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Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing
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| Zeitschriftentitel: | Cancer Informatics |
|---|---|
| Personen und Körperschaften: | , , , , , , |
| In: | Cancer Informatics, 13s3, 2014, S. CIN.S14023 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
SAGE Publications
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| Schlagwörter: |
| author_facet |
Ozer, Hatice Gulcin Usubalieva, Aisulu Dorrance, Adrienne Yilmaz, Ayse Selen Caligiuri, Michael Marcucci, Guido Huang, Kun Ozer, Hatice Gulcin Usubalieva, Aisulu Dorrance, Adrienne Yilmaz, Ayse Selen Caligiuri, Michael Marcucci, Guido Huang, Kun |
|---|---|
| author |
Ozer, Hatice Gulcin Usubalieva, Aisulu Dorrance, Adrienne Yilmaz, Ayse Selen Caligiuri, Michael Marcucci, Guido Huang, Kun |
| spellingShingle |
Ozer, Hatice Gulcin Usubalieva, Aisulu Dorrance, Adrienne Yilmaz, Ayse Selen Caligiuri, Michael Marcucci, Guido Huang, Kun Cancer Informatics Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing Cancer Research Oncology |
| author_sort |
ozer, hatice gulcin |
| spelling |
Ozer, Hatice Gulcin Usubalieva, Aisulu Dorrance, Adrienne Yilmaz, Ayse Selen Caligiuri, Michael Marcucci, Guido Huang, Kun 1176-9351 1176-9351 SAGE Publications Cancer Research Oncology http://dx.doi.org/10.4137/cin.s14023 <jats:p> The genome-wide discoveries such as detection of copy number alterations (CNA) from high-throughput whole-genome sequencing data enabled new developments in personalized medicine. The CNAs have been reported to be associated with various diseases and cancers including acute myeloid leukemia. However, there are multiple challenges to the use of current CNA detection tools that lead to high false-positive rates and thus impede widespread use of such tools in cancer research. In this paper, we discuss these issues and propose possible solutions. First, since the entire genome cannot be mapped due to some regions lacking sequence uniqueness, current methods cannot be appropriately adjusted to handle these regions in the analyses. Thus, detection of medium-sized CNAs is also being directly affected by these mappability problems. The requirement for matching control samples is also an important limitation because acquiring matching controls might not be possible or might not be cost efficient. Here we present an approach that addresses these issues and detects medium-sized CNAs in cancer genomes by (1) masking unmappable regions during the initial CNA detection phase, (2) using pool of a few normal samples as control, and (3) employing median filtering to adjust CNA ratios to its surrounding coverage and eliminate false positives. </jats:p> Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing Cancer Informatics |
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| title |
Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| title_unstemmed |
Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| title_full |
Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| title_fullStr |
Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| title_full_unstemmed |
Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| title_short |
Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| title_sort |
identification of medium-sized copy number alterations in whole-genome sequencing |
| topic |
Cancer Research Oncology |
| url |
http://dx.doi.org/10.4137/cin.s14023 |
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2014 |
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CIN.S14023 |
| description |
<jats:p> The genome-wide discoveries such as detection of copy number alterations (CNA) from high-throughput whole-genome sequencing data enabled new developments in personalized medicine. The CNAs have been reported to be associated with various diseases and cancers including acute myeloid leukemia. However, there are multiple challenges to the use of current CNA detection tools that lead to high false-positive rates and thus impede widespread use of such tools in cancer research. In this paper, we discuss these issues and propose possible solutions. First, since the entire genome cannot be mapped due to some regions lacking sequence uniqueness, current methods cannot be appropriately adjusted to handle these regions in the analyses. Thus, detection of medium-sized CNAs is also being directly affected by these mappability problems. The requirement for matching control samples is also an important limitation because acquiring matching controls might not be possible or might not be cost efficient. Here we present an approach that addresses these issues and detects medium-sized CNAs in cancer genomes by (1) masking unmappable regions during the initial CNA detection phase, (2) using pool of a few normal samples as control, and (3) employing median filtering to adjust CNA ratios to its surrounding coverage and eliminate false positives. </jats:p> |
