<?xml version="1.0" encoding="utf-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Recent changes to Home</title><link>https://sourceforge.net/p/lmat/wiki/Home/</link><description>Recent changes to Home</description><atom:link href="https://sourceforge.net/p/lmat/wiki/Home/feed" rel="self"/><language>en</language><lastBuildDate>Tue, 27 Feb 2018 06:25:00 -0000</lastBuildDate><atom:link href="https://sourceforge.net/p/lmat/wiki/Home/feed" rel="self" type="application/rss+xml"/><item><title>Home modified by Jonathan</title><link>https://sourceforge.net/p/lmat/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;--- v5
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+UPDATE: Please visit https://github.com/LivGen/LMAT for updated code.  Code on Sourceforge site may not compile on newer Linux systems.
+
+
+
 Welcome to the Livermore Metagenomics Analysis Toolkit (LMAT) wiki on SourceForge. This wiki was set up to share ongoing developments of the software and support community development interest for the software as an open source resource (GNU GPL) freely available to anyone working on problems in metagenomics. LMAT is a collection of software tools primarily written in C++, which are designed to efficiently analyze very large shotgun metagenomic datasets for taxonomic and gene function content. The primary initial innovation is to apply pre-computed genome index files tagged with taxonomy data, which are stored in a memory mapped file for fast read-only lookups. The result is the capability to search a large genome database of virus, bacteria, archaea, protozoa, fungal and human (and potentially others) and rapidly determine the contents of very large datasets (e.g. many tens to hundreds of gigabases or more in size). The unique feature of the approach is to rely on commodity hardware that supports a fast interconnect between the computer's CPU, DRAM and local storage and make extensive use of multi-core processing. The approach operates in contrast to traditional clusters where analysis is distributed to multiple nodes across a network. Thus, the model presented here is to maintain an analysis capability that can be co-located with the sequencer. LMAT offers the most complete microbial database publicly available (to our knowledge)  for metagenomic analysis.  The database includes the complete and assembled draft genomes for viruses, bacteria, archaea, fungi and protozoa, human reference assemblies and an extensive collection of genetic data from the 1000 genomes project.

 Work applying three primary configurations is under way:
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&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">Jonathan</dc:creator><pubDate>Tue, 27 Feb 2018 06:25:00 -0000</pubDate><guid>https://sourceforge.net8d700635bbe74f79c61b1f9816c37fa2fd325276</guid></item><item><title>Home modified by Jonathan</title><link>https://sourceforge.net/p/lmat/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;--- v4
+++ v5
@@ -1,4 +1,4 @@
-Welcome to the Livermore Metagenomics Analysis Toolkit (LMAT) wiki on SourceForge. This wiki was set up to share ongoing developments of the software and support community development interest for the software as an open source resource (GNU GPL) freely available to anyone working on problems in metagenomics. LMAT is a collection of software tools primarily written in C++, which are designed to efficiently analyze very large shotgun metagenomic datasets for taxonomic and gene function content. The primary initial innovation is to apply pre-computed genome index files tagged with taxonomy data, which are stored in a memory mapped file for fast read-only lookups. The result is the capability to search a large genome database of virus, bacteria, archaea, protozoa, fungal and human (and potentially others) and rapidly determine the contents of very large datasets (e.g. many tens to hundreds of gigabases or more in size). The unique feature of the approach is to rely on commodity hardware that supports a fast interconnect between the computer's CPU, DRAM and local storage and make extensive use of multi-core processing. The approach operates in contrast to traditional clusters where analysis is distributed to multiple nodes across a network. Thus, the model presented here is to maintain an analysis capability that can be co-located with the sequencer. LMAT offers the most complete microbial database publicly available (to our knowledge)  for metagenomic analysis.  The database includes the complete and assembled draft genomes for viruses, bacteria, archaea, fungi and protozoa, and several human assemblies. 
+Welcome to the Livermore Metagenomics Analysis Toolkit (LMAT) wiki on SourceForge. This wiki was set up to share ongoing developments of the software and support community development interest for the software as an open source resource (GNU GPL) freely available to anyone working on problems in metagenomics. LMAT is a collection of software tools primarily written in C++, which are designed to efficiently analyze very large shotgun metagenomic datasets for taxonomic and gene function content. The primary initial innovation is to apply pre-computed genome index files tagged with taxonomy data, which are stored in a memory mapped file for fast read-only lookups. The result is the capability to search a large genome database of virus, bacteria, archaea, protozoa, fungal and human (and potentially others) and rapidly determine the contents of very large datasets (e.g. many tens to hundreds of gigabases or more in size). The unique feature of the approach is to rely on commodity hardware that supports a fast interconnect between the computer's CPU, DRAM and local storage and make extensive use of multi-core processing. The approach operates in contrast to traditional clusters where analysis is distributed to multiple nodes across a network. Thus, the model presented here is to maintain an analysis capability that can be co-located with the sequencer. LMAT offers the most complete microbial database publicly available (to our knowledge)  for metagenomic analysis.  The database includes the complete and assembled draft genomes for viruses, bacteria, archaea, fungi and protozoa, human reference assemblies and an extensive collection of genetic data from the 1000 genomes project.

