19375 results for "Cheap fc 26 coins Buyfc26coins.com is official EA Sports partner for FC 26 coins That was the fastest delivery ever..fxB4"

in 186.83 milliseconds.

• Genomic characterization of germ-cell tumors in childhood

  Germ cell tumors (GCTs) are rare neoplasms affecting approximately 3.5% of pediatric patients, with diverse histological subtypes. Despite their low mutational burden, prevalent alterations in KIT, KRAS, and NRAS genes are observed, but molecular understanding of pediatric GCTs lags behind adult counterparts. We aimed to elucidate the genomic landscape of 16 pediatric GCT patients via whole exome sequencing (WES), which revealed somatic alterations resembling those in adult GCTs.

  Study EGAS50000000619

• Transcriptomic profiling of myeloid cells from secondary lymphoid organs (lymph nodes and tonsils) from lymphoma patients and controls.

  Despite their recognized impact on the pathogenesis and prognosis of B-cell lymphoma, tumor-associated macrophages (TAM) have not been extensively explored in diffuse large B-cell lymphoma (DLBCL) and follicular lymphoma (FL). We investigated mononuclear phagocyte (MNP) heterogeneity using single cell RNA sequencing (scRNAseq) in B-cell lymphoma lymph nodes compared to reactive secondary lymphoid organs (lymph nodes and tonsils).

  Study EGAS50000001135

• Investigation of chromatin accessibility in clear cell renal cell carcinoma using ATAC-seq

  To identify regions of open and accessible chromatin in clear cell renal cell carcinoma (ccRCC), we performed ATAC-seq on the 786-O, A-498, UM-RC-2 ccRCC cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq and processed narrowPeak fomats. Data were processed using the nf-core atacseq pipeline.

  Dataset EGAD50000001885

• ProstOmics - DNA methylation v2

  Bulk methylation array data from 32 prostate tissue samples from 8 patients (3 with post-surgery relapse). Methylation data were acquired using the microarray assay Illumina Infinium MethylationEPIC v2.0 Kit. The individual samples have information on patient origin and sample type (cancer, cancer-adjacent field-effect normal or normal sample far from cancer). Patient metadata include information of age at surgery, time (months) until reported relapse, pre-surgery PSA and post-surgery T-stage.

  Dataset EGAD50000000606

• ProstOmics - DNA methylation v1

  Bulk methylation array data from 64 prostate tissue samples from 16 patients (5 with post-surgery relapse). Methylation data were acquired using the microarray kit Illumina Infinium MethylationEPIC BeadChip (n=64 ). The individual samples have information on patient origin and sample type (cancer, cancer-adjacent field-effect normal or normal sample far from cancer). Patient metadata include information of age at surgery, time (months) until reported relapse, pre-surgery PSA and post-surgery T-stage.

  Dataset EGAD50000000605

• Single-cell multi-omics reveals clonal evolution and T-cell dynamics underlying differential responses to ibrutinib in Waldenström macroglobulinemia.

  To elucidate the molecular basis underlying differential response and resistance to ibrutinib in Waldenström’s macroglobulinemia (WM), we conducted a prospective phase II trial (NCT02604511) of ibrutinib monotherapy in treatment-naïve patients. Seventy-four sequential bone marrow (BM) aspirates from 17 patients, collected from baseline through 48 treatment cycles, were profiled using single-cell RNA and V(D)J sequencing.

  Study EGAS50000001596

• HipSci___Whole_Exome_sequencing___Usher syndrome and congenital eye defects

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform whole exome sequencing using Agilent whole exome pulldown method on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with Usher syndrome and congenital eye defects.

  Study EGAS00001001985

• Processed naive T cell AIRR-seq data

  This dataset contains processed productively and non-productively rearranged TCR sequences (tsv file format) from bulk AIRR-seq of naive peripheral blood CD4+ T cells from 103 subjects with celiac disease and 103 control donors. Raw sequences have been processed with presto and Change-O as detailed in the linked publication in order to filter by quality, create consensus sequences and collapse identical rearrangements, and analysed with IgBlast. The dataset also contains an accompanying metadata file (csv).

  Dataset EGAD50000002731

• Molecular characterization of hepatocellular carcinoma in patients with non-alcoholic steatohepatitis

  Patients with hepatocellular carcinoma (HCC) associated to non-alcoholic steatohepatitis (NASH) are increasing globally, but their molecular traits are not well characterized. Our molecular characterization revealed higher rates of ACVR2A mutations (10%) – a potential tumour suppressor, presence of a novel mutational signature (MutSig-NASH-HCC), a more relevant role of Wnt/TGF-β proliferation subclass in tumours (42%) and immunosuppressive traits in the adjacent non-tumoral tissue.

