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Home modified by Yao Haobin

Yao Haobin — Sat, 27 Aug 2016 01:52:42 -0000

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 Taxonomic annotation is a critical first step for analysis of metagenomic data. Despite a lot of tools being developed, the performance (both running time and accuracy) is still not satisfactory, in particular, when a close species-level reference does not exist in the database. In this paper, we propose a novel annotation tool, MetaAnnotator, to annotate metagenomics reads which outperforms all existing tools significantly when only genus-level references exist in the database. In particular, from our experiments, MetaAnnotator can assign 87.5% reads correctly (67.5% reads are assigned to the exact genus) with only 8.5% reads wrongly assigned. The best existing tool (MetaCluster-TA) can only achieve 73.4% correct read assignment (with only 50.9% reads assigned to the exact genus and 22.6% reads wrongly assigned). The speed of MetaAnnotator is also the second faster (1 hour for 20 million reads). The core concepts behind MetaAnnotator includes (i) we only consider exact k-mer matches in coding regions of the references as they should be more significant and ac-curate; and (ii) to assign reads to taxonomy nodes, we construct genome and taxonomy specific probabilistic models from reference database; and (iii) with BWT data structure to speed up the k-mer matching.

-The software is implemented with c++. For usage, please refer to "readme" file in released version 1.0.
+The software is implemented with c++. Currently it supports annotation of Bacteria genome. For usage, please refer to "readme" file in released version 1.0.

Home modified by Yao Haobin

Yao Haobin — Fri, 26 Aug 2016 12:58:19 -0000

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 Taxonomic annotation is a critical first step for analysis of metagenomic data. Despite a lot of tools being developed, the performance (both running time and accuracy) is still not satisfactory, in particular, when a close species-level reference does not exist in the database. In this paper, we propose a novel annotation tool, MetaAnnotator, to annotate metagenomics reads which outperforms all existing tools significantly when only genus-level references exist in the database. In particular, from our experiments, MetaAnnotator can assign 87.5% reads correctly (67.5% reads are assigned to the exact genus) with only 8.5% reads wrongly assigned. The best existing tool (MetaCluster-TA) can only achieve 73.4% correct read assignment (with only 50.9% reads assigned to the exact genus and 22.6% reads wrongly assigned). The speed of MetaAnnotator is also the second faster (1 hour for 20 million reads). The core concepts behind MetaAnnotator includes (i) we only consider exact k-mer matches in coding regions of the references as they should be more significant and ac-curate; and (ii) to assign reads to taxonomy nodes, we construct genome and taxonomy specific probabilistic models from reference database; and (iii) with BWT data structure to speed up the k-mer matching.
+
+The software is implemented with c++. For usage, please refer to "readme" file in released version 1.0.

Home modified by Yao Haobin

Yao Haobin — Tue, 23 Aug 2016 05:07:35 -0000

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-Taxonomic annotation is a critical first step for analysis of metagenomic data. Despite a lot of tools being developed, the performance (both running time and accuracy) is still not satisfactory, in particular, when a close species-level reference does not exist in the database. In this paper, we propose a novel annotation tool, MetaAnnotator, to annotate metagenomics reads which outperforms all existing tools significantly when only genus-level references exist in the database. In particular, from our experiments, MetaAnnotator can assign 87.5% reads correctly (67.5% reads are assigned to the exact genus) with only 8.5% reads wrongly assigned. The best existing tool (MetaCluster-TA) can only achieve 73.4% correct read assignment (with only 50.9% reads assigned to the exact genus and 22.6% reads wrongly assigned). The speed of MetaAnnotator is also the second faster (1 hour for 20 million reads). The core concepts behind MetaAnnotator includes (i) we only consider exact k-mer matches in coding regions of the references as they should be more significant and ac-curate; and (ii) to assign reads to taxonomy nodes, we construct genome and taxonomy specific probabilistic models from reference database; and (iii) with BWT data structure to speed up the k-mer matching.: [SamplePage].
+Taxonomic annotation is a critical first step for analysis of metagenomic data. Despite a lot of tools being developed, the performance (both running time and accuracy) is still not satisfactory, in particular, when a close species-level reference does not exist in the database. In this paper, we propose a novel annotation tool, MetaAnnotator, to annotate metagenomics reads which outperforms all existing tools significantly when only genus-level references exist in the database. In particular, from our experiments, MetaAnnotator can assign 87.5% reads correctly (67.5% reads are assigned to the exact genus) with only 8.5% reads wrongly assigned. The best existing tool (MetaCluster-TA) can only achieve 73.4% correct read assignment (with only 50.9% reads assigned to the exact genus and 22.6% reads wrongly assigned). The speed of MetaAnnotator is also the second faster (1 hour for 20 million reads). The core concepts behind MetaAnnotator includes (i) we only consider exact k-mer matches in coding regions of the references as they should be more significant and ac-curate; and (ii) to assign reads to taxonomy nodes, we construct genome and taxonomy specific probabilistic models from reference database; and (iii) with BWT data structure to speed up the k-mer matching.

Home modified by Yao Haobin

Yao Haobin — Tue, 23 Aug 2016 05:07:05 -0000

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-Welcome to your wiki!
+Taxonomic annotation is a critical first step for analysis of metagenomic data. Despite a lot of tools being developed, the performance (both running time and accuracy) is still not satisfactory, in particular, when a close species-level reference does not exist in the database. In this paper, we propose a novel annotation tool, MetaAnnotator, to annotate metagenomics reads which outperforms all existing tools significantly when only genus-level references exist in the database. In particular, from our experiments, MetaAnnotator can assign 87.5% reads correctly (67.5% reads are assigned to the exact genus) with only 8.5% reads wrongly assigned. The best existing tool (MetaCluster-TA) can only achieve 73.4% correct read assignment (with only 50.9% reads assigned to the exact genus and 22.6% reads wrongly assigned). The speed of MetaAnnotator is also the second faster (1 hour for 20 million reads). The core concepts behind MetaAnnotator includes (i) we only consider exact k-mer matches in coding regions of the references as they should be more significant and ac-curate; and (ii) to assign reads to taxonomy nodes, we construct genome and taxonomy specific probabilistic models from reference database; and (iii) with BWT data structure to speed up the k-mer matching.: [SamplePage].

-This is the default page, edit it as you see fit. To add a new page simply reference it within brackets, e.g.: [SamplePage].

-The wiki uses [Markdown](/p/metaannotator/wiki/markdown_syntax/) syntax.

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Home modified by Yao Haobin

Yao Haobin — Tue, 23 Aug 2016 01:32:51 -0000

Welcome to your wiki!

This is the default page, edit it as you see fit. To add a new page simply reference it within brackets, e.g.: [SamplePage].

The wiki uses Markdown syntax.

Project Members:

Yao Haobin (admin)