16758 results for "sec+and+unspecified+malignant+neoplasm"

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• TSCA-LI amplicon sequencing of called variants in WXS data of DSALL.

  Targeted resequencing of samples was done with TruSeq custom amplicon low input kit (TSCA-LI, Illumina). The oligo capture probes were designed to include a prefix of 8 random nucleotides at the 5 end of each probe. The assay is designed such that each targeted locus is annealed with two probes, resulting in amplicons tagged with unique molecular identifiers (UMI) (22) of 16 bases. Raw FASTQ sequencing files were processed as following: (a) The first 8 bases were trimmed from each read and recorded with the corresponding base quality scores (BQ) in the attribute field. (b) Reads were aligned with BWA. (c) First round of PCR duplicate cleaning was performed with picard tools markDuplicates using the parameters BARCODE_TAG=BC TAGGING_POLICY=All REMOVE_DUPLICATES=true (d) Since in the previous step only duplicate reads with identical UMIs were removed, a second pass of filtering was done. Reads with identical mapping were considered unique only if their corresponding UMIs were different in at least 3 positions (i.e., UMI edit distance > 2). (e) Paired-end read pairs overlapping genomic positions were clipped to avoid overestimation of the sequencing coverage using bamUtils clipOverlap.

  Dataset EGAD00001003275

• Sequencing data for oesophageal and related samples - ICGC DCC release 27 earmarked (WGS)

  WGS sequencing for 63 cases (126 samples) from the ICGC ESAD-UK project Tumours 50x Normals 30x HiSeq X BAM files These samples are earmarked for inclusion in ICGC release 27 (deferred to release 28)

  Dataset EGAD00001004028

• Phenotype Risk Scores Identify Patients with Unrecognized Mendelian Disease Patterns

  This study was designed to assess the phenotypic effects of rare variants. Rare variants are difficult to study in a high-throughput manner because most cohorts are underpowered to detect associations. In order to gain power to test rare variants, we use Phenotype Risk Scores (PheRS) based on features of Mendelian diseases. PheRS is calculated using claims data from an EHR that is mapped to clinical features from OMIM's clinical descriptions of Mendelian disease. We calculated PheRS for 1,204 Mendelians diseases in a cohort of 21,701 individuals genotyped on the HumanExome BeadChip. We then tested for association between these diseases and rare variants in causal genes. A phenotype risk score is calculated as the weighted sum of features for a given disease. The features are defined as a set of phecodes (consolidated ICD codes) associated with a particular Mendelian disease as described in OMIM. The weights for each phecode are calculated as the log inverse prevalence of the phecode in our cohort. For an individual, their score equals the sum of the weights for each phecode that is present in their medical record. Our study was based on a cohort of individuals with genotype data linked to de-identified electronic health records (EHR) from Vanderbilt's BioVU resource. We hope that this method will help generate phenotype-genotype correlation data on rare variants which in turn may inform rare variant interpretations use for diagnostics.

  Study phs001516

• EGAD00010000246

  Coeliac disease cases and control samples. (1958BC samples excluded)

  Dataset EGAD00010000246

• Genetic-epigenetic tissue mapping for plasma DNA: applications in prenatal testing, transplantation and oncology

  We developed Genetic-Epigenetic Tissue Mapping (GETMap) to determine the tissue composition of plasma DNA carrying genetic variants not present in the constitutional genome through comparing their methylation profiles with relevant tissues.

  Dataset EGAD00001007041

• High titers and low fucosylation of early phase anti-SARS-CoV-2 IgG promote hyper-inflammation by alveolar macrophages

  We show that early phase anti-Spike IgG in serum of critically ill COVID-19 patients induces hyper-inflammatory responses by human alveolar macrophages. We identified that this excessive inflammatory response is dependent on two antibody features that are specific for severe COVID-19. First, inflammation is driven by high titers of anti-Spike IgG, a hallmark of severe disease. Second, we found that anti-Spike IgG from severely ill patients is intrinsically more pro-inflammatory because of different glycosylation of the Fc tail, particularly by low fucosylation. This dataset is linked with the following ArrayExpress Experiment: E-MTAB-10431 - 2020_COVID19_FCGR_MIL10_IgGfucosylation

  Study EGAS00001005206

• Next Generation Children project

  Whole genome sequencing of sick children in neonatal and paediatric intensive care units, aligned to reference assembly GRCh37.

  Dataset EGAD00001007780

• Papua New Guinean Genome Diversity Project (PGDP)

  The PGDP dataset includes 58 whole genome sequences for Papua New Guinean individuals from different locations. DNA was extrated from saliva samples (Oragen kit). Sequencing libraries were prepared using the TruSeq DNA PCR-Free HT kit. 150 bp paired-end sequencing was performed on the Illumina HiSeq X5 sequencer. The PGDP dataset provides Fastq and BAM files.

  Dataset EGAD00001007783

• Neuroblastoma patient Total RNA Seq data

  Tumor Total RNA Seq data of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.

  Dataset EGAD00001008124

• Multiregional single cell RNA sequencing of human renal cell carcinoma

  The dataset comprises of 5' single cell RNA sequencing with TCR enrichment with 10x Genomics' Chromium technology of multiregional biopsies of human renal cell carcinomas. Biopsies from different tumour regions, the tumour-normal interface, normal kidney, normal adrenal, metastatic regions, peri-nephric fat, and peripheral blood were sequenced from 12 patients with kidney tumours.

  Dataset EGAD00001008030