 Work applying three primary configurations is under way:

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&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">Jonathan</dc:creator><pubDate>Tue, 24 Mar 2015 18:25:37 -0000</pubDate><guid>https://sourceforge.neteb1f04ca030963490ecdb8ebff84e196c1580342</guid></item><item><title>Home modified by Sasha</title><link>https://sourceforge.net/p/lmat/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;--- v3
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 * Use of flash drives (NVRAM) as a proxy for DRAM to further support use of low cost commodity hardware alternatives (and could support alternative high memory low cost cluster based tools).

 [What's New]
+[Example LMAT Run]
&lt;/pre&gt;
&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">Sasha</dc:creator><pubDate>Thu, 15 May 2014 22:25:22 -0000</pubDate><guid>https://sourceforge.net05ae0ca46a2ecfd212a2921df66762f729b366ae</guid></item><item><title>Home modified by Sasha</title><link>https://sourceforge.net/p/lmat/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;--- v2
+++ v3
@@ -6,4 +6,4 @@
 * Reduced size databases, which support search tools that give a quick summary of sample contents and have smaller memory requirements (&lt; 64 GB).
 * Use of flash drives (NVRAM) as a proxy for DRAM to further support use of low cost commodity hardware alternatives (and could support alternative high memory low cost cluster based tools).

-[Whats New]
+[What's New]
&lt;/pre&gt;
&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">Sasha</dc:creator><pubDate>Wed, 07 May 2014 16:23:54 -0000</pubDate><guid>https://sourceforge.netc0fc598403f9763d326a31a622e7d808e8912b49</guid></item><item><title>Home modified by Sasha</title><link>https://sourceforge.net/p/lmat/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;pre&gt;--- v1
+++ v2
@@ -1,8 +1,9 @@
-Welcome to your wiki!
+Welcome to the Livermore Metagenomics Analysis Toolkit (LMAT) wiki on SourceForge. This wiki was set up to share ongoing developments of the software and support community development interest for the software as an open source resource (GNU GPL) freely available to anyone working on problems in metagenomics. LMAT is a collection of software tools primarily written in C++, which are designed to efficiently analyze very large shotgun metagenomic datasets for taxonomic and gene function content. The primary initial innovation is to apply pre-computed genome index files tagged with taxonomy data, which are stored in a memory mapped file for fast read-only lookups. The result is the capability to search a large genome database of virus, bacteria, archaea, protozoa, fungal and human (and potentially others) and rapidly determine the contents of very large datasets (e.g. many tens to hundreds of gigabases or more in size). The unique feature of the approach is to rely on commodity hardware that supports a fast interconnect between the computer's CPU, DRAM and local storage and make extensive use of multi-core processing. The approach operates in contrast to traditional clusters where analysis is distributed to multiple nodes across a network. Thus, the model presented here is to maintain an analysis capability that can be co-located with the sequencer. LMAT offers the most complete microbial database publicly available (to our knowledge)  for metagenomic analysis.  The database includes the complete and assembled draft genomes for viruses, bacteria, archaea, fungi and protozoa, and several human assemblies.

-This is the default page, edit it as you see fit. To add a new page simply reference it within brackets, e.g.: [SamplePage].
+Work applying three primary configurations is under way:

-The wiki uses [Markdown](/p/lmat/wiki/markdown_syntax/) syntax.
+1. Use of single large (e.g. 512GB-1TB) DRAM multi-core node, which can process large amounts of data extremely quickly.
+* Reduced size databases, which support search tools that give a quick summary of sample contents and have smaller memory requirements (&lt; 64 GB).
+* Use of flash drives (NVRAM) as a proxy for DRAM to further support use of low cost commodity hardware alternatives (and could support alternative high memory low cost cluster based tools).

-[[project_admins]]
-[[download_button]]
+[Whats New]
&lt;/pre&gt;
&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">Sasha</dc:creator><pubDate>Wed, 07 May 2014 16:23:16 -0000</pubDate><guid>https://sourceforge.netaceeb9c754bd334ba47b6b117242e3b39c73e361</guid></item><item><title>WikiPage Home modified by David Hysom</title><link>https://sourceforge.net/p/lmat/wiki/Home/</link><description>&lt;div class="markdown_content"&gt;&lt;p&gt;Welcome to your wiki!&lt;/p&gt;
&lt;p&gt;This is the default page, edit it as you see fit. To add a new page simply reference it within brackets, e.g.: &lt;a class="alink" href="SamplePage"&gt;[SamplePage]&lt;/a&gt;.&lt;/p&gt;
&lt;p&gt;The wiki uses &lt;a class="" href="/p/lmat/wiki/markdown_syntax/"&gt;Markdown&lt;/a&gt; syntax.&lt;/p&gt;
&lt;p&gt;&lt;a href="/u/dhysom42/"&gt;David Hysom&lt;/a&gt;&lt;br /&gt;&lt;br /&gt;
&lt;span class="download-button-50d1167ab9363c080dac19eb" style="margin-bottom: 1em; display: block;"&gt;&lt;/span&gt;&lt;/p&gt;&lt;/div&gt;</description><dc:creator xmlns:dc="http://purl.org/dc/elements/1.1/">David Hysom</dc:creator><pubDate>Wed, 19 Dec 2012 01:20:58 -0000</pubDate><guid>https://sourceforge.net9ce627003ee8daba27d1fbb9869fd884819cd2ac</guid></item></channel></rss>