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• 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

• Processed naive B cell AIRR-seq data

  This dataset contains processed productively rearranged BCR sequences (tsv file format) from bulk AIRR-seq of naive peripheral blood B cells from 102 subjects with celiac disease and 102 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 EGAD50000002730

• 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

• ScRNA-seq of PBMC and whole blood samples reveales a dysregulated myeloid cell compartment in severe COVID-19

  In a dual-center, two-cohort study, we performed single-cell RNA-sequencing of whole blood and peripheral blood mononuclear cells to determine changes in immune cell composition and activation in mild vs. severe COVID-19 over time. This study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.

  Dataset EGAD00001006550

• GEL WGS Comparison

  These samples are to be analysed with the CGP Developed cancer panel and the results will be compared with WGS data from 4 different comercial providers.

  Dataset EGAD00001000872

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectum patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectum patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003606

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003612

• Genome and transcriptome sequence data from an adenocarcimona of the lung patient

  Genome and transcriptome sequence data from an adenocarcimona of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003616

• Genome and transcriptome sequence data from a mucinous colloid carcinoma of the pancreas patient

  Genome and transcriptome sequence data from a mucinous colloid carcinoma of the pancreas patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004598

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectosigmoid patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectosigmoid patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004627

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the stomach patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the stomach patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004619

• Genome and transcriptome sequence data from a metastatic mmmt of the endometrium patient

  Genome and transcriptome sequence data from a metastatic mmmt of the endometrium patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004618

• Genome and transcriptome sequence data from a ganglioglioma of the left temporal lobe patient

  Genome and transcriptome sequence data from a ganglioglioma of the left temporal lobe patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004615

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004634

• Paroxysmal Neurological Disorders 2

  We are sequencing the exomes of patients with paroxysmal neurological disorders mainly focusing on migraine and epilepsy. Cases are collected from performance sites of members of the International Headache Genetics consortium and EuroEPINOMICS. Most cases have a strong family history. The study sample will include both cases and controls.

  Dataset EGAD00001000407

• Paroxysmal neurological Disorders

  We are sequencing the exomes of patients with paroxysmal neurological disorders mainly focusing on migraine and epilepsy. Cases are collected from performance sites of members of the International Headache Genetics consortium and EuroEPINOMICS. Most cases have a strong family history. The study sample will include both cases and controls.

  Dataset EGAD00001000412

• Genome and transcriptome sequence data from a metastatic adenoid cystic carcinoma of the breast patient

  Genome and transcriptome sequence data from a metastatic adenoid cystic carcinoma of the breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004921

• Genome and transcriptome sequence data from a squamous cell carcinoma of the alveolar ridge patient

  Genome and transcriptome sequence data from a squamous cell carcinoma of the alveolar ridge patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001004934

• Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma of the nasopharynx tumor patient

  Genome and transcriptome sequence data from a embryonal rhabdomyosarcoma of the nasopharynx patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015307

• The evolution of ovarian high grade serous carcinoma from STIC lesions

  We performed Ampliseq on 11 samples on a targeted panel of 17 genes.

  Study EGAS50000000361

• Whole-genome sequences from uveal melanomas and matched normals

  The dataset comprises whole-genome sequences from 40 primary uveal melanomas and their matched normal samples.

  Dataset EGAD50000002292

• GLASS-NL shallow whole genome sequencing (sWGS) tumor samples

  Shallow whole genome sequencing (sWGS) of 227 initial and recurrent tumor samples from 105 patients in the GLASS-NL cohort.

  Dataset EGAD50000000581

• TAVAREC Methylation

  DNA methylation profiles of samples included in the EORTC 26091 TAVAREC trial

  Dataset EGAD00010002289

• CPCG-200PG-ARRAY

  Raw Array data from the CPCGene 200PG study

  Dataset EGAD00010001218

• whole genome sequencing data of LMS cell lines

  The data set contains bam files aligned using bwa-0.7.8 mem -t 8 -R.

  Dataset EGAD00001003827

• BS-seq in plasma of CRC patients

  We performed whole genome bisulfite sequencing of plasma DNA in 11 colorectal cancer patients to study the colonic DNA in plasma.

  Dataset EGAD00001004568

• Peruvian Population Genomics: Unraveling the Genetic Landscape and Admixture Dynamics of Urban Populations

  Genome-wide study of human populations living in Peruvian urban areas

  Study EGAS00001008264

• Congenital Heart Disease - Pilot

  This pilot study aims to generate pilot data to inform future study designs by resequencing the whole exomes of 10 unrelated individuals diagnosed with Congenital Heart Disease (CHD).

  Dataset EGAD00001000351

• Organoid Derivation Project TGS: Release 1

  Targeted gene sequencing of cancer driver genes to determine the driver mutations present in newly-derived cancer organoid models

  Dataset EGAD00001004368

• Whole genome SMRT sequencing in the HF-GBM-Tumor-Neurosphere-Xenograft study

  This data set consists of whole genome SMRT sequencing fastqs generated from 2 xenograft samples.

