4075 results for "*geneti*"

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• Her2 BC WGS dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001334

• Triple Negative BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001335

• Xenograft BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001336

• BASIS BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001337

• BC WGS Dataset

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001338

• Triple Negative BC RNA Sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001339

• Breast RNA Sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001340

• BASIS RNA Sequencing

  We propose to definitively characterise the somatic genetics of breast cancer through generation of comprehensive catalogues of somatic mutations in breast cancer cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Dataset EGAD00001001341

• Institut Curie Neuroblastoma Whole Genome Sequencing Diagnosis Relapse

  Neuroblastoma, a clinically heterogeneous pediatric cancer, is characterized by distinct genomic profiles but few recurrent mutations. As neuroblastoma is expected to have high degree of genetic heterogeneity, study of neuroblastoma's clonal evolution with deep coverage whole-genome sequencing of diagnosis and relapse samples will lead to a better understanding of the molecular events associated with relapse. Samples were included in this study if sufficient DNA from constitutional, diagnosis and relapse tumors was available for WGS. Whole genome sequencing was performed on trios (constitutional, diagnose and relapse DNA) from eight patients using Illumina Hi-seq2500 leading to paired-ends (PE) 90x90 for 6 of them and 100x100 for two. Expected coverage for sample NB0175 100x100bp was 30X for tumor and constitutional samples. For the seven other patients expected coverage was 80X for tumor samples with PE 100x100, 100X in the other tumor samples and 50X for all constitutional samples (see table 1). Following alignment with BWA (Li et al., Oxford J, 2009 Jul) allowing up to 4% of mismatches, bam files were cleaned up according to the Genome Analysis Toolkit (GATK) recommendations (Van der Auwera et al., Current Protocols in Bioinformatics, 2013, picard-1.45, GenomeAnalysisTK-2.2-16). Variant calling was performed in parallel using 3 variant callers: GenomeAnalysisTK-2.2-16, Samtools-0.1.18 and MuTect-1.1.4 (McKenna et al., Genome Res, 2010; Li et al., Oxford J, 2009 Aug; Cibulskis et al., Nature, 2013). Annovar-v2012-10-23 with cosmic-v64 and dbsnp-v137 were used for the annotation and RefSeq for the structural annotation. For GATK and Samtools, single nucleotide variants (SNVs) with a quality under 30, a depth of coverage under 6 or with less than 2 reads supporting the variant were filter out. MuTect with parameters following GATK and Samtools thresholds have been used to filter our irrelevant variants. .SNVs within and around exons of coding genes overlapping splice sites.. Then,variants reported in more than 1% of the population in the 1000 genomes (1000gAprl_2012) or Exome Sequencing Project (ESP6500) have been discarded in order to filter polymorphisms. Finally, synonymous variants were filtered out. MuTect focuses on somatic by filtering with constitutional sample. Mpileup comparison between constitutional and somatic DNAs allowed us to focus also on tumor specific SNVs with GATK and Samtools. Finally, every SNV called by our pipeline and also supported in any constitutional samples were filtered our in order to prevent putative constitutional DNA coverage deficiency. Then we analyzed CNVs (copy number variants) with HMMcopy-v0.1.1 (Gavin et al., Genome Res, 2012) and control-FREEC-v6.7 (Boeva et al., Bioinformatics 2011) with a respective window of 2000bp and 1000 bp, and auto-correction of normal contamination of tumor samples for Control-FREEC. Finally we explored Structural variants (SVs) including deletions, inversions, tandem duplications and translocations using DELLY-v0.5.5 with standard parameters (Rausch et al., Oxford J, 2012). In tumors, at least 10 supporting reads were required to make a call and 5 supporting reads for the sample NB0175 with a coverage of only 40X (see table 2). To predict SVs in constitutional samples for subsequent somatic filtering, only 2 supporting reads were required in order not to miss one. To identify somatic events, all the SVs in each normal sample were first flanked by 500 bp in both directions and any SVs called in a tumor sample which was in the combined flanked regions of respective normal sample was removed (see graph 1). Deletions with more than 5 genes impacted or larger than 1Mb and inversions or tandem duplications covering more than 4 genes, were removed. We focused on exonic and splicing events for deletions, inversions, and tandem duplications. For translocation, we keep all SVs that occurred in intronic, exonic, 5'UTR, upstream or splicing regions. Bioinformatics detection of variations with Deep sequencing approach Once PE reads merged and adaptors trimmed by SeqPrep with default parameters, merged reads were aligned via the BWA (Li H. and Durbin R. 2009 PMID 19451168) allowing up to 1 differences in the 22-base-long seeds and reporting only unique alignments. Only reads having a mapping quality 20 or more have been further analysed. Variant calling software was not used, since we aimed to predict variations at low frequencies, observed in less than 1% of reads. Such variants require a custom approach. Using DepthOfCoverage functions of the Genome Analysis Toolkit (GATK) v2.13.2 (McKenna A, et al., 2010 Genome Research PMID: 20644199), we focused on high quality coverage of bases A, C, G and T at the targeted variant position. Depth of coverage of each base following a mapping quality higher than 20 and a base quality higher than 10 have been taken into account in order to focus only on high quality data. Aiming to determine the background level of variability at the studied regions, 10 control samples were included in the analysis. The same approach and filtering criteria have been applied as introduced above over the entire amplicons. In order to highlight variants, for each sample the frequencies of each bases at each amplicon position were then compared to those observed in the set of controls. Statistical analyses were performed with the R statistical software (http://www.R-project.org). Fisher’s exact two-sided tests with a Bonferroni correction were performed to compare percentages of bases between the data sets, i.e. for a given base between a case and the controls. Finally, significant variations were filtered-in once (i) a significant increase in the percentage of avariant base and (ii) a significant decrease in the percentage of it's reference base following our p.values criteria was observed (p.val < 0.05).

