Three commercial array platforms compared for DNA copy number detection with DNA isolated from FFPE tissue
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE30123 | GEO | 2012/01/17
SECONDARY ACCESSION(S): PRJNA144033
REPOSITORIES: GEO
Similar Datasets
Project description:Formalin-fixed, paraffin-embedded (FFPE) archival tissue is an important source of DNA material. The most commonly used technique to identify copy number aberrations from chromosomal DNA in tumorigenesis is array comparative genomic hybridization (aCGH). Although copy number analysis using DNA from FFPE archival tissue is challenging, several research groups have reported high quality and reproducible DNA copy number results using aCGH. Aim of the present study is to compare aCGH platforms suitable for copy number analysis using FFPE derived DNA. Two dual channel aCGH platforms (Agilent and NimbleGen) and a single channel SNP based platform (Affymetrix), were evaluated using seven FFPE colon cancer samples, median absolute deviation (MAD), deflection, signal-to-noise ratio (SNR) and DNA input requirements were used as quality criteria. Large differences were observed in MAD values and deflection between platforms; Agilent and NimbleGen showed better MAD values (0.13 for both) compared to Affymetrix (0.22). Contrary, Affymetrix showed a better deflection of 0.94, followed by 0.71 for Agilent and 0.51 for NimbleGen. Since the deflection compensates for the MAD the Signal to Noise Ratios (SNR) were comparable; Agilent ranks first, Affymetrix second and NimbleGen third with SNRs of 3.9, 3.6 and 3.3 respectively. DNA input amounts of 40ng are sufficient for high quality profiles with Affymetrix. For Agilent DNA input amounts of 50ng are sufficient for high quality profiles. For results of similar quality NimbleGen requires at least 100ng. Copy number analysis using DNA derived from FFPE archival material is feasible and shows reproducible results on high-resolution copy number platforms. Input amounts of DNA from FFPE material lower than recommended still yield high quality profiles without additional amplification steps.
2012-01-17 | GSE30120 | GEO
Project description:Formalin-fixed, paraffin-embedded (FFPE) archival tissue is an important source of DNA material. The most commonly used technique to identify copy number aberrations from chromosomal DNA in tumorigenesis is array comparative genomic hybridization (aCGH). Although copy number analysis using DNA from FFPE archival tissue is challenging, several research groups have reported high quality and reproducible DNA copy number results using aCGH. Aim of the present study is to compare aCGH platforms suitable for copy number analysis using FFPE derived DNA. Two dual channel aCGH platforms (Agilent and NimbleGen) and a single channel SNP based platform (Affymetrix), were evaluated using seven FFPE colon cancer samples, median absolute deviation (MAD), deflection, signal-to-noise ratio (SNR) and DNA input requirements were used as quality criteria. Large differences were observed in MAD values and deflection between platforms; Agilent and NimbleGen showed better MAD values (0.13 for both) compared to Affymetrix (0.22). Contrary, Affymetrix showed a better deflection of 0.94, followed by 0.71 for Agilent and 0.51 for NimbleGen. Since the deflection compensates for the MAD the Signal to Noise Ratios (SNR) were comparable; Agilent ranks first, Affymetrix second and NimbleGen third with SNRs of 3.9, 3.6 and 3.3 respectively. DNA input amounts of 40ng are sufficient for high quality profiles with Affymetrix. For Agilent DNA input amounts of 50ng are sufficient for high quality profiles. For results of similar quality NimbleGen requires at least 100ng. Copy number analysis using DNA derived from FFPE archival material is feasible and shows reproducible results on high-resolution copy number platforms. Input amounts of DNA from FFPE material lower than recommended still yield high quality profiles without additional amplification steps.
2012-01-17 | GSE30121 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE30120: Three commercial array platforms compared for DNA copy number detection with DNA isolated from FFPE tissue [NimbleGen] GSE30121: Three commercial array platforms compared for DNA copy number detection with DNA isolated from FFPE tissue [Agilent] Refer to individual Series
2012-01-17 | E-GEOD-30123 | biostudies-arrayexpress
Project description:Formalin-fixed, paraffin-embedded (FFPE) archival tissue is an important source of DNA material. The most commonly used technique to identify copy number aberrations from chromosomal DNA in tumorigenesis is array comparative genomic hybridization (aCGH). Although copy number analysis using DNA from FFPE archival tissue is challenging, several research groups have reported high quality and reproducible DNA copy number results using aCGH. Aim of the present study is to compare aCGH platforms suitable for copy number analysis using FFPE derived DNA. Two dual channel aCGH platforms (Agilent and NimbleGen) and a single channel SNP based platform (Affymetrix), were evaluated using seven FFPE colon cancer samples, median absolute deviation (MAD), deflection, signal-to-noise ratio (SNR) and DNA input requirements were used as quality criteria. Large differences were observed in MAD values and deflection between platforms; Agilent and NimbleGen showed better MAD values (0.13 for both) compared to Affymetrix (0.22). Contrary, Affymetrix showed a better deflection of 0.94, followed by 0.71 for Agilent and 0.51 for NimbleGen. Since the deflection compensates for the MAD the Signal to Noise Ratios (SNR) were comparable; Agilent ranks first, Affymetrix second and NimbleGen third with SNRs of 3.9, 3.6 and 3.3 respectively. DNA input amounts of 40ng are sufficient for high quality profiles with Affymetrix. For Agilent DNA input amounts of 50ng are sufficient for high quality profiles. For results of similar quality NimbleGen requires at least 100ng. Copy number analysis using DNA derived from FFPE archival material is feasible and shows reproducible results on high-resolution copy number platforms. Input amounts of DNA from FFPE material lower than recommended still yield high quality profiles without additional amplification steps. Overall study comprises 6 samples analyzed across three platforms with an additional dilution range (5 concentrations) of a seventh sample on two platforms. This Series represents NimbleGen platform-derived data.
