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SIRAC: Supervised Identification of Regions of Aberration in aCGH datasets.

Lai C, Horlings HM, van de Vijver MJ, van Beers EH, Nederlof PM, Wessels LF, Reinders MJ - BMC Bioinformatics (2007)

Bottom Line: SIRAC does not need any preprocessing of the aCGH datasets, and requires only few, intuitive parameters.We illustrate the features of the algorithm with the use of a simple artificial dataset.The results on two breast cancer datasets show promising outcomes that are in agreement with previous findings, but SIRAC better pinpoints the dissimilarities between the classes of interest.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bioinformatics group, Delft University, Delft, The Netherlands. c.lai@tudelft.nl

ABSTRACT

Background: Array comparative genome hybridization (aCGH) provides information about genomic aberrations. Alterations in the DNA copy number may cause the cell to malfunction, leading to cancer. Therefore, the identification of DNA amplifications or deletions across tumors may reveal key genes involved in cancer and improve our understanding of the underlying biological processes associated with the disease.

Results: We propose a supervised algorithm for the analysis of aCGH data and the identification of regions of chromosomal alteration (SIRAC). We first determine the DNA-probes that are important to distinguish the classes of interest, and then evaluate in a systematic and robust scheme if these relevant DNA-probes are closely located, i.e. form a region of amplification/deletion. SIRAC does not need any preprocessing of the aCGH datasets, and requires only few, intuitive parameters.

Conclusion: We illustrate the features of the algorithm with the use of a simple artificial dataset. The results on two breast cancer datasets show promising outcomes that are in agreement with previous findings, but SIRAC better pinpoints the dissimilarities between the classes of interest.

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Related in: MedlinePlus

NKI dataset, summary tables results and comparison with Bergamaschi et al. Summary of the aberrations per chromosome arm for the four different subtypes (Basal, ERBB2, Luminal A or Luminal B). The numbers in the top of the tables denotes the chromosomes. A arm is indicated with a red color when a significant region is found on that arm that shows a deletion of the DNA-probes of interest. Similarly, green indicates amplification. The gray boxes indicate that the aberration was not present in the class of interest but in the rest of the samples. The top and the bottom tables show the aberrations found with the SIRAC algorithm on the NKI dataset for two different values of the FDR, i.e. FDR < 0.005 and FDR < 0.05 respectively. The middle table presents the results of Bergamaschi et al. [33] on their breast cancer dataset.
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Figure 5: NKI dataset, summary tables results and comparison with Bergamaschi et al. Summary of the aberrations per chromosome arm for the four different subtypes (Basal, ERBB2, Luminal A or Luminal B). The numbers in the top of the tables denotes the chromosomes. A arm is indicated with a red color when a significant region is found on that arm that shows a deletion of the DNA-probes of interest. Similarly, green indicates amplification. The gray boxes indicate that the aberration was not present in the class of interest but in the rest of the samples. The top and the bottom tables show the aberrations found with the SIRAC algorithm on the NKI dataset for two different values of the FDR, i.e. FDR < 0.005 and FDR < 0.05 respectively. The middle table presents the results of Bergamaschi et al. [33] on their breast cancer dataset.

Mentions: Figure 5(a) summarizes the aberrations found on the p or q chromosomal arms of the different subtypes when s = 2. The same color coding used in the lower plots of Figure 4 is applied to the chromosome arms, i.e. red specifies a deletion, green an amplification, and gray indicates that the aberration was not in the class of interest. Note that the resolution of SIRAC is neither restricted to chromosome arms nor to cytobands. The representation per chromosomal arm given in Figure 5 is adopted only for the sake of conciseness. The Basal subtype is associated with the largest number of aberrations, with deletions on Chromosomes 4, 5, 14 and 15, and amplifications on Chromosomes 6, 10 and 12. The ERBB2 subtype has only an amplification on the q arm of Chromosome 17, covering the genomic position where the ERBB2 gene is located. This is a known aberration, and the results suggest that this is the only aberration that differentiates this subtype from the other samples. The fact that this known aberration is found, also serves as a positive control for the SIRAC algorithm. The Luminal A subtype is characterized by a strong amplification on Chromosome 1 and a deletion on Chromosome 16. The Luminal B has less pronounce aberrations on Chromosomes 1, 8, 12 and 20.


SIRAC: Supervised Identification of Regions of Aberration in aCGH datasets.

