Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA148397 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The aim of this study is to determine copy number variations in the multiple myeloma patients, which were positive for BCL1/JH t(11;14)(q13;q32) translocation. Identification of common chromosomal aberrations representing the t(11;14)(q13;q32) subtype is possible by comparing the microarray data across all the samples under studied. Eight multiple myeloma samples were analyzed. Each sample was compared against normal control (match with patient's race and gender), which was pooled from ten healthy individuals.
2012-12-31 | E-GEOD-33757 | biostudies-arrayexpress
Project description:The aim of this study is to determine copy number variations in the multiple myeloma patients, which were positive for BCL1/JH t(11;14)(q13;q32) translocation. Identification of common chromosomal aberrations representing the t(11;14)(q13;q32) subtype is possible by comparing the microarray data across all the samples under studied.
2012-12-31 | GSE33757 | GEO
Project description:Integrated genomics approach to detect allelic imbalances in multiple myeloma
| PRJNA123167 | ENA
Project description:Integrated genomics approach to detect allelic imbalances in multiple myeloma, SNP data
| PRJNA122809 | ENA
Project description:A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: an integrated genomics approach reveals a wide dosage effect on gene and microRNA expression This SuperSeries is composed of the following subset Series: GSE13591: Integrated genomics approach to detect allelic imbalances in multiple myeloma GSE16121: Integrated genomics approach to detect allelic imbalances in multiple myeloma, SNP data Refer to individual Series
2009-05-16 | E-GEOD-16122 | biostudies-arrayexpress
Project description:A SNP microarray and FISH-based procedure to detect allelic imbalances in multiple myeloma: an integrated genomics approach reveals a wide dosage effect on gene and microRNA expression Multiple myeloma (MM) is characterized by marked genomic instability. Beyond structural rearrangements, a relevant role in its biology is represented by allelic imbalances leading to significant variations in ploidy status. To better elucidate the genomic complexity of MM, we analyzed a panel of 45 patients using combined FISH and microarray approaches. Using a self-developed procedure to infer exact local copy numbers for each sample, we identified a significant fraction of patients showing marked aneuploidy. A conventional clustering analysis showed that aneuploidy, chromosome 1 alterations, hyperdiploidy and recursive deletions at 1p and chromosomes 13, 14 and 22 were the main aberrations driving samples grouping. Then, we integrated mapping information with gene and microRNAs expression profiles: a multiclass analysis of the identified clusters showed a marked gene-dosage effect, particularly concerning 1q transcripts, also confirmed by correlating gene expression levels and local copy number alterations. A wide dosage effect affected also microRNAs, indicating that structural abnormalities in MM closely reflect in their expression imbalances. Finally, we identified several loci in which genes and microRNAs expression correlated with loss-of-heterozygosity occurrence. Our results provide insights into the composite network linking genome structure and gene/microRNA transcriptional features in MM. Keywords: Integrated genomics approach based on SNP microarray and FISH procedures to detect allelic imbalances in multiple myeloma.
2009-05-16 | GSE16121 | GEO
Project description:Genomic analysis of Multiple Myeloma using RNA Sequencing
| PRJNA271873 | ENA
Project description: Not available
| S-EPMC2531291 | biostudies-literature