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

in 82.19 milliseconds.

• Chordoma Targeted Sequencing Study

  This Study uses a focused bespoke bait pull down library method to target findings of Chordoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Dataset EGAD00001000267

• Meningioma Targeted Sequencing Study

  This Study uses a focused bespoke bait pull down library method to target findings of Meningioma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Dataset EGAD00001000273

• Whole Genome Sequencing of a secondary myelodysplastic syndrome (MDS)

  Illumina HiSeq sequence data (with >30x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009); duplicate reads were removed from the final BAM file. No realignment or recalibration was performed. Sample derived from secondary myelodysplastic syndrome (MDS), arising after treatment for medulloblastoma in an 11-year old female Li-Fraumeni syndrome case (LFS-MB1; Rausch et al., 2012; matching WGS data available under EGAS00001000085).

  Dataset EGAD00001000665

• Whole Exome DNA Sequencing of matched brain tumor-normal pairs

  Illumina HiSeq sequence data (with >80x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009); duplicate reads were removed from the final BAM file. No realignment or recalibration was performed.The whole exome sequencing data of 20 SHH medulloblastomas from phs000504.v1.p1 dataset has been used in our study on SHH medulloblastomas: http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000504.v1.p1

  Dataset EGAD00001000698

• Whole Genome DNA Sequencing of matched brain tumor-normal pairs (ICGC)

  Illumina HiSeq sequence data (with >30x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009); duplicate reads were removed from the final BAM file. No realignment or recalibration was performed.

  Dataset EGAD00001000697

• RNA-sequencing of primary urothelial bladder cancer samples

  Paired-end RNA-sequencing of tumour tissue samples (n=85) from primary urothelial bladder cancer patients. Sequencing was performed using either HiSeq (n=27) or NextSeq (n=58) Illumina platforms. Of the 85 samples, 78 are Non-muscle invasive (NMIBC) and 7 are Muscle invasive (MIBC).

  Dataset EGAD00001007005

• Location specific ACVR1, FGFR1 and TP53 mutations in pediatric glioblastomas in conjunction with H3.3 K27M.

  Recurrent somatic H3 K27M mutations characterize midline pediatric high-grade astrocytomas (pHGAs). In 40 treatment-naïve midline pHGAs we find additional somatic mutations specific to tumor location. Gain-of-function mutations in ACVR1 occur in tumors of the pons in conjunction with H3.1K27M, while FGFR1 mutations/fusions occur in thalamic tumors in conjunction with H3.3 K27M. Genetic profiles of pHGA show actionable targets, suggesting that pre-treatment biopsy could effectively orient therapeutic efforts.

  Study EGAS00001000720

• Fecal 16S UC sequencing data

  Fecal 16S-V4 rRNA gene sequence data from NCT02749630 ulcerative colitis patients. Stool samples were collected at screening as well as on days 29, 43, 64, 85, and 134 processed for 16SV4 rRNA gene sequencing

  Dataset EGAD00001008818

• Fecal 16S HV sequencing data

  Fecal 16S-V4 rRNA gene sequence data from NCT02749630 healthy volunteers. Stool samples were collected at screening as well as on days 29, 43, 64, 85, and 134 processed for 16SV4 rRNA gene sequencing

  Dataset EGAD00001008840

• cfMethyl-Seq

  cfMethyl-Seq libraries were generated for 479 cfDNA samples and were sequenced with 150 bp paired-end reads.

  Dataset EGAD00001009003

• Leiomyosarcoma Whole Genome Sequencing

  DNA was extracted from fresh frozen LMS material for 29 untreated tumors (24 primary tumors, 5 metastatic 13 relapses) and 13 tumors treated with radiation (7 primaries, 6 metastatic relapses). DNA from matched blood was used as a normal reference. Whole-genome sequencing was performed using established protocols on Illumina instruments.