  Dataset EGAD00001001356

• Neuroblastoma relapse trio series from the AMC

  The majority of neuroblastoma patients have tumors that initially respond to chemotherapy, but a large proportion of patients will experience therapy-resistant relapses. The molecular basis of this aggressive phenotype is unknown. Whole genome sequencing of 23 paired diagnostic and relapsed neuroblastomas showed clonal evolution from the diagnostic tumor with a median of 29 somatic mutations unique to the relapse sample. Eighteen of the 23 relapse tumors (78%) showed RAS-MAPK pathway mutations. Seven events were detected only in the relapse tumor while the others showed clonal enrichment. In neuroblastoma cell lines we also detected a high frequency of activating mutations in the RAS-MAPK pathway (11/18, 61%) and these lesions predicted for sensitivity to MEK inhibition in vitro and in vivo. Our findings provide a rationale for genetic characterization of relapse neuroblastoma and show that RAS-MAPK pathway mutations may function as a biomarker for new therapeutic approaches to refractory disease.

  Dataset EGAD00001001360

• Egypt Genome Project - low coverage whole genome sequencing

  All humans outside Africa are descendants of the same single exit, usually dated at 50-70 thousand years ago. However, the route taken out of Africa is still debated. The two main candidates are a northern route via Egypt and the Levant, or a southern route via Ethiopia and the Arabian Peninsula. We are generating genetic data to evaluate these two possibilities. In this study we propose to generate low-coverage sequencing data for 100 Egyptian samples.

  Dataset EGAD00001001372

• Genetic and epigenetic characterization of adenoid cystic carcinoma

  Whole genome sequences of ACC primagrafts, Histone modification maps and transcription factor binding maps for ACC primagrafts and primary tumors. Processed ChIP-seq data is available on GEO under accession number GSE76465.

  Dataset EGAD00001001662

• Low coverage whole-genome sequencing of samples from the Cretan Greek isolate collection HELIC-MANOLIS

  Whole-genome sequencing at 1x of samples from the Cretan Greek isolate collection HELIC-MANOLIS. Genome-wide association studies of complex traits have been successful in identifying common variant associations, but a substantial heritability gap remains. The field of complex trait genetics is shifting towards the study of low frequency and rare variants, which are hypothesised to have larger effects. The study of these variants can be empowered by focusing on isolated populations, in which rare variants may have increased in frequency and linkage disequilibrium tends to be extended. This work focuses on an isolated population from Crete, Greece. Sequencing is very efficient in isolated populations, because variants found in a few samples will be shared by others in extended haplotype contexts, supporting accurate imputation.

  Dataset EGAD00001001637

• Independent development of lymphoid and histiocytic malignancies from a shared early precursor

  Whole Exome Sequencing data from the germline of the patient as well as the tumors in bone marrow (T-ALL), Liver (Histiocytic Sarcoma) and ileum (non-Langerhans Cell Histiocytosis).

