TACOA – Taxonomic classification of environmental genomic fragments using a kernelized nearest neighbor approach

doi:10.1186/1471-2105-10-56

BMC Bioinformatics

Volume 10

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Methodology article

TACOA – Taxonomic classification of environmental genomic fragments using a kernelized nearest neighbor approach

Naryttza N Diaz¹^,2 , Lutz Krause⁵ , Alexander Goesmann¹^,4 , Karsten Niehaus³ and Tim W Nattkemper²

¹Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany

²Biodata Mining & Applied Neuroinformatics Group, Faculty of Technology, Bielefeld University, Bielefeld, Germany

³Proteome and Metabolome Research, Faculty of Biology, Bielefeld University, Bielefeld, Germany

⁴Computational Genomics, Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany

⁵Nestlé Research Center, BioAnalytical Science Department, Lausanne, Switzerland

author email corresponding author email

BMC Bioinformatics 2009, 10:56doi:10.1186/1471-2105-10-56


Published:	11 February 2009

Additional files

Additional file 1:

Oligonucleotide length-dependent performance for two different genomic fragment length. Achieved specificity (left), sensitivity (middle) and false negative rate (right) for different oligonucleotide lengths in genomic fragments of length 800 bp (a) and 50 Kbp (b). For clarity the standard deviation was not depicted in these figures, instead is given as Additional file 2.

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Additional file 2:

Standard deviation for average accuracy and false negative rate achieved for different oligonucleotide lengths. Standard deviation and average specificity, sensitivity and false negative rate is given for all oligonucleotide lengths and taxonomic ranks evaluated.

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Additional file 3:

Fragment-length and rank dependent performance. Sensitivity (left) and specificity (right) achieved by TACOA for each genomic fragment length and taxonomic rank evaluated. Single read lengths are simulated by fragments 800 bp and 1 Kbp long and contigs by fragment lengths between 3 Kbp and 50 Kbp.

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Additional file 4:

Classification accuracy achieved using two different reference sets. Each colored bar depicts the accuracy achieved by TACOA with two different reference sets. The label "Taxonomic organism of test fragment absent from reference set" refers when the test fragment is classified using a reference set not containing the source organism from which the test fragment originates from.

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Additional file 5:

Intervals for specificity (left) and sensitivity (right) of predicted taxonomic classes for reads. Classification accuracy intervals for genomic fragments of length 800 bp (top) and 1 Kbp (bottom).

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Additional file 6:

Intervals for specificity (left) and sensitivity (right) of predicted taxonomic classes for contigs. Classification accuracy intervals for genomic fragments of length 3 Kbp, 10 Kbp, 15 Kbp, and 50 Kbp (from top to bottom).

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Additional file 7:

Detailed accuracy obtained for genomic fragments of length 800 bp using TACOA and PhyloPythia classifiers. At each taxonomic rank, the classification accuracy (specificity and sensitivity) achieved for two different intrinsic classifiers: TACOA and PhyloPythia is given. The symbol (-) refers to the cases where the respective value cannot be mathematically defined.

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Additional file 8:

Detailed accuracy obtained for genomic fragments of length 1 Kbp using TACOA and PhyloPythia classifiers. At each taxonomic rank, the classification accuracy (specificity and sensitivity) achieved for two different intrinsic classifiers: TACOA and PhyloPythia is given. The symbol (-) refers to the cases where the respective value cannot be mathematically defined.

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Additional file 9:

Detailed accuracy obtained for genomic fragments of length 10 Kbp using TACOA and PhyloPythia classifiers. At each taxonomic rank, the classification accuracy (specificity and sensitivity) achieved for two different intrinsic classifiers: TACOA and PhyloPythia is given. The symbol (-) refers to the cases where the respective value cannot be mathematically defined.

Format: PDF Size: 38KB Download file

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