008 Community Technology Preview. The Parallel Extensions library enables the program to use multiple processors at the cost of just a few lines of code.

Some source code features of possible interest:

Builds both Silverlight and .NET versions from the same C# code in the same Visual Studio solution.
Includes installer that installs both versions including setting up the Silverlight version to run locally.
The Silverlight version resizes the Silverlight control on the web page.
The Silverlight version shows results interactively as they are produced. It allows the run to be paused and continued. It plots the performance of the algorithm.
The command-line version runs multi-core, if available.
The Silverlight control appears in an HTML table and is visable to both IE and Firefox.
The code uses the HashSet data structure. For Silverlight, where HashSet is not available automatically, a mini version is provided.

How to run regression tests

Updated Wiki: Create Epitome

CarlK — Mon, 03 Nov 2008 20:07:00 GMT

Create Epitome

"CreateEpitome" is an interactive program (created via Silverlight) and a command-line program for Windows.

Given a weighted set of amino-acid sequences, it creates a new amino-acid sequence that covers input sequences. It works step-by-step, producing an output line after each step. The possible steps include:

Combining two input sequences that overlap
Adding an input sequence to an output component with which it overlap
Combining two output components that overlap

To achieve reasonable efficiency, the program

Works in a heuristic, greedy fashion. It always takes the best next move without considering how that affects future moves.
Keeps up-to-date lists of all candidate moves and their value. When a move is made, it updates the list of candidates efficiently, avoiding complete regeneration.
Command-line version runs on multiple processors, if they are available.

References
D. Yerly, D. Heckerman, T. Allen, T. Suscovich, N. Jojic, C. Kadie, W. Pichler, A. Cerny, C. Brander. Design, expression and processing of epitomized HCV encoded CTL epitopes. J. Immunol, to appear.

D. Nickle, N. Jojic, D. Heckerman, V. Jojic, D. Kirovski, M. Rolland, S. Pond, J. Mullins. Comparison of immunogen designs that optimize peptide coverage: Reply to Fischer et al., PLoS Computational Biology, 4(1):e25, January 2008.

D. Nickle, M. Rolland, M. Jensen, S. Pond, W. Deng, M. Seligman, D. Heckerman, J. Mullins, and N. Jojic. Coping with viral diversity in HIV vaccine design, PLoS Computational Biology, 3(4): e75, April 2007.

N. Jojic, V. Jojic, B. Frey, C. Meek, and D. Heckerman. Using epitomes to model genetic diversity: Rational design of HIV vaccine cocktails. NIPS 2005.

Web Version
http://atom.research.microsoft.com/EpitomeCreator/
Pre-Compiled Programs for Windows

To install the program

Go to http://www.codeplex.com/MSCompBio/Release/ProjectReleases.aspx
Then click "CreateEpitome.msi"

Interactive Version

Run by selecting "Start" and "Create Epitome"

Command-Line Exe's:

How to run CreateEpitome, the command-line exe

Regression test

Source Code Files
(To download see Source Code tab above)

Solution file: CreateEpitome\CreateVaccine\CreateEpitome.sln
Build directory: CreateEpitome\CreateVaccine\CreateEpitome\bin\Release

Compiling the project requires

Visual Studio 2008 SP1
Silverlight Tools for VS 2008 SP1
Microsoft Parallel Extensions to .NET Framework 3.5, June 2008 Community Technology Preview. The Parallel Extensions library enables the program to use multiple processors at the cost of just a few lines of code.

Some source code features of possible interest:

Builds both Silverlight and .NET versions from the same C# code in the same Visual Studio solution.
Includes installer that installs both versions including setting up the Silverlight version to run locally.
The Silverlight version resizes the Silverlight control on the web page.
The Silverlight version shows results interactively as they are produced. It allows the run to be paused and continued. It plots the performance of the algorithm.
The command-line version runs multi-core, if available.
The Silverlight control appears in an HTML table and is visable to both IE and Firefox.
The code uses the HashSet data structure. For Silverlight, where HashSet is not available automatically, a mini version is provided.

How to run regression tests

Updated Wiki: Create Epitome

CarlK — Mon, 03 Nov 2008 16:29:19 GMT

Create Epitome

"CreateEpitome" is an interactive program (created via Silverlight) and a command-line program for Windows.

Given a weighted set of amino-acid sequences, it creates a new amino-acid sequence that covers input sequences. It works step-by-step, producing an output line after each step. The possible steps include:

Combining two input sequences that overlap
Adding an input sequence to an output component with which it overlap
Combining two output components that overlap

To achieve reasonable efficiency, the program

Works in a heuristic, greedy fashion. It always takes the best next move without considering how that affects future moves.
Keeps up-to-date lists of all candidate moves and their value. When a move is made, it updates the list of candidates efficiently, avoiding complete regeneration.
Command-line version runs on multiple processors, if they are available.

References
D. Yerly, D. Heckerman, T. Allen, T. Suscovich, N. Jojic, C. Kadie, W. Pichler, A. Cerny, C. Brander. Design, expression and processing of epitomized HCV encoded CTL epitopes. J. Immunol, to appear.

D. Nickle, N. Jojic, D. Heckerman, V. Jojic, D. Kirovski, M. Rolland, S. Pond, J. Mullins. Comparison of immunogen designs that optimize peptide coverage: Reply to Fischer et al., PLoS Computational Biology, 4(1):e25, January 2008.

D. Nickle, M. Rolland, M. Jensen, S. Pond, W. Deng, M. Seligman, D. Heckerman, J. Mullins, and N. Jojic. Coping with viral diversity in HIV vaccine design, PLoS Computational Biology, 3(4): e75, April 2007.

