Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios [Omni2.5]
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ABSTRACT:
PROVIDER: PRJNA786931 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Illumina Infinium whole genome genotyping (WGG) arrays are increasingly being applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Methods developed for normalization of WGG arrays have mostly focused on diploid, normal samples. However, for cancer samples genomic aberrations may confound normalization and data interpretation. Therefore, we examined the effects of the conventionally used normalization method for Illumina Infinium arrays when applied to cancer samples. We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illumina’s proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the normalization strategy using 535 individual hybridizations from 10 data sets from the analysis of cancer genomes and normal blood samples generated on Illumina Infinium II 300k version 1 and 2, 370k and 550k BeadChips. We show that the proposed normalization strategy successfully removes asymmetry in estimates of both allelic proportions and copy numbers. Additionally, the normalization strategy reduces the technical variation for copy number estimates while retaining the response to copy number alterations. The proposed normalization strategy represents a valuable low-level analysis tool that improves the quality of data obtained from Illumina Infinium arrays, in particular when used for LOH and copy number variation studies.
2008-10-04 | GSE11977 | GEO
Project description:Illumina Infinium whole genome genotyping (WGG) arrays are increasingly being applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Methods developed for normalization of WGG arrays have mostly focused on diploid, normal samples. However, for cancer samples genomic aberrations may confound normalization and data interpretation. Therefore, we examined the effects of the conventionally used normalization method for Illumina Infinium arrays when applied to cancer samples. We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illumina’s proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the normalization strategy using 535 individual hybridizations from 10 data sets from the analysis of cancer genomes and normal blood samples generated on Illumina Infinium II 300k version 1 and 2, 370k and 550k BeadChips. We show that the proposed normalization strategy successfully removes asymmetry in estimates of both allelic proportions and copy numbers. Additionally, the normalization strategy reduces the technical variation for copy number estimates while retaining the response to copy number alterations. The proposed normalization strategy represents a valuable low-level analysis tool that improves the quality of data obtained from Illumina Infinium arrays, in particular when used for LOH and copy number variation studies. To investigate the effects of a quantile normalization of Illumina Infinium data, compared to conventional normalization using BeadStudio (www.illumina.com), we renormalized 535 individual hybridizations conducted on Illumina 300K, 370K and 550K BeadChips. Sample types included breast cancer, colon cancer, urothelial carcinoma, leukemia as well as normal blood and HapMap samples. This series includes the 6 breast cancers hybridized on Illumina HumanHap 550K BeadChips.
2008-10-04 | E-GEOD-11977 | biostudies-arrayexpress
Project description:Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios [CytoSNP]
| PRJNA786924 | ENA
Project description:BACKGROUND: Illumina Infinium whole genome genotyping (WGG) arrays are increasingly being applied in cancer genomics to study gene copy number alterations and allele-specific aberrations such as loss-of-heterozygosity (LOH). Methods developed for normalization of WGG arrays have mostly focused on diploid, normal samples. However, for cancer samples genomic aberrations may confound normalization and data interpretation. Therefore, we examined the effects of the conventionally used normalization method for Illumina Infinium arrays when applied to cancer samples. RESULTS: We demonstrate an asymmetry in the detection of the two alleles for each SNP, which deleteriously influences both allelic proportions and copy number estimates. The asymmetry is caused by a remaining bias between the two dyes used in the Infinium II assay after using the normalization method in Illumina's proprietary software (BeadStudio). We propose a quantile normalization strategy for correction of this dye bias. We tested the normalization strategy using 535 individual hybridizations from 10 data sets from the analysis of cancer genomes and normal blood samples generated on Illumina Infinium II 300 k version 1 and 2, 370 k and 550 k BeadChips. We show that the proposed normalization strategy successfully removes asymmetry in estimates of both allelic proportions and copy numbers. Additionally, the normalization strategy reduces the technical variation for copy number estimates while retaining the response to copy number alterations. CONCLUSION: The proposed normalization strategy represents a valuable tool that improves the quality of data obtained from Illumina Infinium arrays, in particular when used for LOH and copy number variation studies.
