Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions

Abstract The simultaneous testing of a large number of hypotheses in a genome scan, using individual thresholds for significance, inherently leads to inflated genome-wide false positive rates. There exist various approaches to approximating the correct genomewide p-values under various assumptions,...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Sinha, Ritwik [verfasserIn] Sinha, Moumita Mathew, George Elston, Robert C Luo, Yuqun

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2005

Schlagwörter:	Mixture Distribution True Region Natural Spline Major Gene Effect Local False Discovery Rate

Anmerkung:	© Sinha et al; licensee BioMed Central Ltd 2005. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (

Übergeordnetes Werk:	Enthalten in: BMC genetics - London : BioMed Central, 2000, 6(2005), Suppl 1 vom: 30. Dez.
Übergeordnetes Werk:	volume:6 ; year:2005 ; number:Suppl 1 ; day:30 ; month:12

Links:	Volltext

DOI / URN:	10.1186/1471-2156-6-S1-S23

Katalog-ID:	SPR027000559

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allfields	10.1186/1471-2156-6-S1-S23 doi (DE-627)SPR027000559 (SPR)1471-2156-6-S1-S23-e DE-627 ger DE-627 rakwb eng Sinha, Ritwik verfasserin aut Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Sinha et al; licensee BioMed Central Ltd 2005. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Abstract The simultaneous testing of a large number of hypotheses in a genome scan, using individual thresholds for significance, inherently leads to inflated genome-wide false positive rates. There exist various approaches to approximating the correct genomewide p-values under various assumptions, either by way of asymptotics or simulations. We explore a philosophically different criterion, recently proposed in the literature, which controls the false discovery rate. The test statistics are assumed to arise from a mixture of distributions under the null and non-null hypotheses. We fit the mixture distribution using both a nonparametric approach and commingling analysis, and then apply the local false discovery rate to select cut-off points for regions to be declared interesting. Another criterion, the minimum total error, is also explored. Both criteria seem to be sensible alternatives to controlling the classical type I and type II error rates. Mixture Distribution (dpeaa)DE-He213 True Region (dpeaa)DE-He213 Natural Spline (dpeaa)DE-He213 Major Gene Effect (dpeaa)DE-He213 Local False Discovery Rate (dpeaa)DE-He213 Sinha, Moumita aut Mathew, George aut Elston, Robert C aut Luo, Yuqun aut Enthalten in BMC genetics London : BioMed Central, 2000 6(2005), Suppl 1 vom: 30. Dez. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:6 year:2005 number:Suppl 1 day:30 month:12 https://dx.doi.org/10.1186/1471-2156-6-S1-S23 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2005 Suppl 1 30 12
spelling	10.1186/1471-2156-6-S1-S23 doi (DE-627)SPR027000559 (SPR)1471-2156-6-S1-S23-e DE-627 ger DE-627 rakwb eng Sinha, Ritwik verfasserin aut Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Sinha et al; licensee BioMed Central Ltd 2005. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Abstract The simultaneous testing of a large number of hypotheses in a genome scan, using individual thresholds for significance, inherently leads to inflated genome-wide false positive rates. There exist various approaches to approximating the correct genomewide p-values under various assumptions, either by way of asymptotics or simulations. We explore a philosophically different criterion, recently proposed in the literature, which controls the false discovery rate. The test statistics are assumed to arise from a mixture of distributions under the null and non-null hypotheses. We fit the mixture distribution using both a nonparametric approach and commingling analysis, and then apply the local false discovery rate to select cut-off points for regions to be declared interesting. Another criterion, the minimum total error, is also explored. Both criteria seem to be sensible alternatives to controlling the classical type I and type II error rates. Mixture Distribution (dpeaa)DE-He213 True Region (dpeaa)DE-He213 Natural Spline (dpeaa)DE-He213 Major Gene Effect (dpeaa)DE-He213 Local False Discovery Rate (dpeaa)DE-He213 Sinha, Moumita aut Mathew, George aut Elston, Robert C aut Luo, Yuqun aut Enthalten in BMC genetics London : BioMed Central, 2000 6(2005), Suppl 1 vom: 30. Dez. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:6 year:2005 number:Suppl 1 day:30 month:12 https://dx.doi.org/10.1186/1471-2156-6-S1-S23 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2005 Suppl 1 30 12