N. Jojic, V. Jojic, B. Frey, C. Meek, and D. Heckerman. Using epitomes to model genetic diversity: Rational design of HIV vaccine cocktails. NIPS 2005.

Web Version
http://atom.research.microsoft.com/EpitomeCreator/
Pre-Compiled Programs for Windows

To install the program

Go to http://www.codeplex.com/MSCompBio/Release/ProjectReleases.aspx
Then click "CreateEpitome.msi"

Interactive Version

Run by selecting "Start" and "Create Epitome"

Command-Line Exe's:

How to run CreateEpitome, the command-line exe

Regression test

Source Code Files
(To download see Source Code tab above)

Solution file: CreateEpitome\CreateVaccine\CreateEpitome.sln
Build directory: CreateEpitome\CreateVaccine\CreateEpitome\bin\Release

Compiling the project requires

Visual Studio 2008 SP1
Silverlight Tools for VS 2008 SP1
Microsoft Parallel Extensions to .NET Framework 3.5, June 2008 Community Technology Preview. The Parallel Extensions library enables the program to use multiple processors at the cost of just a few lines of code.

Some source code features of possible interest:

Builds both Silverlight and .NET versions from the same C# code in the same Visual Studio solution.
Includes installer that installs both versions including setting up the Silverlight version to run locally.
Includes project for the Silverlight's two-page web site.
The Silverlight version resizes the Silverlight control on the web page.
The Silverlight version shows results interactively as they are produced. It allows the run to be paused and continued. It plots the performance of the algorithm.
The command-line version runs multi-core, if available.
The Silverlight control appears in an HTML table and is visable to both IE and Firefox.
The code uses the HashSet data structure. For Silverlight, where HashSet is not available automatically, a mini version is provided.

How to run regression tests

Updated Wiki: Create Epitome

CarlK — Mon, 03 Nov 2008 15:37:18 GMT

Create Epitome

"CreateEpitome" is an interactive program (created via Silverlight) and a command-line program for Windows.

Given a weighted set of amino-acid sequences, it creates a new amino-acid sequence that covers input sequences. It works step-by-step, producing an output line after each step. The possible steps include:

Combining two input sequences that overlap
Adding an input sequence to an output component with which it overlap
Combining two output components that overlap

To achieve reasonable efficiency, the program

Works in a heuristic, greedy fashion. It always takes the best next move without considering how that affects future moves.
Keeps up-to-date lists of all candidate moves and their value. When a move is made, it updates the list of candidates efficiently, avoiding complete regeneration.
Command-line version runs on multiple processors, if they are available.

References
D. Yerly, D. Heckerman, T. Allen, T. Suscovich, N. Jojic, C. Kadie, W. Pichler, A. Cerny, C. Brander. Design, expression and processing of epitomized HCV encoded CTL epitopes. J. Immunol, to appear.

D. Nickle, N. Jojic, D. Heckerman, V. Jojic, D. Kirovski, M. Rolland, S. Pond, J. Mullins. Comparison of immunogen designs that optimize peptide coverage: Reply to Fischer et al., PLoS Computational Biology, 4(1):e25, January 2008.

D. Nickle, M. Rolland, M. Jensen, S. Pond, W. Deng, M. Seligman, D. Heckerman, J. Mullins, and N. Jojic. Coping with viral diversity in HIV vaccine design, PLoS Computational Biology, 3(4): e75, April 2007.

N. Jojic, V. Jojic, B. Frey, C. Meek, and D. Heckerman. Using epitomes to model genetic diversity: Rational design of HIV vaccine cocktails. NIPS 2005.

Web Version
http://atom.research.microsoft.com/EpitomeCreator/
Pre-Compiled Programs for Windows

To install the program

Go to http://www.codeplex.com/MSCompBio/Release/ProjectReleases.aspx
Then click "CreateEpitome.msi"

Interactive Version

Run by selecting "Start" and "Create Epitome"

Command-Line Exe's:

How to run CreateEpitome, the command-line exe

Regression test

Source Code Files
(To download see Source Code tab above)

Solution file: CreateEpitome\CreateVaccine\CreateEpitome.sln
Build directory: CreateEpitome\CreateVaccine\CreateEpitome\bin\Release

Compiling the project requires

Visual Studio 2008 SP1
Silverlight Tools for VS 2008 SP1
Microsoft Parallel Extensions to .NET Framework 3.5, June 2008 Community Technology Preview. The Parallel Extensions library enables the program to use multiple processors at the cost of just a few lines of code.

Some source code features of possible interest:

Builds both Silverlight and .NET versions from the same C# code in the same Visual Studio solution.
Includes installer that installs both versions including setting up the Silverlight version to run locally.
Includes project for the Silverlight's two-page web site.
The Silverlight version resizes the Silverlight control on the web page.
The Silverlight version shows results interactively as they are produced. It allows the run to be paused and continued. It plots the performance of the algorithm.
The command-line version runs multi-core, if available.
The Silverlight control appears in a HTML table and is visable to both IE and Firefox.

How to run regression tests

Method	AminoAcidLength	numComponents	coverage	Vaccine
Greedy	7	1	0.3	TWINKLE
Greedy	7	1	0.3	TWINKLE
Greedy	10	2	0.4	TWINKLE,HOW
Greedy	13	2	0.5	WHATWINKLE,HOW
Greedy	12	1	0.5	HOWHATWINKLE
Greedy	15	2	0.6	HOWHATWINKLE,YOU
Greedy	18	3	0.7	HOWHATWINKLE,YOU,ARE
Greedy	20	3	0.8	HOWHATWINKLE,YOU,STARE
Greedy	26	4	0.9	HOWHATWINKLE,YOU,STARE,LITTLE
Greedy	32	5	1	HOWHATWINKLE,YOU,STARE,LITTLE,WONDER