  Dataset EGAD00001007722

• OSTEOMICS_RNA

  RNA sequencing of 79 libraries were prepared, from sample of Osteosarcoma tumors biopsied at diagnosis, with TruSeq Stranded mRNA kit following recommendations: the key steps consist of PolyA mRNA capture with oligo dT beads using 1µg total RNA, fragmentation to approximately 400pb, DNA double strand synthesis, and ligation of Illumina adaptors amplification of the library by PCR for sequencing. Libraries sequencing was performed using Illumina sequencers (NextSeq 500 or Hiseq 2000/2500/4000) in 75 bp paired-end mode.

  Dataset EGAD00001008213

• Ither2 WXS dataset - Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment.

  Dataset EGAD00001010178

• Ither2 RNA-Seq dataset - Implementation of pediatric precision oncology into clinical practice: The individualized Therapies for Children with cancer program “iTHER”

  iTHER is a prospective national precision oncology program aiming to define tumor molecular profiles in children and adolescents with primary very high-risk, relapsed, or refractory pediatric tumors in order to identify relevant aberrations to inform treatment.

  Dataset EGAD00001010179

• CCA RNA-seq data (60 CCA, 6 normal, 16 cell-line)

  Fastq files for RNA-seq for 60 CCAs, 6 normal bile duct tissues, 14 CCA cell-lines (including replicates), and 2 normal cholangiocyte cell-lines (including replicates). RNA was extracted using the Qiagen RNeasy Mini kit. Illumina Tru-Seq Stranded Total RNA kit (Illumina, San Diego, California, USA) was used to prepare RNA libraries from 1 µg of total RNA. Paired-end 150 bp sequencing was performed using Illumina HiSeq4000 sequencer with the paired-end 150 bp read option.

  Dataset EGAD00001011998

• CCA ChIP-seq data (63 CCA, 8 normal, 19 cell-line)

  Fastq files for H3K27ac ChIP-seq (with matched input-DNA control) for 63 CCAs, 8 normal bile duct tissues, 16 CCA cell-lines (including replicates), and 3 normal cholangiocyte cell-lines (including replicates). Library prep was performed with the NEBNext ChIP-seq library preparation kit. Each library (including matching input DNA) was sequenced to an average depth of 20 to 30 million raw reads on Illumina HiSeq4000 sequencer, with paired-end sequencing (except for 3 normal bile tissues done with single-end sequencing).

  Dataset EGAD00001012103

• Efficacy of two different FGFR-inhibitors in a patient with extrahepatic cholangiocarcinoma harboring an FGFR2 mutation

  Cholangiocarcinomas (CCAs) is a type of cancer with few effective systemic therapies. Elucidation of the molecular landscape of the disease from genomic studies based on next generation sequencing (NGS) has contributed to the introduction of new targeted therapies. One of these treatments consists of a class of small molecules that target members of the FGFR family of receptor tyrosine kinases. These drugs are effective and have been approved for cholangiocarcinomas with fusions or rearrangements of FGFR genes. In contrast, the role of these inhibitors in cholangiocarcinomas with mutations in FGFR genes is less well defined. We report here a patient with a cholangiocarcinoma bearing a FGFR2 p.Ser252Trp mutation. The patient was treated with two different FGFR inhibitors, as the first caused ocular toxicity. She obtained clinical benefit from both. This case illustrates the efficacy of FGFR inhibitors on cholangiocarcinoma with specific point mutations. This is the first case to report the clinical benefit of these drugs in FGFR2 p.Ser252Trp mutation. Clinical benefit can be sustained, as seen in our patient. Our case also shows that FGFR inhibitors-induced adverse effects, such as ocular toxicities, may not recur after re-challenge with an alternative drug of the same class.