allfields_unstemmed	10.1186/1471-2156-6-S1-S23 doi (DE-627)SPR027000559 (SPR)1471-2156-6-S1-S23-e DE-627 ger DE-627 rakwb eng Sinha, Ritwik verfasserin aut Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Sinha et al; licensee BioMed Central Ltd 2005. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Abstract The simultaneous testing of a large number of hypotheses in a genome scan, using individual thresholds for significance, inherently leads to inflated genome-wide false positive rates. There exist various approaches to approximating the correct genomewide p-values under various assumptions, either by way of asymptotics or simulations. We explore a philosophically different criterion, recently proposed in the literature, which controls the false discovery rate. The test statistics are assumed to arise from a mixture of distributions under the null and non-null hypotheses. We fit the mixture distribution using both a nonparametric approach and commingling analysis, and then apply the local false discovery rate to select cut-off points for regions to be declared interesting. Another criterion, the minimum total error, is also explored. Both criteria seem to be sensible alternatives to controlling the classical type I and type II error rates. Mixture Distribution (dpeaa)DE-He213 True Region (dpeaa)DE-He213 Natural Spline (dpeaa)DE-He213 Major Gene Effect (dpeaa)DE-He213 Local False Discovery Rate (dpeaa)DE-He213 Sinha, Moumita aut Mathew, George aut Elston, Robert C aut Luo, Yuqun aut Enthalten in BMC genetics London : BioMed Central, 2000 6(2005), Suppl 1 vom: 30. Dez. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:6 year:2005 number:Suppl 1 day:30 month:12 https://dx.doi.org/10.1186/1471-2156-6-S1-S23 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2005 Suppl 1 30 12
allfieldsGer	10.1186/1471-2156-6-S1-S23 doi (DE-627)SPR027000559 (SPR)1471-2156-6-S1-S23-e DE-627 ger DE-627 rakwb eng Sinha, Ritwik verfasserin aut Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Sinha et al; licensee BioMed Central Ltd 2005. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Abstract The simultaneous testing of a large number of hypotheses in a genome scan, using individual thresholds for significance, inherently leads to inflated genome-wide false positive rates. There exist various approaches to approximating the correct genomewide p-values under various assumptions, either by way of asymptotics or simulations. We explore a philosophically different criterion, recently proposed in the literature, which controls the false discovery rate. The test statistics are assumed to arise from a mixture of distributions under the null and non-null hypotheses. We fit the mixture distribution using both a nonparametric approach and commingling analysis, and then apply the local false discovery rate to select cut-off points for regions to be declared interesting. Another criterion, the minimum total error, is also explored. Both criteria seem to be sensible alternatives to controlling the classical type I and type II error rates. Mixture Distribution (dpeaa)DE-He213 True Region (dpeaa)DE-He213 Natural Spline (dpeaa)DE-He213 Major Gene Effect (dpeaa)DE-He213 Local False Discovery Rate (dpeaa)DE-He213 Sinha, Moumita aut Mathew, George aut Elston, Robert C aut Luo, Yuqun aut Enthalten in BMC genetics London : BioMed Central, 2000 6(2005), Suppl 1 vom: 30. Dez. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:6 year:2005 number:Suppl 1 day:30 month:12 https://dx.doi.org/10.1186/1471-2156-6-S1-S23 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2005 Suppl 1 30 12
allfieldsSound	10.1186/1471-2156-6-S1-S23 doi (DE-627)SPR027000559 (SPR)1471-2156-6-S1-S23-e DE-627 ger DE-627 rakwb eng Sinha, Ritwik verfasserin aut Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions 2005 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Sinha et al; licensee BioMed Central Ltd 2005. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License ( Abstract The simultaneous testing of a large number of hypotheses in a genome scan, using individual thresholds for significance, inherently leads to inflated genome-wide false positive rates. There exist various approaches to approximating the correct genomewide p-values under various assumptions, either by way of asymptotics or simulations. We explore a philosophically different criterion, recently proposed in the literature, which controls the false discovery rate. The test statistics are assumed to arise from a mixture of distributions under the null and non-null hypotheses. We fit the mixture distribution using both a nonparametric approach and commingling analysis, and then apply the local false discovery rate to select cut-off points for regions to be declared interesting. Another criterion, the minimum total error, is also explored. Both criteria seem to be sensible alternatives to controlling the classical type I and type II error rates. Mixture Distribution (dpeaa)DE-He213 True Region (dpeaa)DE-He213 Natural Spline (dpeaa)DE-He213 Major Gene Effect (dpeaa)DE-He213 Local False Discovery Rate (dpeaa)DE-He213 Sinha, Moumita aut Mathew, George aut Elston, Robert C aut Luo, Yuqun aut Enthalten in BMC genetics London : BioMed Central, 2000 6(2005), Suppl 1 vom: 30. Dez. (DE-627)326644938 (DE-600)2041497-3 1471-2156 nnns volume:6 year:2005 number:Suppl 1 day:30 month:12 https://dx.doi.org/10.1186/1471-2156-6-S1-S23 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 6 2005 Suppl 1 30 12
