M.pneumoniae - Whole organism, Copy per cell, cpc normalized data (Kuhner,science,2009)
Ontology highlight
ABSTRACT:
ORGANISM(S): 722438
SUBMITTER: 
Christian von Mering
PROVIDER: 259848635 | PAXDB | 2009
REPOSITORIES: PAXDB
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| bioprojects-abundance-files-v4.0.zip | Other |
Items per page: 5 1 - 1 of 1 |
Similar Datasets
Project description:Copy Number Variation data from non-trasformed human fibroblasts
| PRJNA967026 | ENA
Project description:DNA hypomethylation could lead to activation of alternate promoters in GBM. We profiled DNA methylation and H3K4me3 genome-wide, and also performed expression and copy number analysis on the same samples In this dataset, we include all array CGH copy number data obtained for five GBMs. We used estimated copy number to normalize sequencing-based methylation data.
2013-08-13 | GSE49808 | GEO
Project description:Insertions of endogenous retroviruses cause a significant fraction of mutations in inbred mice but not all strains are equally susceptible. Notably, most new Intracisternal A particle (IAP) ERV mutagenic insertions have occurred in C3H mice. We show here that strain-specific insertionally polymorphic IAPs have accumulated faster in C3H/HeJ mice relative to other strains and that IAP transcript levels are higher in C3H/HeJ embryonic stem (ES) cells compared to other ES cells. To investigate the mechanism for high IAP activity in C3H mice, we identified 61 IAP copies in C3H/HeJ ES cells enriched for H3K4me3 (a mark of active promoters) and, among those tested, all are unmethylated in C3H ES cells. Notably, 13 of the 61 are specific to C3H/HeJ and are members of the non-autonomous 1Δ1 IAP subfamily that is responsible for nearly all new insertions in C3H. One copy is full length with intact open reading frames and hence potentially capable of providing proteins in trans to other 1Δ1 elements. This potential “master copy” is present in other strains, including 129, but its 5’ long terminal repeat (LTR) is methylated in 129 ES cells. Thus, the unusual IAP activity in C3H may be due to reduced epigenetic repression coupled with the presence of a master copy.
2020-06-10 | GSE152208 | GEO
Project description:DNA hypomethylation could lead to activation of alternate promoters in GBM. We profiled DNA methylation and H3K4me3 genome-wide, and also performed expression and copy number analysis on the same samples In this dataset, we include all array CGH copy number data obtained for five GBMs. We used estimated copy number to normalize sequencing-based methylation data. Five total samples were analyzed.
2013-08-13 | E-GEOD-49808 | biostudies-arrayexpress
Project description:Soft tissue sarcomas (STS) often present a significant diagnostic challenge as many STS bear histologic resemblance, but are known to have very different clinical and biologic characteristics. Some STS subtypes are characterized by specific genetic abnormalities and this has helped in their classification, diagnosis and even treatment. However, a large majority of STS have no known specific genetic aberrations even though they almost always have highly aberrant karyotypes. We therefore hypothesize that the latter subgroup of STS bear genetic abnormalities that are sub-type specific, but as yet unidentified. High-resolution mapping of copy number aberrations in cancer genomes is a valuable way of identifying recurrent genomic changes that could be of pathogenetic significance. Traditionally, this has been done using high quality DNA obtained from fresh frozen tissue or cells and archived tissue is generally regarded as unsuitable because of the degradative effects of formalin fixation on DNA. Utility of archival tumour material for such molecular genetic analysis is vital, especially for rare cancers like STS but recent efforts to accomplish this have produced variable results. We therefore set out, in addition to optimize a protocol for obtaining genomic copy number data from formalin-fixed, paraffin-embedded (FFPE) STS material that is comparable to that from fresh frozen (FF) material. Microarray-based Comparative Genomic Hybridization (aCGH), a high- resolution, genome-wide method was used to identify somatic copy number aberrations (SCNAs) in primary STS samples (fresh frozen and archival FFPE), using an optimized protocol for labeling DNA. Findings were confirmed using Conventional Cytogenetics and Fluorescence in-situ Hybridization (FISH). Data obtained from paired samples (FF and FFPE) of the same tumours showed similar results and array results were consistently of good quality. On-going analysis of the recurrent SCNAs in combination with expression data and clinical correlates may serve to identify specific patterns that can serve as diagnostic markers, characterize subgroups with prognostic implication or identify potential therapeutic targets.
2015-07-24 | GSE39663 | GEO
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 46 archived frozen tumor samples collected from Department of Obstetrics and Gynecology, Tri-Service General Hospital, Taiwan, containing 9 clear cell, 6 mucinous, and 31 serous. Data was pre-processed and normalized with Hapmap CHB using the Affymetric Genotyping Console.
2012-10-25 | E-GEOD-30300 | biostudies-arrayexpress
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 56 samples containing the 4 histotypes were used for this study. It contained 12 clear cell carcinoma, 6 endometrioid adenocarcinoma, 2 mucinous adenocarcinoma, 5 mucinous-borderline tumors, 26 serous adenocarcinoma, and 5 serous-borderline tumors. Data was pre-processed and normalized with Hapmap JPT using the Affymetric Genotyping Console.