  Study EGAS50000000015

• CUT&RUN-sequencing identifies PTK7 as a direct Wnt target in patient-derived colorectal cancer organoids

  The aberrant activation of Wnt/β-catenin signaling by APC mutations is a hallmark of colorectal cancer (CRC), but targeting Wnt signaling therapeutically has proven challenging. Deciphering the molecular effects of mutant APC-driven Wnt activation is crucial to enable the discovery of novel therapeutic targets. Here, we employ CUT&RUN-sequencing in patient-derived CRC organoids derived from two donors to dissect the transcriptional regulation by β-catenin in CRC. This analysis identified several genes of interest for CRC development as potential β-catenin target genes. Among these, we characterize PTK7, a co-receptor of the Wnt pathway and stem cell marker, as a main transcriptional target of β-catenin in CRC. We confirm that the expression of PTK7 is directly regulated by β-catenin in a comprehensive panel of CRC models. We demonstrate that APC mutations introduced by CRISPR/Cas9 result in the upregulation of PTK7 expression in human colon organoids, underlining the relevance of this upregulation during CRC carcinogenesis. Finally, we show that PTK7 promotes proliferation in CRC models without definitively affecting canonical Wnt signaling. Together, these results suggest that PTK7, which can be potentially targeted by existing drugs, is a Wnt target gene that contributes to oncogenic growth in CRC.

  Study EGAS00001008295

• Host whole genome variations are associated with neurocognitive outcome in survivors of pediatric medulloblastoma

  Host whole genome analysis is a promising source of predictive information for long-term morbidity in cancer survivors. However, studies on genetic predictors of long-term outcome, particularly neurocognitive function following chemoradiation in pediatric oncology are limited. In the present study, we evaluated variations in host whole genome single nucleotide polymorphisms (SNPs) and their association with cognitive outcome. Whole-genome SNP analysis of host peripheral blood was conducted on 22 medulloblastoma long-term survivors, of whom 18 completed neuropsychological testing. First, unsupervised consensus clustering of the most variable SNPs within 409 genes involved in DNA repair was performed. Discrete variant groups were identified, although they were not associated with cognitive outcome, suggesting that variations in genes corresponding to a single functional group may be insufficient to predict long-term outcome alone. In support of this interpretation, unsupervised hierarchical clustering analysis using disease-associated gene variants by cognitive impairment status yielded two distinct variant clusters comprised of 36 variants, 34 of which were in noncoding regions. These findings illustrate for the first time that cognitively impaired survivors have a distinct variant profile compared to other medulloblastoma survivors. Future research in larger cohorts is needed to validate host genome predictors of cognitive impairment that may impact clinical management.

  Study EGAS00001002996

• SNP Genotype Data: Subpopulations of Filipino, Malaysian, and Papua New Guinea

  In the context of the study 'Exploring Adaptive Phenotypes for the Human Calcium-Sensing Receptor Polymorphism R990G,' this repository contains 11 VCF files. Each file includes genetic data from 22 autosomes, representing distinct subpopulations. The subpopulations are as follows: Malaysian: Aeta (15 samples) Agta (11 samples) Batak (10 samples) Mamanwa (6 samples) Filipino: Jehai (13 samples) Kintaq (6 samples) Temiar (5 samples) Papua New Guinea: Highlands (2 samples) Koinambe (10 samples) Kosipe (10 samples) Sepik (2 samples) The numbers in parentheses indicate the sample size for each respective subpopulation.

  Study EGAS50000000044

• Sequencing data for oesophageal and related samples - ICGC DCC release 28 earmarked (WGS)

  WGS sequencing for 43 cases (86 samples) from the ICGC ESAD-UK project Tumours 50x Normals 30x HiSeq X BAM files These samples are earmarked for inclusion in ICGC release 28

  Dataset EGAD00001004029

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90682

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 624 samples; filetype=bam

  Dataset EGAD00001004737

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90689A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 378 samples; filetype=bam

  Dataset EGAD00001004739

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90689C

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 718 samples; filetype=bam

  Dataset EGAD00001004741

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90694B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1222 samples; filetype=bam

  Dataset EGAD00001004743

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90706

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 522 samples; filetype=bam

  Dataset EGAD00001004744

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95622A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 509 samples; filetype=bam

  Dataset EGAD00001004746

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95632B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 626 samples; filetype=bam

  Dataset EGAD00001004748

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95660A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1522 samples; filetype=bam

  Dataset EGAD00001004750

• WES data

  WES FASTq files of 76 bulk pre-treatment tumors and 76 matched peripheral blood mononuclear cells from GO30140 group A