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spellingShingle	Sinha, Ritwik misc Mixture Distribution misc True Region misc Natural Spline misc Major Gene Effect misc Local False Discovery Rate Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions
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topic_title	Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions Mixture Distribution (dpeaa)DE-He213 True Region (dpeaa)DE-He213 Natural Spline (dpeaa)DE-He213 Major Gene Effect (dpeaa)DE-He213 Local False Discovery Rate (dpeaa)DE-He213
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title	Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions
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title_full	Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions
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title_sort	local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions
title_auth	Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions
abstract	Abstract The simultaneous testing of a large number of hypotheses in a genome scan, using individual thresholds for significance, inherently leads to inflated genome-wide false positive rates. There exist various approaches to approximating the correct genomewide p-values under various assumptions, either by way of asymptotics or simulations. We explore a philosophically different criterion, recently proposed in the literature, which controls the false discovery rate. The test statistics are assumed to arise from a mixture of distributions under the null and non-null hypotheses. We fit the mixture distribution using both a nonparametric approach and commingling analysis, and then apply the local false discovery rate to select cut-off points for regions to be declared interesting. Another criterion, the minimum total error, is also explored. Both criteria seem to be sensible alternatives to controlling the classical type I and type II error rates. © Sinha et al; licensee BioMed Central Ltd 2005. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (
abstractGer	Abstract The simultaneous testing of a large number of hypotheses in a genome scan, using individual thresholds for significance, inherently leads to inflated genome-wide false positive rates. There exist various approaches to approximating the correct genomewide p-values under various assumptions, either by way of asymptotics or simulations. We explore a philosophically different criterion, recently proposed in the literature, which controls the false discovery rate. The test statistics are assumed to arise from a mixture of distributions under the null and non-null hypotheses. We fit the mixture distribution using both a nonparametric approach and commingling analysis, and then apply the local false discovery rate to select cut-off points for regions to be declared interesting. Another criterion, the minimum total error, is also explored. Both criteria seem to be sensible alternatives to controlling the classical type I and type II error rates. © Sinha et al; licensee BioMed Central Ltd 2005. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (
abstract_unstemmed	Abstract The simultaneous testing of a large number of hypotheses in a genome scan, using individual thresholds for significance, inherently leads to inflated genome-wide false positive rates. There exist various approaches to approximating the correct genomewide p-values under various assumptions, either by way of asymptotics or simulations. We explore a philosophically different criterion, recently proposed in the literature, which controls the false discovery rate. The test statistics are assumed to arise from a mixture of distributions under the null and non-null hypotheses. We fit the mixture distribution using both a nonparametric approach and commingling analysis, and then apply the local false discovery rate to select cut-off points for regions to be declared interesting. Another criterion, the minimum total error, is also explored. Both criteria seem to be sensible alternatives to controlling the classical type I and type II error rates. © Sinha et al; licensee BioMed Central Ltd 2005. This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (
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title_short	Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions
url	https://dx.doi.org/10.1186/1471-2156-6-S1-S23
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author2	Sinha, Moumita Mathew, George Elston, Robert C Luo, Yuqun
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up_date	2024-07-03T23:52:22.622Z
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We fit the mixture distribution using both a nonparametric approach and commingling analysis, and then apply the local false discovery rate to select cut-off points for regions to be declared interesting. Another criterion, the minimum total error, is also explored. 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Local false discovery rate and minimum total error rate approaches to identifying interesting chromosomal regions

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