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| author | Ozer, Hatice Gulcin, Usubalieva, Aisulu, Dorrance, Adrienne, Yilmaz, Ayse Selen, Caligiuri, Michael, Marcucci, Guido, Huang, Kun |
| author_facet | Ozer, Hatice Gulcin, Usubalieva, Aisulu, Dorrance, Adrienne, Yilmaz, Ayse Selen, Caligiuri, Michael, Marcucci, Guido, Huang, Kun, Ozer, Hatice Gulcin, Usubalieva, Aisulu, Dorrance, Adrienne, Yilmaz, Ayse Selen, Caligiuri, Michael, Marcucci, Guido, Huang, Kun |
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| description | <jats:p> The genome-wide discoveries such as detection of copy number alterations (CNA) from high-throughput whole-genome sequencing data enabled new developments in personalized medicine. The CNAs have been reported to be associated with various diseases and cancers including acute myeloid leukemia. However, there are multiple challenges to the use of current CNA detection tools that lead to high false-positive rates and thus impede widespread use of such tools in cancer research. In this paper, we discuss these issues and propose possible solutions. First, since the entire genome cannot be mapped due to some regions lacking sequence uniqueness, current methods cannot be appropriately adjusted to handle these regions in the analyses. Thus, detection of medium-sized CNAs is also being directly affected by these mappability problems. The requirement for matching control samples is also an important limitation because acquiring matching controls might not be possible or might not be cost efficient. Here we present an approach that addresses these issues and detects medium-sized CNAs in cancer genomes by (1) masking unmappable regions during the initial CNA detection phase, (2) using pool of a few normal samples as control, and (3) employing median filtering to adjust CNA ratios to its surrounding coverage and eliminate false positives. </jats:p> |
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| spelling | Ozer, Hatice Gulcin Usubalieva, Aisulu Dorrance, Adrienne Yilmaz, Ayse Selen Caligiuri, Michael Marcucci, Guido Huang, Kun 1176-9351 1176-9351 SAGE Publications Cancer Research Oncology http://dx.doi.org/10.4137/cin.s14023 <jats:p> The genome-wide discoveries such as detection of copy number alterations (CNA) from high-throughput whole-genome sequencing data enabled new developments in personalized medicine. The CNAs have been reported to be associated with various diseases and cancers including acute myeloid leukemia. However, there are multiple challenges to the use of current CNA detection tools that lead to high false-positive rates and thus impede widespread use of such tools in cancer research. In this paper, we discuss these issues and propose possible solutions. First, since the entire genome cannot be mapped due to some regions lacking sequence uniqueness, current methods cannot be appropriately adjusted to handle these regions in the analyses. Thus, detection of medium-sized CNAs is also being directly affected by these mappability problems. The requirement for matching control samples is also an important limitation because acquiring matching controls might not be possible or might not be cost efficient. Here we present an approach that addresses these issues and detects medium-sized CNAs in cancer genomes by (1) masking unmappable regions during the initial CNA detection phase, (2) using pool of a few normal samples as control, and (3) employing median filtering to adjust CNA ratios to its surrounding coverage and eliminate false positives. </jats:p> Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing Cancer Informatics |
| spellingShingle | Ozer, Hatice Gulcin, Usubalieva, Aisulu, Dorrance, Adrienne, Yilmaz, Ayse Selen, Caligiuri, Michael, Marcucci, Guido, Huang, Kun, Cancer Informatics, Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing, Cancer Research, Oncology |
| title | Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| title_full | Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| title_fullStr | Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| title_full_unstemmed | Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| title_short | Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| title_sort | identification of medium-sized copy number alterations in whole-genome sequencing |
| title_unstemmed | Identification of Medium-Sized Copy Number Alterations in Whole-Genome Sequencing |
| topic | Cancer Research, Oncology |
| url | http://dx.doi.org/10.4137/cin.s14023 |