  Dataset EGAD00001008129

• Gene expression QTL mapping in stimulated iPSC-derived macrophages

  Immune cells sense and respond to external stimuli, initiating an inflammatory response, with genetic variants potentially altering these responses. Traditional QTL mapping often uses naïve cells, missing condition-specific variants detectable post-stimulation. Our study uses a high-throughput platform to map eQTLs across 24 conditions using iPSC-derived macrophages, identifying that 76% of eQTLs in stimulated conditions were also present in naïve cells. We found response eQTLs (reQTLs) vary widely across conditions, with rare single-condition reQTLs being overrepresented among disease-colocalizing eQTLs. This study nominates 21.7% more disease effector genes at GWAS loci through reQTL colocalization, with 38.6% not found in the GTEx catalogue, highlighting the importance of condition-specific regulatory variation in understanding disease risk alleles. Our findings underscore the value of condition-specific studies in elucidating the genetic mechanisms underlying complex diseases. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001015380

• Wilm's tumor sequencing data

  No. of samples: 80 (28 ULP-WGS, 26 WES, 26 RNA-SEQ) File types: FASTQ (28 ULP-WGS, 19 WES, 18 RNA) and BAM (7 WES, 8 RNA) Technology used: Sequencing - Illumina Novoseq 6000; Map/Align - Illumina DRAGEN v3.7.5; Genome assembly - GrCh38p13 Filename nomenclature: - SampleName_Passage_SampleType_TissueType_SequencingType - Passage of: PX = unknown; PZ = from patient; P0 = first passage from patient on plastic; P1 = first passage from plastic/PDX/organoid - SampleType: STN = normal; STT = tumor - SampleType STN: 00 = tissue unknown; 01 = adjacent normal; 02 = fibroblast; 03 = germline blood; 21 = cell line from patient tissue; 22 = cell line from PDX; 23 = cell line from patient fibroblast - SampleType STT: 00 = tissue unknown; 01 = primary tumor; 21 = cell line from patient; 22 = cell line from PDX - TissueType: WT = Wilm's tumor; 00 = kidney unknown; 01 = kidney left; 02 = kidney right - SequencingType: 00 = unknown; 02 = ultra-low pass whole-genome sequencing; 20 = whole-exome; 61 = bulk RNA-sequencing

  Dataset EGAD00001011111

• A next-generation dual guide CRISPR system for genetic interaction library screening

  Raw sgRNA sequencing data from a pilot CRISPR screening library to test the dual guide vector system (8,914 guide pairs), and from a large scale genetic interaction screen (~100,136 guide pairs) in HT-29 cells. This data refers to Burgold et al. Nature Communications 2025.

  Dataset EGAD00001015754

• Sequencing data for oesophageal and related samples - ICGC DCC release 26 (WGS)

  WGS sequencing for 303 cases (620 samples) from the ICGC ESAD-UK project Tumours 50x Normals 30x HiSeq X BAM files These samples are all available in ICGC release 26

  Dataset EGAD00001003580

• Inherited chromosomally-integrated human herpesvirus 6A/B (HHV-6A/B) genome sequences in the Japanese population

  The deposited sequences represent inherited chromosomally-integrated human herpesvirus 6 (iciHHV-6) genomes identified from 10 BioBank Japan (BBJ) subjects based on the analysis of the whole-genome sequencing (WGS) data. In brief, we re-aligned unmapped reads from the WGS to HHV-6A genome (Genbank accession number: KJ123690.1) using BWA-MEM algorithm. Ten out of 3,256 subjects were identified with high depth of coverage of HHV-6. We further distinguished subjects with integrated HHV-6A subtypes from those with integrated HHV-6B based on phylogenetic analysis of concatenated sequences of three viral genes (U27/U43/U83, which show high divergence between viral species). We reconstructed the HHV-6 viral genome of 10 subjects. First, reads that mapped to a reference HHV-6A genome (KJ123690.1) were further aligned against the integrated HHV-6A genome derived from a Japanese individual NA18999 (GenBank Accession number: KY316047.1) using BWA-MEM. Based on the alignment, variant calling was performed using freebayes (version: v1.2.0-2-g29c4002) with parameters ploidy = 1 and min-alternate-fraction = 0.8 {Garrison, 2012}. We generated subject-specific iciHHV-6 viral sequences by applying the resulting variants to the KY316047.1 reference genome using the FastaAlternateReferenceMaker function in the Genome Analysis Toolkit (GATK) v3.7. Please note that HHV-6B-specific variants are unlikely to be sensitively reconstructed using this method.