2012-01-17 | E-GEOD-30120 | biostudies-arrayexpress
Project description:Formalin-fixed, paraffin-embedded (FFPE) archival tissue is an important source of DNA material. The most commonly used technique to identify copy number aberrations from chromosomal DNA in tumorigenesis is array comparative genomic hybridization (aCGH). Although copy number analysis using DNA from FFPE archival tissue is challenging, several research groups have reported high quality and reproducible DNA copy number results using aCGH. Aim of the present study is to compare aCGH platforms suitable for copy number analysis using FFPE derived DNA. Two dual channel aCGH platforms (Agilent and NimbleGen) and a single channel SNP based platform (Affymetrix), were evaluated using seven FFPE colon cancer samples, median absolute deviation (MAD), deflection, signal-to-noise ratio (SNR) and DNA input requirements were used as quality criteria. Large differences were observed in MAD values and deflection between platforms; Agilent and NimbleGen showed better MAD values (0.13 for both) compared to Affymetrix (0.22). Contrary, Affymetrix showed a better deflection of 0.94, followed by 0.71 for Agilent and 0.51 for NimbleGen. Since the deflection compensates for the MAD the Signal to Noise Ratios (SNR) were comparable; Agilent ranks first, Affymetrix second and NimbleGen third with SNRs of 3.9, 3.6 and 3.3 respectively. DNA input amounts of 40ng are sufficient for high quality profiles with Affymetrix. For Agilent DNA input amounts of 50ng are sufficient for high quality profiles. For results of similar quality NimbleGen requires at least 100ng. Copy number analysis using DNA derived from FFPE archival material is feasible and shows reproducible results on high-resolution copy number platforms. Input amounts of DNA from FFPE material lower than recommended still yield high quality profiles without additional amplification steps. Overall study comprises 6 samples analyzed across three platforms with an additional dilution range (5 concentrations) of a seventh sample on two platforms. This Series represents Agilent platform-derived data.
2012-01-17 | E-GEOD-30121 | biostudies-arrayexpress
Project description:MotivationCopy number variations (CNVs) are gains and losses of DNA segments and have been associated with disease. Many large-scale genetic association studies are performing CNV analysis using whole exome sequencing (WES) and whole genome sequencing (WGS). In many of these studies, previous single-nucleotide polymorphism (SNP)-array data are available. An integrated cross-platform analysis is expected to improve resolution and accuracy, yet there is no tool for effectively combining data from sequencing and array platforms. The detection of CNVs using sequencing data alone can also be further improved by the utilization of allele-specific reads.ResultsWe propose a statistical framework, integrated CNV (iCNV) detection algorithm, which can be applied to multiple study designs: WES only, WGS only, SNP array only, or any combination of SNP and sequencing data. iCNV applies platform-specific normalization, utilizes allele specific reads from sequencing and integrates matched NGS and SNP-array data by a hidden Markov model. We compare integrated two-platform CNV detection using iCNV to naïve intersection or union of platforms and show that iCNV increases sensitivity and robustness. We also assess the accuracy of iCNV on WGS data only and show that the utilization of allele-specific reads improve CNV detection accuracy compared to existing methods.Availability and implementationhttps://github.com/zhouzilu/iCNV.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC6041760 | biostudies-literature
Project description:MotivationDNA copy number variants (CNVs) are gains and losses of segments of chromosomes, and comprise an important class of genetic variation. Recently, various microarray hybridization-based techniques have been developed for high-throughput measurement of DNA copy number. In many studies, multiple technical platforms or different versions of the same platform were used to interrogate the same samples; and it became necessary to pool information across these multiple sources to derive a consensus molecular profile for each sample. An integrated analysis is expected to maximize resolution and accuracy, yet currently there is no well-formulated statistical method to address the between-platform differences in probe coverage, assay methods, sensitivity and analytical complexity.ResultsThe conventional approach is to apply one of the CNV detection ('segmentation') algorithms to search for DNA segments of altered signal intensity. The results from multiple platforms are combined after segmentation. Here we propose a new method, Multi-Platform Circular Binary Segmentation (MPCBS), which pools statistical evidence across platforms during segmentation, and does not require pre-standardization of different data sources. It involves a weighted sum of t-statistics, which arises naturally from the generalized log-likelihood ratio of a multi-platform model. We show by comparing the integrated analysis of Affymetrix and Illumina SNP array data with Agilent and fosmid clone end-sequencing results on eight HapMap samples that MPCBS achieves improved spatial resolution, detection power and provides a natural consensus across platforms. We also apply the new method to analyze multi-platform data for tumor samples.AvailabilityThe R package for MPCBS is registered on R-Forge (http://r-forge.r-project.org/) under project name MPCBS.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC2852203 | biostudies-literature