| S-EPMC2572624 | biostudies-literature
Project description:Recurring genetic abnormalities have been identified in Philadelphia chromosome (Ph)-positive acute lymphoblastic leukemia (ALL). Among them, IKZF1 deletion was associated with poor prognosis in patients treated with imatinib-based or dasatinib-based regimens. However, the molecular determinants for clinical outcomes in ponatinib-treated patients remain unknown. We systematically analyzed genetic alterations in adults with Ph-positive ALL uniformly treated in clinical trials with dasatinib-based regimens or a ponatinib-based regimen and investigated the molecular determinants for treatment outcomes using pretreatment specimens collected from adults with Ph-positive ALL treated with Hyper-CVAD plus dasatinib or ponatinib. DNA sequencing and SNP microarray were performed and recurrent genetic abnormalities were found in 84% of the patients, among whom IKZF1 deletion was most frequently detected (60%). IKZF1 deletion frequently co-occurred with other copy-number abnormalities (IKZF1plus, 46%) and was significantly associated with unfavorable overall survival (OS) (false discovery rate < 0.1) and increased cumulative incidence of relapse (p = 0.01). In a multivariate analysis, dasatinib therapy, lack of achievement of 3-month complete molecular response, and the presence of IKZF1plus status were significantly associated with poor OS. The differential impact of IKZF1plus was largely restricted to patients given Hyper-CVAD plus ponatinib; dasatinib-based regimens had unfavorable outcomes regardless of the molecular abnormalities.
2021-12-10 | GSE190392 | GEO
Project description:Recurring genetic abnormalities have been identified in Philadelphia chromosome (Ph)-positive acute lymphoblastic leukemia (ALL). Among them, IKZF1 deletion was associated with poor prognosis in patients treated with imatinib-based or dasatinib-based regimens. However, the molecular determinants for clinical outcomes in ponatinib-treated patients remain unknown. We systematically analyzed genetic alterations in adults with Ph-positive ALL uniformly treated in clinical trials with dasatinib-based regimens or a ponatinib-based regimen and investigated the molecular determinants for treatment outcomes using pretreatment specimens collected from adults with Ph-positive ALL treated with Hyper-CVAD plus dasatinib or ponatinib. DNA sequencing and SNP microarray were performed and recurrent genetic abnormalities were found in 84% of the patients, among whom IKZF1 deletion was most frequently detected (60%). IKZF1 deletion frequently co-occurred with other copy-number abnormalities (IKZF1plus, 46%) and was significantly associated with unfavorable overall survival (OS) (false discovery rate < 0.1) and increased cumulative incidence of relapse (p = 0.01). In a multivariate analysis, dasatinib therapy, lack of achievement of 3-month complete molecular response, and the presence of IKZF1plus status were significantly associated with poor OS. The differential impact of IKZF1plus was largely restricted to patients given Hyper-CVAD plus ponatinib; dasatinib-based regimens had unfavorable outcomes regardless of the molecular abnormalities.
2021-12-10 | GSE190390 | GEO
Project description:Normalization of Illumina Infinium whole-genome SNP data improves copy number estimates and allelic intensity ratios
| PRJNA105855 | ENA
Project description:Unexpected variability of allelic imbalance estimates from RNA sequencing
| PRJNA599964 | ENA
Project description:RNA sequencing and other experimental methods producing large amounts of data are increasingly dominant in molecular biology. However, the noise properties of these techniques are not fully appreciated. We assessed how reproducible are the measurements of allele-specific expression between replicate RNA-seq experiments from the same RNA sample. Surprisingly, estimates of allelic imbalance (AI) varied between technical replicates up to 8-fold higher than expected from commonly applied noise models. We show that AI overdispersion substantially varies between replicates and experimental series, appears to arise during the construction of sequencing libraries, and can be measured by comparing technical replicates. We demonstrate that compensation for AI overdispersion greatly reduces technical variation and enables reliable differential analysis of allele-specific expression across samples and across experiments. Conversely, not taking AI overdispersion into account can lead to a substantial number of false positives in analysis of allele-specific gene expression.
2021-03-26 | GSE143310 | GEO