Affymetrix SNP array data for human prostate tumor samples
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE62218 | GEO | 2014/10/20
SECONDARY ACCESSION(S): PRJNA263493
REPOSITORIES: GEO
Similar Datasets
Project description:Metabolomics was used to identify metabolic fingerprints of AKT1 activation or MYC overexpression in human prostate tumors. Genomics was used to determine how many of these tumors had a genetic aberration underlying signaling activation. Copy number analysis of Affymetrix 250K SNP arrays was performed for 59 human prostate tumors and 6 normal prostate samples.
2014-10-20 | E-GEOD-62218 | biostudies-arrayexpress
Project description: Not available
| S-DIXA-D-1096 | biostudies-other
Project description:To shed light on the molecular bases of B-lineage acute lymphoblastic leukemia lacking known rearrangements (B-NEG ALL) and the differences between children and adults, we analyzed 168 B-NEG ALLs - including children, adolescents/young adults (AYA) and adults by genome-wide technologies, namely Next-generation sequencing and copy number aberration (CNA). Affymetrix SNP array analysis was performed according to the manufacturer's directions on DNA extracted from bone marrow sampled at diagnosis and paired germline DNA extracted from peripheral blood/bone marrow at complete remission or saliva.
2016-03-01 | GSE67405 | GEO
Project description:Chordomas are rare, low to intermediate grade malignant bone tumors of the axial skeleton, believed to originate from the notochord. Treatment options are limited and mainly restricted to surgical excision, as chordomas have been proven to be largely resistant to conventional ionizing radiation and chemotherapy. Therefore a new cell line was established. The cell line has been characterized by immunohistochemistry,western blot and karyotyping using cobra fish technology. Copy number variations (CNV) and loss-of heterozygosity (LOH) from fibroblasts, tumor tissue, low and high cell line passage was evaluted by using Affymetrix 6.0SNP Arrays. DNA isolated from the patients MNCs was used as control. The cell line MUG-Chor1 is highly similar to genetic profiles of chordomas and provides therefore a powerful tool for further investigations.
2012-07-12 | GSE25720 | GEO
Project description:BackgroundCopy number data are routinely being extracted from genome-wide association study chips using a variety of software. We empirically evaluated and compared four freely-available software packages designed for Affymetrix SNP chips to estimate copy number: Affymetrix Power Tools (APT), Aroma.Affymetrix, PennCNV and CRLMM. Our evaluation used 1,418 GENOA samples that were genotyped on the Affymetrix Genome-Wide Human SNP Array 6.0. We compared bias and variance in the locus-level copy number data, the concordance amongst regions of copy number gains/deletions and the false-positive rate amongst deleted segments.ResultsAPT had median locus-level copy numbers closest to a value of two, whereas PennCNV and Aroma.Affymetrix had the smallest variability associated with the median copy number. Of those evaluated, only PennCNV provides copy number specific quality-control metrics and identified 136 poor CNV samples. Regions of copy number variation (CNV) were detected using the hidden Markov models provided within PennCNV and CRLMM/VanillaIce. PennCNV detected more CNVs than CRLMM/VanillaIce; the median number of CNVs detected per sample was 39 and 30, respectively. PennCNV detected most of the regions that CRLMM/VanillaIce did as well as additional CNV regions. The median concordance between PennCNV and CRLMM/VanillaIce was 47.9% for duplications and 51.5% for deletions. The estimated false-positive rate associated with deletions was similar for PennCNV and CRLMM/VanillaIce.ConclusionsIf the objective is to perform statistical tests on the locus-level copy number data, our empirical results suggest that PennCNV or Aroma.Affymetrix is optimal. If the objective is to perform statistical tests on the summarized segmented data then PennCNV would be preferred over CRLMM/VanillaIce. Specifically, PennCNV allows the analyst to estimate locus-level copy number, perform segmentation and evaluate CNV-specific quality-control metrics within a single software package. PennCNV has relatively small bias, small variability and detects more regions while maintaining a similar estimated false-positive rate as CRLMM/VanillaIce. More generally, we advocate that software developers need to provide guidance with respect to evaluating and choosing optimal settings in order to obtain optimal results for an individual dataset. Until such guidance exists, we recommend trying multiple algorithms, evaluating concordance/discordance and subsequently consider the union of regions for downstream association tests.