2012-10-25 | E-GEOD-30283 | biostudies-arrayexpress
Project description:Integrated profiling of somatic molecular alterations present in tumors is necessary to further our understanding of the tumorigenic process. We investigated the potential relationships between gene copy number alterations and DNA methylation profiles in a case series of pleural mesotheliomas (n=23). Gene copy number (CN) alterations profiled with 500K SNP arrays and DNA methylation measured at over 750 cancer-related genes with methylation bead-arrays were examined concomitantly. Considering each probed locus, there were no instances of significantly correlated CN alteration and methylation (no loci with Q < 0.05) and averaging loci over their associated genes revealed only two genes with significantly correlated CN and methylation alterations (Q < 0.04). In contrast to the lack of discrete correlations, the overall extent of tumor CN alteration was significantly associated with DNA methylation profile when comparing CN alteration extent among methylation profile classes (P < 0.02), and there was evidence that this association was partially attributable to prevalent allele loss observed at the maintenance DNA methyltransferase DNMT1. Taken together, this work indicates a strong association between global genetic and global epigenetic dysregulation in mesothelioma rather than a discrete, local coordination of gene inactivation, and further highlights the utility and necessity of integrative genomics approaches in cancer biology. From the total study population, 23 tumors from the incident case series were chosen for copy number alteration profiling by hybridizing 5ml containing ⥠50ng/ml of tumor or matched peripheral blood DNA to each of the two GeneChips® that comprise the Human Mapping 500K single-nucleotide polymorphism array set (Affymetrix, Santa Clara, CA), following manufacturer protocols and standard operating procedures at the Harvard Partners Microarray Core servicing facility. Probe intensities at each locus were determined in the GCOS software and genotypes calls were generated using the Genotyping Analysis Software (Affymetrix). Probe signals were normalized to their matched referent peripheral blood sample data using the Copy Number Analysis Tool v4.0.1 software (CNAT) (Affymetrix) with median scaling and default tuning parameters, and copy number states were inferred by Hidden Markov Model analysis. The supplementary file 'GSE21057_tumor_copy_number.txt' contains the (blood-normalized) copy number calls for each tumor sample.
2010-07-31 | E-GEOD-21057 | biostudies-arrayexpress
Project description:High-grade osteosarcoma is a tumor with a complex genomic profile, occurring primarily in adolescents with a second peak at middle age. The extensive genomic alterations obscure the identification of genes driving tumorigenesis during osteosarcoma development. In order to identify such driver genes, we integrated DNA copy number profiles (Affymetrix SNP 6.0) of 32 diagnostic biopsies with 84 expression profiles (Illumina Human-6 v2.0) of high-grade osteosarcoma as compared with its putative progenitor cells, i.e. mesenchymal stem cells (n=12) or osteoblasts (n=3). In addition, we performed paired analyses between copy number and expression profiles of a subset of 29 patients for which both DNA and mRNA profiles were available. Integrative analyses were performed in Nexus Copy Number software and statistical language R. Paired analyses were performed on all probes detecting significantly differentially expressed genes in corresponding LIMMA analyses. For both non-paired and paired analyses, copy number aberration frequency was set to >35%. Non-paired and paired integrative analyses resulted in 45 and 101 genes, respectively, which were present in both analyses using different control sets. Paired analyses detected >90% of all genes found with the corresponding non-paired analyses. Remarkably, approximately twice as many genes as found in the corresponding non-paired analyses were detected. Affected genes were intersected with differentially expressed genes in osteosarcoma cell lines, resulting in 31 new osteosarcoma driver genes. Cell division related genes, such as MCM4 and LATS2, were overrepresented and genomic-instability was predictive for metastasis-free survival, suggesting that deregulation of the cell cycle is a driver of osteosarcomagenesis. This SuperSeries is composed of the following subset Series: GSE28974: Genome-wide gene expression profiling of mesenchymal stem cells GSE33153: Copy number analysis of high-grade osteosarcoma GSE33382: Genome-wide gene expression analysis of high-grade osteosarcoma For data processing, we refer to the individual series. We performed both non-paired and paired integrative analyses on SNP and gene expression data. Non-paired integrative analysis was performed by importing lists of differentially expressed genes into the Copy Number module of Nexus software version 5 (BioDiscovery, CA). Based on the length of the gene list, Nexus software performs a Fisher's exact test in order to determine whether the number of differentially expressed genes in a specific region with a significant copy number alteration is larger than expected by chance. Genes present in such regions of copy number alteration with FDR-adjusted P-values (Q-bounds in Nexus software) < 0.05 were returned from this integrative analysis. Nexus software only reports genes which are both gained and overexpressed, or both deleted and downregulated. For the paired integrative analysis, copy number data of all autosomal overlapping genes between the copy number and gene expression arrays were exported from Nexus software, and converted into a binary file containing all genes with a gain (1) and no gain (0), and a similar binary file for losses. As in the non-paired integrative analysis, we did not apply any restrictions on the size of copy number alterations. Gene expression data of each probe for each sample were normalized against average gene expression of the corresponding probes over all control samples (either expression data from 12 MSCs, or from 3 osteoblasts). This was performed by subtracting the average expression of the control samples from the expression levels of the sample of interest, since these are log-transformed expression values. For both analyses, only genes that were significantly differentially expressed between the 84 osteosarcoma samples and the specific control set were analyzed, in order to make sure that no genes returned from the integrative analysis were not significantly differentially expressed. Subse quently, genes that overlapped between the copy number binary files and that matched the fold change of expression (upregulation for genes with gains, and downregulation for genes with losses) were returned.
2012-03-27 | E-GEOD-33383 | biostudies-arrayexpress