  Dataset EGAD00001001596

• Sequence Data for Paper: Epigenetic reprogramming during differentiation of human CD4+ T lymphocytes into memory stages

  Sequence Data of total RNA, miRNA, WGB, mRNA, NOMe, Chip (H3K27ac,H3K27me, H3K36me3, H3K4me1, H3K4me3, H3K9me3, Input) Short Desrciption: Epigenetic profiling of human CD4+ memory T cells reveals their proliferative history and argues in favor of a progressive differentiation model driven by epigenetically controlled master regulators.

  Dataset EGAD00001001865

• BLUEPRINT Epigenetic characterization of megakaryocytes and erythroblasts

  Megakaryocytes and erythroblasts derive from the same progenitor cell type but carry out very different functions. In order to understand how the different functional phenotypes arise we have characterised the epigenetic landscape of these cells.

  Dataset EGAD00001001871

• Integrative genome profiling in AML

  AML emerges as a consequence of accumulating independent genetic aberrations that direct regulation and/or dysfunction of genes resulting in aberrant activation of signalling pathways, resistance to apoptosis and uncontrolled proliferation. Given the significant heterogeneity of AML genomes, AML patients demonstrate a highly variable response rate and poor median survival in response to current chemotherapy regimens. For the past 4 years we have conducted gene expression profiling on purified bone marrow populations equating to normal haematopoietic stem and progenitor cells from healthy subjects and patients with de novo AML in order to identify AML signatures of aberrantly expressed genes in cancer versus normal. We are now applying a series of bioinformatic methodologies combined with clinical and conventional diagnostic data to establish novel genomics strategies for improved prognostication of AML. Additionally, we use our AML signatures to unravel oncogenic signalling pathway activities in AML patients and test inhibitory drugs for these pathways inn preclinical therapeutic programmes. We consider that superimposing GEP and clinical data for our AML patient cohort with additional data on their mutational status will significantly improve the prognostic power of the study as well as unravel yet unknown mutations associated with aberrant signalling activities of oncogenic pathways.

  Dataset EGAD00001001873

• 33 patients with Monoclonal Gammopathy of Undetermined Significance (MGUS)

  Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant precursor of multiple myeloma (MM) with a 1% risk of progression per year. Although targeted analyses have shown the presence of specific genetic abnormalities such as IGH translocations, RB1 deletion, 1q gain, hyperdiploidy or RAS genes mutations, little is known about molecular mechanism of malignant transformation. We have performed whole exome sequencing together with SNP array analysis in 33 flow-cytometry separated abnormal PC samples of MGUS patients to describe somatic gene mutations and chromosome changes at the genome-wide level. Non-synonymous mutations (NS-SNVs) and copy number alterations (CNAs) were present in 97.0% and in 63.6% of cases, respectively. Importantly, the number of somatic mutations was significantly lower in MGUS compared to MM (p<10-4) and we have identified 6 myeloma significantly mutated genes which are KRAS, NRAS, DIS3, HIST1H1E, EGR1 and LTB in the MGUS dataset. We also found a positive correlation with increasing chromosome changes and somatic mutations. IGH translocations were present in 27.3% of cases comprising t(4;14), t(11;14), t(14;16) or t(14;20) and were in a similar frequency to MM, which corresponded with primary lesion hypothesis. Data from this study showed MGUS is a genetically comprehensive disease, however overall genetic instability is significantly lower compared to MM.

  Dataset EGAD00001001901

• GILD-ExomeSeq-PTNHL

  This study is meant to gain further knowledge in haematological cancers. Patients samples (mainly DNAs or PCR products) from haematolocical cancer patients will be sequenced, and the outputs will be correlated to their diagnosis and/or prognosis; the findings may also add more insight into the understanding of biology in this type of tumour. We will be sequencing Primary Testicular Lymphomas (PTL) to identify genetic drivers of this rare cancer

  Dataset EGAD00001001986

• March 2016 update of Whole genome bisulfite sequencing assay data (bams) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  March 2016 update of Whole genome bisulfite sequencing assay data (bams) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001987

• Non-ADT METs ICGC Prostate UK

  To characterize the subclonal genomic architecture of non-androgen-deprived metastatic prostate cancer, we performed whole-genome sequencing (WGS) of pelvic lymph node metastases and matching noncancerous blood from 10 patients to an average sequencing depth of 55x. The patients are part of PELICAN (Project to ELIminate Lethal Cancer) study led by G. Steven Bova at Johns Hopkins University (USA) and Tampere University (Finland). As of September 2020, study using these data is: Wedge et al, Nature Genetics 2018 (PMID: 29662167)