  Study EGAS00001005222

• Discriminating Th17.1 cell driven sarcoidosis-like inflammation from relapse after anti-BCMA CAR T cells in multiple myeloma

  We present a case study on sarcoidosis-like flare-up after Idecabtagen Vicleucel (Ide-cel), a BCMA targeting CAR T cell therapy, and identified a Th17.1 driven autoimmune mechanism as the biological underpinning of this phenomenon using single-cell RNA-seq analysis. Furthermore, single-cell RNA-seq allowed to discriminate between immune-mediated changes and true relapse after CAR T cell treatment.

  Study EGAS00001006133

• Variation and transmission of the human gut microbiota across generations - shotgun data

  Variation and transmission of the human gut microbiota across generations - shotgun sequencing data

  Dataset EGAD00001008207

• Pediatric Papillary Thyroid Carcinoma RNA-Seq

  38 PPTCs were sequenced using RNASeq to identify oncogenic variants in driver-unknown tumors and to explore gene expression patterns. RNA libraries were quantified by qPCR using the Kapa Library Quantification Illumina/ABI Prism Kit protocol (KAPA Biosystems). Libraries were pooled in equimolar quantities and paired-end sequenced on 2 lanes of a High Throughput Run Mode flowcell with the V4 sequencing chemistry on an Illumina HiSeq 2500 platform following Illumina’s recommended protocol to generate paired-end reads of 126-bases in length.

  Dataset EGAD00001007499

• Exome_sequencing_of_Congenital_Heart_Disease_families_from_the_Competence_Network_Berlin

  This project aims to study exomes from families and trios withcongenital heart disease (CHD). The samples have been collected underthe Competence Network - Congenital Heart Defects in Berlin, Germany.The phenotypes are mainly left ventricular outflow obstruction (aorticstenosis, bicuspd aortic valve disease coarctation and hypoplasticleft heart), but will also include samples with hypoplastic rightheart and atrioventricular septal defects. We will perform whole exomesequencing using Agilent sequence capture and Illumina HiSeqsequencing.

  Study EGAS00001000368

• Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures

  Cancer genomes harbor a broad spectrum of structural variants (SV) driving tumorigenesis, a relevant subset of which are likely to escape discovery in short reads. We employed Oxford Nanopore Technologies (ONT) sequencing in a paired diagnostic and post-therapy medulloblastoma to unravel the haplotype-resolved somatic genetic and epigenetic landscape. We assemble complex rearrangements and such associated with telomeric sequences, including a 1.55 Megabasepair chromothripsis event. We uncover a complex SV pattern termed "templated insertion thread", characterized by short (mostly less than 1kb) insertions showing prevalent self-concatenation into highly amplified structures of up to 50kbp in size. Templated insertion threads occur in 3% of cancers, with a prevalence ranging to 74% in liposarcoma, and frequent colocalization with chromothripsis. We also perform long-read based methylome profiling and discover allele-specific methylation (ASM) effects, complex rearrangements exhibiting differential methylation, and differential promoter methylation in seven cancer-driver genes. Our study shows the potential of long-read sequencing in cancer.

  Study EGAS00001006576

• Functional Multiomics of Cellular Therapy and Immune Checkpoint Blockade Therapy for Solid Tumors

  Tumor samples were collected from a patient with synovial sarcoma, which acquired resistance to ACT targeting NY-ESO-1. Biopsies (n=3; primary, metastasis, and recurrence) were subjected to bulk tumor DNA and RNA sequencing, as well as high-dimensional spatial profiling of RNA and protein targets. Bulk tumor whole exome and RNA sequencing corresponding to all three tumor specimens and whole exome sequencing from patient-matched normal blood are made available through this accession.

  Study phs002762

• FusionSeq: a modular framework for finding gene fusions by analyzing Paired-End RNA-Sequencing data

  We have developed FusionSeq to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts such as misalignments or random pairing of transcript fragments and it ranks candidates according to several statistics. It also has a module to identify exact sequences at breakpoint junctions. FusionSeq detected known and novel fusions in a specially sequenced calibration data set, including 8 cancers with and without known rearrangements.

  Study phs000311

• Spatial omics analysis of non-small cell lung cancers for revealing molecular statuses of intratumor heterogeneity and tumor microenvironment

  In this study, we perform spatial transcriptome analysis Visium/Xenium and other omics analysis using surgical specimens of Japanese non-small cell lung cancer cases to understand omics statuses of cancer cells and their surrounding stromal and immune cells in local tumor regions. We aim to stratify lung cancer patients with considering intratumor heterogeneity and complicated microenvironent of lung cancer tissues by using spatial omics data and histopathological information.

  Study JGAS000613

• EGAD00010000768

  Replication data for HipSci normal samples using both HumanCoreExome-12_v1 and HumanOmni2.5-8 BeadChips

  Dataset EGAD00010000768

• Fecal WMS UC sequencing data

  Fecal WMS data from NCT02749630 ulcerative colitis patients. Stool samples were collected at screening as well as on day 64 and prepared for whole metagenomic sequencing.