Lai C, Horlings HM, van de Vijver MJ, van Beers EH, Nederlof PM, Wessels LF, Reinders MJ - BMC Bioinformatics (2007)

NKI dataset, summary tables results and comparison with Bergamaschi et al. Summary of the aberrations per chromosome arm for the four different subtypes (Basal, ERBB2, Luminal A or Luminal B). The numbers in the top of the tables denotes the chromosomes. A arm is indicated with a red color when a significant region is found on that arm that shows a deletion of the DNA-probes of interest. Similarly, green indicates amplification. The gray boxes indicate that the aberration was not present in the class of interest but in the rest of the samples. The top and the bottom tables show the aberrations found with the SIRAC algorithm on the NKI dataset for two different values of the FDR, i.e. FDR < 0.005 and FDR < 0.05 respectively. The middle table presents the results of Bergamaschi et al. [33] on their breast cancer dataset.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2198922&req=5

Figure 5: NKI dataset, summary tables results and comparison with Bergamaschi et al. Summary of the aberrations per chromosome arm for the four different subtypes (Basal, ERBB2, Luminal A or Luminal B). The numbers in the top of the tables denotes the chromosomes. A arm is indicated with a red color when a significant region is found on that arm that shows a deletion of the DNA-probes of interest. Similarly, green indicates amplification. The gray boxes indicate that the aberration was not present in the class of interest but in the rest of the samples. The top and the bottom tables show the aberrations found with the SIRAC algorithm on the NKI dataset for two different values of the FDR, i.e. FDR < 0.005 and FDR < 0.05 respectively. The middle table presents the results of Bergamaschi et al. [33] on their breast cancer dataset.
Mentions: Figure 5(a) summarizes the aberrations found on the p or q chromosomal arms of the different subtypes when s = 2. The same color coding used in the lower plots of Figure 4 is applied to the chromosome arms, i.e. red specifies a deletion, green an amplification, and gray indicates that the aberration was not in the class of interest. Note that the resolution of SIRAC is neither restricted to chromosome arms nor to cytobands. The representation per chromosomal arm given in Figure 5 is adopted only for the sake of conciseness. The Basal subtype is associated with the largest number of aberrations, with deletions on Chromosomes 4, 5, 14 and 15, and amplifications on Chromosomes 6, 10 and 12. The ERBB2 subtype has only an amplification on the q arm of Chromosome 17, covering the genomic position where the ERBB2 gene is located. This is a known aberration, and the results suggest that this is the only aberration that differentiates this subtype from the other samples. The fact that this known aberration is found, also serves as a positive control for the SIRAC algorithm. The Luminal A subtype is characterized by a strong amplification on Chromosome 1 and a deletion on Chromosome 16. The Luminal B has less pronounce aberrations on Chromosomes 1, 8, 12 and 20.

Bottom Line: SIRAC does not need any preprocessing of the aCGH datasets, and requires only few, intuitive parameters.We illustrate the features of the algorithm with the use of a simple artificial dataset.The results on two breast cancer datasets show promising outcomes that are in agreement with previous findings, but SIRAC better pinpoints the dissimilarities between the classes of interest.

View Article: PubMed Central - HTML - PubMed

Affiliation: Bioinformatics group, Delft University, Delft, The Netherlands. c.lai@tudelft.nl

ABSTRACT

Background: Array comparative genome hybridization (aCGH) provides information about genomic aberrations. Alterations in the DNA copy number may cause the cell to malfunction, leading to cancer. Therefore, the identification of DNA amplifications or deletions across tumors may reveal key genes involved in cancer and improve our understanding of the underlying biological processes associated with the disease.

Results: We propose a supervised algorithm for the analysis of aCGH data and the identification of regions of chromosomal alteration (SIRAC). We first determine the DNA-probes that are important to distinguish the classes of interest, and then evaluate in a systematic and robust scheme if these relevant DNA-probes are closely located, i.e. form a region of amplification/deletion. SIRAC does not need any preprocessing of the aCGH datasets, and requires only few, intuitive parameters.

Conclusion: We illustrate the features of the algorithm with the use of a simple artificial dataset. The results on two breast cancer datasets show promising outcomes that are in agreement with previous findings, but SIRAC better pinpoints the dissimilarities between the classes of interest.

Show MeSH
Related in: MedlinePlus