  Dataset EGAD00001002002

• Ashkenazi Jewish Leukoencephalopathy Syndrome

  Using whole exome sequencing (WES), we identified homozygosity for a missense variant, VPS11: c.2536T>G (p.C846G), as the genetic cause of a leukoencephalopathy syndrome in two individuals from two unrelated Ashkenazi Jewish (AJ) families. Both patients exhibited highly concordant disease progression characterized by infantile onset leukoencephalopathy with brain white matter abnormalities, severe motor impairment, cortical blindness, intellectual disability, and seizures.

  Dataset EGAD00001002005

• Characterisation of the genomic landscape of CRLF2-d ALL

  To determine the clinical and genetic landscape of CRLF2 deregulated acute lymphoblastic leukaemia (CRLF2-d ALL). We identified 172 patients with a CRLF2 rearrangement treated on either the UKALL2003 trial for children and adolescents (1-24 years) or the UKALLXII trial for adolescents and adults (15-59 years). Genomic technologies from conventional karyotyping, and FISH through to whole genome and exome sequencing were used to characterise the genomes of patients with CRLF2-d ALL. This is the largest study to date to investigate the genomic landscape of CRLF2-d ALL and define CRLF2-d as a unique subgroup of B-other ALL. We have confirmed the high incidence of CRLF2-d in Down syndrome-ALL and demonstrated the co-existence of CRLF2-d with other primary chromosomal rearrangements, suggesting that in these patients CRLF2-d can be a secondary genetic abnormality. Other defining features included enrichment of IKZF1, BTG1 and ADD3 deletions in IGH-CRLF2 patients and specific chromosomal gains seen at much higher frequencies than B-other ALL . We report recurrent established and new co-operating abnormalities and the novel involvement of USP9X and DDX3X in CRLF2-d ALL. It is clear from these data that CRLF2-d ALL is heterogenoeus, requiring a combination of genetic abnormalities in functionally relevent genes, to work alongside the deregulated expression of CRLF2 in order to initiate and drive leukaemogenesis in this subtype. Although the functional relevance of many of the abnormalities presented here are currently unknown, many are likely to activate alternate pathways or sensitize patients to current therapies.

  Dataset EGAD00001002007

• Characterisation of the genomic landscape of CRLF2-d ALL

  To determine the clinical and genetic landscape of CRLF2 deregulated acute lymphoblastic leukaemia (CRLF2-d ALL). We identified 172 patients with a CRLF2 rearrangement treated on either the UKALL2003 trial for children and adolescents (1-24 years) or the UKALLXII trial for adolescents and adults (15-59 years). Genomic technologies from conventional karyotyping, and FISH through to whole genome and exome sequencing were used to characterise the genomes of patients with CRLF2-d ALL. This is the largest study to date to investigate the genomic landscape of CRLF2-d ALL and define CRLF2-d as a unique subgroup of B-other ALL. We have confirmed the high incidence of CRLF2-d in Down syndrome-ALL and demonstrated the co-existence of CRLF2-d with other primary chromosomal rearrangements, suggesting that in these patients CRLF2-d can be a secondary genetic abnormality. Other defining features included enrichment of IKZF1, BTG1 and ADD3 deletions in IGH-CRLF2 patients and specific chromosomal gains seen at much higher frequencies than B-other ALL . We report recurrent established and new co-operating abnormalities and the novel involvement of USP9X and DDX3X in CRLF2-d ALL. It is clear from these data that CRLF2-d ALL is heterogenoeus, requiring a combination of genetic abnormalities in functionally relevent genes, to work alongside the deregulated expression of CRLF2 in order to initiate and drive leukaemogenesis in this subtype. Although the functional relevance of many of the abnormalities presented here are currently unknown, many are likely to activate alternate pathways or sensitize patients to current therapies.

  Dataset EGAD00001002008

• Low-depth whole genome sequencing across multiple isolated populations

  Isolated populations have unique population genetics characteristics that can help boost power in genetic association studies for complex traits. Leveraging these advantageous characteristics requires an in-depth understanding of parameters that have shaped sequence variation in isolates. This study performs a comprehensive investigation of these parameters using low-depth whole genome sequencing (WGS) across multiple isolates.

  Dataset EGAD00001002014