  Study JGAS000240

• HELIUS cohort

  The gut microbiota composition is unique to every individual but is shaped by common factors including diet, lifestyle, medication use, early-life determinants, living environment or genetics. Most of these factors may be influenced by ethnicity. This study explored variations in fecal microbiota composition in 6048 individuals with different ethnic backgrounds living in the same geographical area (Amsterdam, the Netherlands). The HELIUS data are owned by the Amsterdam University Medical Centers, location AMC in Amsterdam, The Netherlands. To allow sharing of microbiome data collected in HELIUS with (inter)national researchers, 16s rRNA sequence analysis has been stored at the European genome-phenome archive (EGA; accession code EGAD00001004106). This requires that access needs to be granted, also because the HELIUS data are stored with relevant phenotypical variables. Access is granted to all researchers affiliated with an internationally recognized research institution who request to use the HELIUS data within the EGA context, after having signed the data transfer agreement. Any researcher can request the data by submitting a proposal to the HELIUS Executive Board as outlined at http://www.heliusstudy.nl/en/researchers/collaboration, by email: heliuscoordinator at amsterdamumc dot nl. The HELIUS Executive Board will check proposals if they do not conflict with ethical approvals and informed consent forms of the HELIUS study.

  Study EGAS00001002969

• Target gene sequencing for human normal endometrial glands

  The raw fastq files target sequencing of 112 genes for 1,298 endometrial glands and matched blood samples. The paired-end sequencing data sets (R1 and R2) are deposited. ABCC1, ACRC, ANK3, ARHGAP35, ARID1A, ARID5B, ATCAY, ATM, ATR, BARD1, BCOR, BRCA1, BRCA2, BRD4, BRIP1, CAMTA1, CDC23, CDYL, CFAP54, CHD4, CHEK1, CHEK2, CTCF, CTNNB1, CUX1, DGKA, DISP2, DYNC2H1, EMSY, FAAP24, FAM135B, FAM175A, FAM65C, FANCA, FANCB, FANCC, FANCD2, FANCE, FANCF, FANCG, FANCI, FANCL, FANCM, FAT1, FAT3, FBN2, FBXW7, FGFR2, FRG1, GPR50, HEATR1, HIST1H4B, HNRNPCL1, HOOK3, KIAA1109, KIF26A, KMT2B, KMT2C, KRAS, LAMA2, LRP1B, MLH1, MON2, MRE11A, MSH2, MSH6, MTOR, NBN, PALB2, PHEX, PIK3CA, PIK3R1, PLXNB2, PLXND1, PMS2, POLE, POLR3B, PPP2R1A, PTEN, PTPN13, RAD50, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54B, RAD54L, RICTOR, SACS, SIGLEC9, SLC19A1, SLX4, SPEG, STT3A, TAF1, TAF2, TAS2R31, TFAP2C, TNC, TONSL, TP53, TTC6, UBA7, VNN1, WT1, XIRP2, ZBED6, ZC3H13, ZFHX3, ZFHX4, ZMYM4.