| S-EPMC3146450 | biostudies-literature
Project description:ObjectiveOur goal was to evaluate the influence of quality control (QC) decisions using two genotype calling algorithms, CRLMM and Birdseed, designed for the Affymetrix SNP Array 6.0.MethodsVarious QC options were tried using the two algorithms and comparisons were made on subject and call rate and on association results using two data sets.ResultsFor Birdseed, we recommend using the contrast QC instead of QC call rate for sample QC. For CRLMM, we recommend using the signal-to-noise rate ≥4 for sample QC and a posterior probability of 90% for genotype accuracy. For both algorithms, we recommend calling the genotype separately for each plate, and dropping SNPs with a lower call rate (<95%) before evaluating samples with lower call rates. To investigate whether the genotype calls from the two algorithms impacted the genome-wide association results, we performed association analysis using data from the GENOA cohort; we observed that the number of significant SNPs were similar using either CRLMM or Birdseed.ConclusionsUsing our suggested workflow both algorithms performed similarly; however, fewer samples were removed and CRLMM took half the time to run our 854 study samples (4.2 h) compared to Birdseed (8.4 h).
| S-EPMC3136375 | biostudies-literature
Project description:Prostate cancer (PCa) is the most commonly diagnosed non-cutaneous cancer in male subjects in Western countries. The widespread use of prostate-specific antigen (PSA) has increased the detection of this cancer form in earlier stages. Moreover, it has increased the need for new diagnostic procedures to be developed for patient stratification based on risk of progression. We analysed laser-microdissected prostate tumour tissue from 43 patients with histologically verified PCa, using the new high-resolution Affymetrix Mapping 50K single-nucleotide polymorphism array. The results showed six major loss of heterozygosity regions at chromosomes 6q14-16, 8p23-11, 10q23, 13q13-21 and 16q21-24 and a novel region at chromosome 21q22.2, all of which reveal concomitant copy number loss. Tumour development was further characterised by numerous novel genomic regions almost exclusively showing copy number loss. However, tumour progression towards a metastatic stage, as well as poor differentiation, was identified by specific patterns of copy number gains of genomic regions located at chromosomes 8q, 1q, 3q and 7q. Androgen ablation therapy was further characterised by copy gain at chromosomes 2p and 10q. In conclusion, patterns of allelic imbalance were discovered in PCa, consisting allelic loss as an early event in tumour development, and distinct patterns of allelic amplification related to tumour progression and poor differentiation.
| S-EPMC2360016 | biostudies-literature
Project description:The data were used to define the homozygous regions in OCD-risk breeds, together with published Gentrain dataset.
2013-12-23 | GSE53577 | GEO
Project description:Background: The high incidence of recurrence and unpredictable clinical outcome for paediatric ependymoma reflect the imprecision of current therapeutic staging and need for novel risk stratification markers. Gain of chromosome 1q has been reported as a frequent aberration and correlate of adverse outcome in ependymoma. We therefore evaluated a prognostic role for 1q25 gain across three age-defined European clinical trial cohorts of paediatric intracranial ependymoma. Methods: The frequency of 1q gain in paediatric ependymoma was assessed across 51 tumours (42 primary, 9 recurrent) using Affymetrix® 500K SNP arrays. Gain of 1q25 was evaluated by interphase FISH (iFISH) across 189 primary intracranial ependymomas from children treated on the CCLG/SIOP CNS9204 (n = 60) and BBSFOP (n = 65) adjuvant chemotherapy trials, or with primary post-operative radiotherapy (SIOP CNS9904/RT group, n = 64). Results were correlated with clinical, histological and survival data. Findings: Gain of 1q was the most frequent imbalance in primary (7/42, 17 %) and recurrent ependymomas (3/9, 33 %). Gain of 1q25 was the strongest independent predictor of tumour progression in both CNS9204 (HR 3·36, p = 0·0009) and BBSFOP (HR 4·10, p = 0·0009) trial cohorts. In contrast, 1q25 gain was not prognostic for the older CNS9904/RT only group (PFS: p = 0·37, OS: p = 0·95). Clinical variables implicated in adverse outcome amongst cohorts included incomplete tumour resection and posterior fossa location. Interpretation: This is the first study to prospectively identify then validate a prognostic genomic marker for childhood ependymoma across independent prospective trial groups. 1q25 gain predicts progression in primary chemotherapy cohorts but not those treated by post-operative radiotherapy. We propose 1q25 gain is incorporated as an adverse marker into future European chemotherapeutic clinical trial design.
2012-02-09 | GSE32101 | GEO
Project description:This data was used to identify regions of the genome that have undergone positive selection in a high-altitude Tibetan population.
2010-07-22 | GSE21661 | GEO