  Dataset EGAD00001002264

• shallow whole genome sequencing dataset

  shallow whole genome sequencing dataset contains 44 samples. all the samples are early stage high ovarian high grade serous carcinoma.

  Dataset EGAD00001008588

• Access to public datasets in the EGA

  Dac EGAC00001000514

• WES of Multiple myeloma/MGUS cases (germline) - Fastq files

  WXS - Exome capture using the Twist Human Core Exome Kit on germline DNA, paired-end (2x100bp) sequencing on a NovaSeq system. Number of samples: 295

  Dataset EGAD50000001799

• Nanopore targeted sequencing of the CFTR gene in Moroccan patients with suspected cystic fibrosis

  This dataset contains fastq files sequencing with Oxford Nanopore (MK1C)

  Dataset EGAD50000002062

• PBAT sequencing of human embryonic stem cells

  To assess the DNA methylation landscape of naïve human embryonic stem cells derived from ERKi or control blastocysts using PXGL or UXGL media.

  Dataset EGAD50000001475

• HDAC inhibitor quisinostat in synovial sarcoma cell lines

  An RNA Seq study of the effects of HDAC inhibitor Quisinostat on six different synovial sarcoma cell lines

  Dataset EGAD00001003810

• Bone Cancer - Rare Types Whole Genome

  We propose to definitively characterise the somatic genetics of a selection of rare bone cancers through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Dataset EGAD00001000785

• Exome sequencing of Bilateral Anophthalmia cases- Pilot Study

  This pilot study aims to generate pilot data to inform future study designs by resequencing the whole exomes of 10 unrelated individuals diagnosed with Bilateral Anophthalmia.

  Dataset EGAD00001000348

• Melanoma microRNA profiling

  This dataset includes microRNA profiling of 61 early-passage metastatic melanoma cell lines. The data are provided as single-end small RNA seq fastq files.

  Dataset EGAD00001006269

• Melanoma transcriptome profiling

  This dataset includes transcriptome profiling of 68 early-passage metastatic melanoma cell lines. The data are provided as paired-end RNA seq fastq files.

  Dataset EGAD00001006270

• Single-cell dissection of the immune response after a myocardial infarction

  38 STEMI patients at hospital admission, 24 hours (acute phase) and 6-8 weeks (chronic phase) after STEMI

  Dataset EGAD00001010064

• Chromatin accessibility profiles of bulk Acute Myeloid Leukemia (AML) samples

  Chromatin accessibility profiles of bulk Acute Myeloid Leukemia (AML) samples, 60 datasets. Part of the study EGAS00001004893 and EGAS00001004896.

  Dataset EGAD00001010299

• Paired-end Whole Exome-seq analysis of the 3D spatially mapped GBM samples.

  Dataset contains 50 paired-end Whole Exome sequencing samples from 3 patients. 3 normal blood samples are also included.

  Dataset EGAD00001010289

• H3K27ac ChIPseq of cohesin-mutated and wildtype adult AMLs

  ChIP-seq targeting the H3K27ac histone modification in cohesin-mutated (STAG2 or RAD21 mutation) and cohesin wildtype (CTRL-AMLs) AMLs.

  Dataset EGAD00001011204

• Non-Coding Mutations Cause Enhancer Targeting Resulting in Protein Synthesis Dysregulation During B-Cell Lymphoma Progression

  In this study, we performed whole-genome sequencing of longitudinal tumor pairs, representing transformation of follicular lymphoma (FL) to high grade B-cell lymphoma with MYC and BCL2 rearrangements (known as "double hit lymphoma" or DHL), a very aggressive class of non-Hodgkin B cell lymphoma (B-NHL). We identified coding and noncoding genomic alterations acquired during the course of lymphoma progression.

  Study phs003398

• Single-Cell RNA-Sequencing of Bone Marrow and Circulating Tumor Cells from Patients with Multiple Myeloma and its Precursor Conditions

  We performed single-cell RNA and V(D)J-sequencing of tumor cells from bone marrow and peripheral blood specimens and patients with Monoclonal Gammopathy of Undetermined Significance (MGUS), Smoldering Multiple Myeloma (SMM), and Multiple Myeloma (MM), as well as healthy donors. In this study we aimed to shed light on the mechanisms underlying tumor cell circulatory capacity and dissemination.

  Study phs003855

• 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

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0063_000

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0063_000 for Triple negative breast cancer patient-derived xenograft SA609X3XB01584

  Dataset EGAD00001011209

• 10x Single Cell Gene Expression Library TENX068

  10x Single Cell Gene Expression library TENX068 for Triple negative breast cancer patient-derived xenograft SA609X4XB03080

  Dataset EGAD00001011210

• 10x Single Cell Gene Expression Library TENX069

  10x Single Cell Gene Expression library TENX069 for Triple negative breast cancer patient-derived xenograft SA609X4XB03083

  Dataset EGAD00001011211

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0150_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0150_001 for Triple negative breast cancer sample SA609X5XB03230

  Dataset EGAD00001011212