  Dataset EGAD00001008465

• EGAD00010000288

  All cases and Finnish, Dutch, Italian control samples (Hap550)

  Dataset EGAD00010000288

• EGAD00010000286

  All cases and controls (Hap550)

  Dataset EGAD00010000286

• EGAD00010000292

  All cases and Finnish, Dutch, Italian control samples (Hap300)

  Dataset EGAD00010000292

• EGAD00010000298

  All cases and controls (Hap300)

  Dataset EGAD00010000298

• The genomic architecture of mesothelioma

  The genome-wide landscape of somatically acquired mutations in mesothelioma has not been deeply characterised to date, but advances in DNA sequencing technology now allow this to be addressed comprehensively. Harnessing massively parallel DNA sequencing platforms, we will identify somatically acquired point mutations in all coding regions of the genome from patients with mesothelioma. In addition, using paired-end sequencing, we will map copy number changes and genomic rearrangements from the same patients.

  Dataset EGAD00001000360

• 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

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001001090

• Genetic landscape of inherited retinal dystrophies

  In the context of research, this dataset contains 423 IRD samples; 411 of them analyzed with Clinical Exome Sequencing solutions, and 12 with Whole Exome Sequencing.

  Dataset EGAD00001007022

• Bulk RNA sequencing of Singapore colorectal cancer patients (SG-BULK)

  RNA-seq libraries were prepared using the KAPA Stranded RNA-Seq Kit with RiboErase (Kapa Biosystems, Wilmington, MA) and sequenced to a target depth of 200-M reads on the Illumina HiSeq platform (Illumina, San Diego, CA).

  Dataset EGAD00001008512

• CBD-RAW-SC-GEX: 10X Single-Cell Gene Expression

  Raw Illumina sequencing data and CellRanger BAM output files. For further information regarding this dataset, please contact Stephen Sansom at contact@combat.ox.ac.uk.

  Dataset EGAD00001008007

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90553C

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1700 samples; filetype=bam

  Dataset EGAD00001004729

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90554A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 628 samples; filetype=bam

  Dataset EGAD00001004730

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90554B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 596 samples; filetype=bam

  Dataset EGAD00001004731

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90554C

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1735 samples; filetype=bam

  Dataset EGAD00001004732

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90560A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 585 samples; filetype=bam

  Dataset EGAD00001004733

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90560B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 766 samples; filetype=bam

  Dataset EGAD00001004734

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90600C

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2055 samples; filetype=bam

  Dataset EGAD00001004735

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90648B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 620 samples; filetype=bam

  Dataset EGAD00001004736

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90685

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 481 samples; filetype=bam

  Dataset EGAD00001004738

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90689B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 735 samples; filetype=bam

  Dataset EGAD00001004740

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90694A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 493 samples; filetype=bam

  Dataset EGAD00001004742

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95621B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 488 samples; filetype=bam

  Dataset EGAD00001004745

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95624A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 604 samples; filetype=bam

  Dataset EGAD00001004747

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95632D

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples; filetype=bam

  Dataset EGAD00001004749

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95664A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 465 samples; filetype=bam

  Dataset EGAD00001004751

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95670A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 615 samples; filetype=bam

  Dataset EGAD00001004753

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95722A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 968 samples; filetype=bam

  Dataset EGAD00001004755

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95724B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 561 samples; filetype=bam

  Dataset EGAD00001004757

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 928 samples; filetype=bam

  Dataset EGAD00001004759

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95736A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1072 samples

  Dataset EGAD00001004761

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96145A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 589 samples; filetype=bam

  Dataset EGAD00001004763

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 648 samples; filetype=bam

  Dataset EGAD00001004765

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96165A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 755 samples; filetype=bam

  Dataset EGAD00001004767

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires forlibrary A96176A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 531 samples; filetype=bam

  Dataset EGAD00001004769

• 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

• 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

• Renal habitat WXS

  This project is correlating the molecular profiling of renal tumours with multiparametric and 13C-MRI including by 13C-MRSI. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010125

• Res1_PC9_exp2_MC_01.04.22

  8 cell pellet samples for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Dataset EGAD00001012233

• Res1_PC9_exp1_MC_29.03.22

  8 cell pellet samples for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Dataset EGAD00001012232

• Res1_H23_exp2_MC_13.07.22

  8 samples are cell pellets for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kosuke primers.

