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• Comprehensive Genomic Characterization of Acral Melanoma

  In this study, we performed paired tumor/normal long insert whole genome and exome sequencing and tumor RNA sequencing on primary or metastatic acral melanoma tumors collected from 34 patients. Patients were enrolled from either Vanderbilt University or the Memorial Sloan-Kettering Cancer Center. We report an integrated analysis of DNA and RNA sequencing data to describe genomic and transcriptomic characteristics of acral melanoma.

  Study phs001036

• Single cell atlas of relapsed/refractory large B-cell lymphoma

  Relapsed/refractory large B-cell lymphomas (rrLBCL) are clinically and biologically diverse lymphoid malignancies with intricate microenvironments that play a key role in disease development. In this study, we used single-nucleus multiome profiling along with bulk DNA and RNA sequencing on 120 tumor and control biopsies to comprehensively characterize the various cell types and subsets found in rrLBCL tumors.

  Study EGAS50000001293

• Whole-exome sequencing and RNA-seq data of paired normal-tumour samples from MMR-proficient early-onset colorectal cancer patients

  This study aims to identify novel hereditary colorectal cancer predisposition genes by performing whole-exome sequencing and RNA-seq of paired normal colonic mucosa and colorectal cancer samples from 19 patients diagnosed with MMR-proficient colorectal cancer at an age of 50 years or younger. Both whole-exome and RNA sequencing were performed on the Illumina platform.

  Study EGAS50000001296

• Single-cell sequencing data from AIM⁺ HIV-1-specific T cells in post-intervention controllers and non-controllers

  This study characterizes the transcriptional landscape and TCR repertoire of HIV-1–specific T cells across multiple longitudinal samples from two people living with HIV who achieved post-treatment viral control after short-course antibody-based therapy, compared with two non-controllers. Antigen-specific T cells were isolated by activation-induced marker (AIM)–based sorting prior to sequencing.

  Study EGAS50000001570

• Sample Multiplexing Oligo Comparison

  In this study, we compared various multiplexing reagents, including MULTI-Seq, Hashtag antibody, and CellPlex, in patient-derived xenografts (PDXs). We found that all multiplexing reagents worked well in cell types robust to ex vivo manipulation but suffered from signal-to-noise issues in more delicate sample types. We also compared the performance of fixed scRNA-Seq kits and CRISPR-based destruction of non-informative genes.

  Study EGAS50000000153

• scATAC-seq of CD4+ T cells from blood, lymph nodes and tumors of NSCLC patients

  This study explore the CD4+ T cells diversity in paired blood, lymph nodes and tumors of 2 different NSCLC patients. After FACS-sorted of Tregs (DAPI- CD45+ CD4+ CD25hi CD127lo) and Tconvs (DAPI- CD45+ CD4+CD25lo CD127lo/hi), cells were mixed in equal proportion (fifty/fifty ratio) and procesed with 10X Chromium (10X Genomics) scATAC kit and sequenced using Illumina platforms.

  Study EGAS50000000294

• HipSci___Whole_Exome_sequencing___Cardiomyopathy

  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 hypertrophic cardiomyopathy

  Study EGAS00001001980

• HipSci___Whole_Exome_sequencing___Alport

  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 Alport syndrome

  Study EGAS00001001974

• HipSci___Whole_Exome_sequencing___Retinitis_Pigmentosa

  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 Retinitis Pigmentosa

  Study EGAS00001001984

• HipSci___Whole_Exome_sequencing___BPD

  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 blood and platelet disorders

  Study EGAS00001001976

• HipSci___Whole_Exome_sequencing___Monogenic_Diabetes

  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 Monogenic Diabetes.

  Study EGAS00001001140

• HipSci___Whole_Exome_sequencing___Bardet_Biedl_Syndrome

  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 Bardet-Biedl syndrome

  Study EGAS00001000969

• HipSci___Whole_Exome_sequencing___Congenital_hyperinsulinia

  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 congenital hyperinsulinia

  Study EGAS00001001977

• HipSci___Whole_Exome_sequencing___Ataxia

  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 hereditary cerebral ataxia

  Study EGAS00001001978

• HipSci___Whole_Exome_sequencing___Kabuki

  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 Kabuki syndrome

  Study EGAS00001001981

• HipSci___Whole_Exome_sequencing___HSP

  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 hereditary spastic paraplegia

  Study EGAS00001001979

• HipSci___Whole_Exome_sequencing___Battens

  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 Battens disease

  Study EGAS00001001975

• HipSci___Whole_Exome_sequencing___Macular_dystrophy

  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 Macular dystrophy

  Study EGAS00001001982

• HipSci___Whole_Exome_sequencing___PID

  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 blood and platelet disorders

  Study EGAS00001001983

• Proteotranscriptomic classification and characterization of pancreatic neuroendocrine neoplasms

  Pancreatic neuroendocrine neoplasms (PNENs) are biologically and clinically heterogeneous neoplasms. We used a multi-omics approach to uncover the molecular factors underlying this heterogeneity and derive a potential disease classification. Transcriptomic analysis of 84 primary PNEN specimens, drawn from two cohorts (n = 36 and 48), identified four subgroups with distinct molecular profiles. Whole-exome sequencing revealed subgroup-enriched mutational differences.

  Study EGAS00001005024

• Organoid Derivation Project: WGS (2023-06-22)

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients. . This dataset contains all the data available for this study on 2023-06-22.

  Dataset EGAD00001011090

• Indonesian Microbiome Ecology and Evolution v1 - Data Access Policy

  This Data Access Policy sets forth the terms, conditions, and limitations governing access to and use of the raw sequencing data of samples in the Indonesian Microbiome Ecology and Evolution (IndoMEE) v1 dataset by individuals who are not part of the Data Producer. The IndoMEE v1 dataset comprises 126 human faecal samples collected across Indonesia between 2015 and 2021, that was collected to study patterns of human microbiome variation across Indonesia’s diverse geography and lifestyles.

  Dac EGAC50000000587

• RNA-seq of STIC lesions and adjacent normal samples

  In this study, we characterize premalignant lesions of the fallopian tube (serous tubal intraepithelial carcinomas) to explore the earliest events of tumorigenesis following mutation of the TP53 tumor suppressor gene. We conduct laser capture microdissection to isolate premalignant cells from adjacent normal cells, and subject isolated tissues to RNA-seq. Our findings reveal the earliest transcriptional changes established during premalignancy within the fallopian tube.

  Dataset EGAD50000000289

• colorectal_epigenome

  Three different types of samples were used: 19 normal adjacent, 17 adenoma and 19 colorectal tumor tissue samples. This included 10 pairs of colorectal cancer and normal samples and 1 pair of adenoma-normal samples of the same patient. Tissue specimens were formalin-fixed paraffin-embedded (FFPE). DNA was isolated using the QIAamp FFPE Tissue kit (Qiagen, Hilden, DE) according to the manufacturer’s instructions. The processed DNA was run on the Illumina Human MethylEPIC® v1.0 BeadChip array.

  Dataset EGAD00010002726

• SG Peranakan Project dataset

  This dataset contains the genotypes jointly-called from whole genome sequencing data of 177 self-reported Peranakans in Singapore. Reads were aligned to GRCh37 reference genome and jointly-called with other WGS samples. Basic quality control measures and population phasing without reference were performed on the called genotypes. The data are stored in VCF v 4.3 format, and one .vcf.gz file stored the genotypes from one of the 23 chromosomes (22 autosomes+X chromosome).

  Dataset EGAD00001007786