Project description:Genomic technologies, such as array comparative genomic hybridization (aCGH), increasingly offer definitive gene dosage profiles in clinical samples. Historically, copy number profiling was limited to large fresh-frozen tumors where intact DNA could be readily extracted. Genomic analyses of pre-neoplastic tumors and diagnostic biopsies are often limited to DNA processed by formalin-fixation and paraffin-embedding (FFPE). We present specialized protocols for DNA extraction and processing from FFPE tissues utilizing DNase processing to generate randomly fragmented DNA. The protocols are applied to FFPE clinical samples of varied tumor types, from multiple institutions and of varied block age. Direct comparative analyses with regression coefficient were calculated on split-sample (portion fresh/portion FFPE) of colorectal tumor samples. We show equal detection of a homozygous loss of SMAD4 at the exon-level in the SW480 cell line and gene-specific alterations in the split tumor samples. aCGH application to a set of archival FFPE samples of skin squamous cell carcinomas detected a novel hemizygous deletion in INPP5A on 10q26.3. Finally we present data on derivative of log ratio, a particular sensitive detector of measurement variance, for 216 sequential hybridizations to assess protocol reliability over a wide range of FFPE samples.
| S-EPMC2811007 | biostudies-other
Project description:Systematic tumour profiling is essential for biomarker research and clinically for assessing response to therapy. Solving the challenge of delivering informative copy number (CN) profiles from formalin-fixed paraffin embedded (FFPE) material, the only likely readily available biospecimen for most cancers, involves successful processing of small quantities of degraded DNA. To investigate the potential for analysis of such lesions, whole-genome CNVseq was applied to 300 FFPE primary tumour samples, obtained from a large-scale epidemiological study of melanoma. The quality and the discriminatory power of CNVseq was assessed. Libraries were successfully generated for 93% of blocks, with input DNA quantity being the only predictor of success (success rate dropped to 65% if <20 ng available); 3% of libraries were dropped because of low sequence alignment rates. Technical replicates showed high reproducibility. Comparison with targeted CN assessment showed consistency with the Next Generation Sequencing (NGS) analysis. We were able to detect and distinguish CN changes with a resolution of ≤10 kb. To demonstrate performance, we report the spectrum of genomic CN alterations (CNAs) detected at 9p21, the major site of CN change in melanoma. This successful analysis of CN in FFPE material using NGS provides proof of principle for intensive examination of population-based samples.
| S-EPMC6586881 | biostudies-literature
Project description:BackgroundDNBSEQ™ platforms are new massively parallel sequencing (MPS) platforms that use DNA nanoball technology. Use of data generated from DNBSEQ™ platforms to detect single nucleotide variants (SNVs) and small insertions and deletions (indels) has proven to be quite effective, while the feasibility of copy number variants (CNVs) detection is unclear.ResultsHere, we first benchmarked different CNV detection tools based on Illumina whole-genome sequencing (WGS) data of NA12878 and then assessed these tools in CNV detection based on DNBSEQ™ sequencing data from the same sample. When the same tool was used, the CNVs detected based on DNBSEQ™ and Illumina data were similar in quantity, length and distribution, while great differences existed within results from different tools and even based on data from a single platform. We further estimated the CNV detection power based on available CNV benchmarks of NA12878 and found similar precision and sensitivity between the DNBSEQ™ and Illumina platforms. We also found higher precision of CNVs shorter than 1 kbp based on DNBSEQ™ platforms than those based on Illumina platforms by using Pindel, DELLY and LUMPY. We carefully compared these two available benchmarks and found a large proportion of specific CNVs between them. Thus, we constructed a more complete CNV benchmark of NA12878 containing 3512 CNV regions.ConclusionsWe assessed and benchmarked CNV detections based on WGS with DNBSEQ™ platforms and provide guidelines for future studies.
| S-EPMC7659224 | biostudies-literature