  Dataset EGAD00001012234

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96213A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 522 samples; filetype=bam

  Dataset EGAD00001004771

• Investigation of the Causal Etiology in a Patient with T-B+NK+ Immunodeficiency

  We describe a male proband with normal B lymphocyte and natural killer (NK) cell numbers, but who had T lymphopenia beginning at 1 week of age. His peripheral blood contained very few T cell receptor excision circles (TREC), suggesting impaired thymic T cell development. He received an allogeneic hematopoietic stem cell marrow transplant, but despite engraftment, it did not fully correct the T lymphopenia. Sequencing excluded known immunodeficiency genes; however, whole exome sequencing revealed X-linked inheritance by the male proband of a missense mutation in MED14 (MED14V763A), a component of the mediator complex. Functional screening of the MED14V763A variant in zebrafish suggested that MED14 is essential for normal development, since morpholino (MO)-mediated loss of MED14 function attenuated T cell development, but it was rescued by ectopic expression of the wild type human MED14 but not by the MED14V763A variant. This defect in T cell repopulation is consistent with the incomplete T cell reconstitution observed upon transplantation of the proband with bone marrow from his healthy male sibling, who was found to have the same MED14V763A variant. However, the brother was normal, indicating that the altered MED14 could not by itself explain the disease. WES also revealed a mutation in the L1 cell adhesion molecule (L1CAMQ498H); however, introducing that mutation in vivo in mice did not disrupt T cell development. Consequently, the immunodeficiency in the patient is not fully elucidated. It is possible that MED14 contributes, but it is also possible that another gene is fully responsible for the disease.

  Study phs002990

• KiCS WGS data for academic and for-profit use

  Data from samples that are marked for both academic and for-profit use.

  Dataset EGAD00001009699

• Efficacy of two different FGFR-inhibitors in a patient with extrahepatic cholangiocarcinoma harboring an FGFR2 mutation

  Cholangiocarcinomas (CCAs) is a type of cancer with few effective systemic therapies. Elucidation of the molecular landscape of the disease from genomic studies based on next generation sequencing (NGS) has contributed to the introduction of new targeted therapies. One of these treatments consists of a class of small molecules that target members of the FGFR family of receptor tyrosine kinases. These drugs are effective and have been approved for cholangiocarcinomas with fusions or rearrangements of FGFR genes. In contrast, the role of these inhibitors in cholangiocarcinomas with mutations in FGFR genes is less well defined. We report here a patient with a cholangiocarcinoma bearing a FGFR2 p.Ser252Trp mutation. The patient was treated with two different FGFR inhibitors, as the first caused ocular toxicity. She obtained clinical benefit from both. This case illustrates the efficacy of FGFR inhibitors on cholangiocarcinoma with specific point mutations. This is the first case to report the clinical benefit of these drugs in FGFR2 p.Ser252Trp mutation. Clinical benefit can be sustained, as seen in our patient. Our case also shows that FGFR inhibitors-induced adverse effects, such as ocular toxicities, may not recur after re-challenge with an alternative drug of the same class.

  Dataset EGAD50000000021

• Use of Deep Sequencing to Dectect Clonal Mutations In Sun Exposed Skin Epidermis PART2

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Dataset EGAD00001000825

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73044A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1340 samples; filetype=bam

  Dataset EGAD00001004719

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73044B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2057 samples; filetype=bam

  Dataset EGAD00001004720

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73046B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1970 samples; filetype=bam

  Dataset EGAD00001004721

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73047D

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2091 samples; filetype=bam

  Dataset EGAD00001004722

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73056B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1267 samples; filetype=bam

  Dataset EGAD00001004723

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 230 samples; filetype=bam

  Dataset EGAD00001004724

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 232 samples; filetype=bam

  Dataset EGAD00001004725

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616C

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 239 samples; filetype=bam

  Dataset EGAD00001004726

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75617A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 692 samples; filetype=bam

  Dataset EGAD00001004727

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90553A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 612 samples; filetype=bam

  Dataset EGAD00001004728

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95664B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 606 samples; filetype=bam

  Dataset EGAD00001004752