  Dataset EGAD00001008817

• Separation of chronic myeloid leukemia stem cells from normal hematopoietic stem cells at single-cell resolution

  We provide whole exome DNA sequening data in fastq format for 23 clinical samples of chronic myeloid leukemia stem cells (CML-SC) plus two buccal swipes derived normal samples. CML samples are comprised of 4 to 8 replicates from two patients, at diagnosis and after treatment. Single CML stem cells before treatment and single non-transformed hematopoietic stem cells (HSC) at remission were selected from bone marrow samples by FACS, according to newly identified genetic markers CD33+CD26+ at diagnosis and CD33+CD26-/CD33-CD26- at remission. WES libraries of colony forming assays derived CML-SC and HSC populations were prepared using Agilent SureSelect Human All Exon V6 kit and sequenced running 150 cycles (2x 75bp paired-end) on an Illumina NextSeq 500 platform.

  Dataset EGAD00001009847

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0187_001A for Follicular lymphoma patient sample TFRIPAIR10_FL

  Dataset EGAD00001010222

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0170_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0170_003 for Follicular lymphoma patient sample TFRI_Cont_5

  Dataset EGAD00001010207

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0167_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_003 for Follicular lymphoma patient sample TFRI_Cont_2

  Dataset EGAD00001010204

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0168_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0168_003 for Follicular lymphoma patient sample TFRI_Cont_3

  Dataset EGAD00001010205

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_003

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_003 for Follicular lymphoma patient sample TFRI_Cont_4

  Dataset EGAD00001010206

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0171_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0171_003A for Follicular lymphoma patient sample TFRI_Cont_6

  Dataset EGAD00001010208

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0178_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0178_003A for Follicular lymphoma patient sample TFRI_Cont_8

  Dataset EGAD00001010209

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0183_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0183_003A for Follicular lymphoma patient sample TFRI_Cont_9

  Dataset EGAD00001010210

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0187_003A for Follicular lymphoma patient sample TFRI_Cont_10

  Dataset EGAD00001010211

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0188_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0188_003A for Follicular lymphoma patient sample TFRI_Cont_11

  Dataset EGAD00001010212

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0197_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0197_003A for Follicular lymphoma patient sample TFRI_Cont_12

  Dataset EGAD00001010213

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0198_003A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0198_003A for Follicular lymphoma patient sample TFRI_Cont_13

  Dataset EGAD00001010214

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0167_001

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_001 for Follicular lymphoma patient sample TFRIPAIR2_FL

  Dataset EGAD00001010215

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0168_001

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0168_001 for Follicular lymphoma patient sample TFRIPAIR3_FL

  Dataset EGAD00001010216

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_001

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_001 for Follicular lymphoma patient sample TFRIPAIR4_FL

  Dataset EGAD00001010217

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0170_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0170_001A for Follicular lymphoma patient sample TFRIPAIR5_FL

  Dataset EGAD00001010218

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0171_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0171_001A for Follicular lymphoma patient sample TFRI_Pair_6_FL

  Dataset EGAD00001010219

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0178_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0178_001A for Follicular lymphoma patient sample TFRIPAIR8_FL

  Dataset EGAD00001010220

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0183_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0183_001A for Follicular lymphoma patient sample TFRIPAIR9_FL

  Dataset EGAD00001010221

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0188_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0188_001A for Follicular lymphoma patient sample TFRIPAIR11_FL

  Dataset EGAD00001010223

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0197_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0197_001A for Follicular lymphoma patient sample TFRIPAIR12_FL

  Dataset EGAD00001010224

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0198_001A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0198_001A for Follicular lymphoma patient sample TFRI_Pair_13_FL

  Dataset EGAD00001010225

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0167_002

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0167_002 for Diffuse large B-cell lymphoma patient sample TFRIPAIR2_DLBCL

  Dataset EGAD00001010226

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0168_002

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0168_002 for Diffuse large B-cell lymphoma patient sample TFRIPAIR3_DLBCL

  Dataset EGAD00001010227

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0169_002

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0169_002 for Diffuse large B-cell lymphoma patient sample TFRIPAIR4_DLBCL

  Dataset EGAD00001010228

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0170_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0170_002A for Diffuse large B-cell lymphoma patient sample TFRIPAIR5_DLBCL

  Dataset EGAD00001010229

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0171_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0171_002A for Diffuse large B-cell lymphoma patient sample TFRI_Pair_6_DLBCL

  Dataset EGAD00001010230

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0178_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0178_002A for Diffuse large B-cell lymphoma patient sample TFRIPAIR8_DLBCL

  Dataset EGAD00001010231

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0183_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0183_002A for Diffuse large B-cell lymphoma patient sample TFRI_Pair_9_DLBCL

  Dataset EGAD00001010232

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0187_002A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0187_002A for Diffuse large B-cell lymphoma patient sample TFRIPAIR10_DLBCL

  Dataset EGAD00001010233