9295 results for "cancer rna-seq"

in 32.45 milliseconds.

• RNA sequencing data of in vitro differentiated megakaryocyte cells transduced with E527K and WT SRC

  For RNA sequencing (RNAseq), CD34+ hematopoietic stem cells (HSC) were isolated from healthy controls before transduction with WT-SRC and E527K-SRC lentiviral vectors in triplicate and differentiation to MK. RNA was extracted from the complete cell population as the aim was to detect differences in genes regulating MK maturation and differentiation. A total of six WT-SRC and six E527K-SRC RNA samples were used for RNAseq to identify differentially expressed genes.

  Study EGAS00001005808

• MMP-seq cell lines (FASTQ)

  MMP-seq cell lines (FASTQ)

  Dataset EGAD00001001107

• MMP-seq tumor samples (FASTQ)

  MMP-seq tumor samples (FASTQ)

  Dataset EGAD00001001108

• scRNA-seq and scATAC-seq data of bone marrow

  17 scRNA-seq and 16 scATAC-seq datasets on bone marrows derived from 16 patients. The sequencing dataset consists of 5 samples without bone marrow infiltration, defined as controls (C1, C2, C3, C4, and C5) and 11 neuroblastoma infiltrated bone marrow samples from patients with MYCN amplification (M1, M2, M3, M4), ATRX mutations (A1, A2), and cases lacking either alteration (S1, S2, S3, S4, S5).

  Dataset EGAD00001008635

• CITE-Seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) of CLL_24

  To explore intratumor-heterogeneity of CLL_24 using single-cell multi-omics approach, we generated single-cell CITE-seq data for CLL_24, coupling scRNA-seq and protein surface marker measurements with oligo-tagged antibodies.

  Dataset EGAD00001009174

• DNA methylation (MCIP-seq) of human acute leukemias and healthy donors

  MCIP-seq of 77 primary samples obtained from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). Moreover, MCIP-seq of CD34+ HSPCs from 3 healthy donors is included.

  Dataset EGAD00001011052

• ChIP Seq data of multiple myeloma and plasma cell leukaemia cell lines

  ChIP-seq data (H3K4Me1, H3K4Me3, H3K27Ac histone modifications) on multiple myeloma cell line KMS11 and plasma cell leukaemia cell lines L363 and JJN3

  Study EGAS00001002414

• Study of tumor RNA expression differences between treated and untreated PitNET patients

  The goal of the study is to evaluate response of PitNET to drug therapy before surgery. Patients with and without drug therapy are compared in RNA level. The RNA is extracted from surgery material, sequenced and deferentially expressed genes (DEG) determined.

  Study EGAS00001004736

• miRNA seq data of 13 cases

  miRNA seq data of 13 cases (MMML)

  Dataset EGAD00001001632

• Oncogenic cooperation between the TCF7-SPI1 fusion and NRAS(G12D) requires β-catenin activity to drive T-cell acute lymphoblastic leukemia.

  In this study we investigate the role of TCF7-SPI1 fusions, more specifically in cooperation with RAS mutations. We make use of patients samples. This study contains paired-end RNA sequencing of the patients, Oxford Nanopore Technologies (ONT) sequencing, single cell RNA sequencing and RNA sequencing of treatment with inhibitors of these samples.

  Study EGAS00001005097

• Raw DNA and RNA data from breast cancer organoids, control samples and biopsies

  Whole genome sequencing data for primary tumors, matching control material from blood and their corresponding organoid. Whole transcriptome data for organoids.

  Dataset EGAD00001003751

• Dataset for liposarcoma-RNA

  Rare cancer sequencing data of 40 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008854

• Somatic L1 retrotransposition in normal colorectal epthelium

  Throughout an individual’s lifetime, genomic alterations accumulate in somatic cells. However, the mutational landscape induced by retrotransposition of long interspersed nuclear element-1 (L1), a widespread mobile element in the human genome, is poorly understood in normal cells. Here, we explored the whole-genome sequences of 406 normal colorectal clones, 12 MUTYH-associated adenomatous clones, and 19 matched colorectal cancer tissues. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 (in 139 clones) and read-through RNA expression profiles (in 116 clones) to investigate the epigenetic regulation of L1 activity.

  Dataset EGAD00001010183

• ChIP-seq of primary AML patients with t(3;3)/inv(3)

  ChIP-seq was conducted in blasts from patients with t(3;3) AML to assess differences of the GATA2 super-enhancer between the translocated allele and the non-translocated allele. The dataset includes 2x H3K27ac ChIP-seq and 1x MYB ChIP-seq. ChIP samples were processed according to the Illumina TruSeq ChIP Sample Preparation Protocol (Illumina) or Diagenode Library V3 preparation protocol (Diagenode) and either sequenced single-end (1x 50 bp) on the HiSeq 2500 platform (Illumina) or paired-end (2x100 bp) on the Novaseq 6000 platform (Illumina). Briefly, reads were aligned to the human reference genome build hg19 with bowtie for single-end runs and bowtie2 for paired-end runs.

  Dataset EGAD00001006821

• Whole genome landscape of adult T-cell leukemia/lymphoma

  Whole-genome sequence (WGS) data of tumor-normal pairs from 139 ATL patients and RNA sequence (RNA-seq) data of tumors from 28 ATL patients.

  Dataset EGAD00001008289

• scRNAseq of colonic organoids derived from biopsies taken from healthy human individuals treated with IL22

  scRNAseq dataset of colonic organoids derived from epithelium from biopsies taken from three healthy human individuals. The organoids have either been grown in standard conditions (control) or treated with IL22 (treated). Includes 6 samples in total, one control from each individual (ctrl1, ctrl2, ctrl3) and one treated from each (treat1, treat2, treat3). The samples have been multiplexed using the antibody hashing technique. The 6 samples have been pooled into the one organoids sample. In order to analyse the raw files, they have to be demultiplexed first. Information necessary for demultiplexing, as well as which files belong to which sample, can be found in the map_file.csv, attached to each sample. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into HTO (hashtag) and RNA (transcriptome) files. HTO has one index (I1) and two read (R1, R2) files and RNA has two index (I1, I2) and two read (R1, R2) files. The fastq files are for the pooled (organoids) sample and need to be demultiplexed. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Since count matrices have been created after the demultiplexing step, there’s one matrix for each of the 6 individual samples. scRNA-seq data from human colon organoids was analysed in the same manner as for the Colitis dataset, apart from the following changes. Data was generated with the Cell Hashing technique, which uses oligo-tagged antibodies against surface proteins to barcode single cells. This allows for samples to be multiplexed together and run in a single experiment. The data was demultiplexed using the HTODemux() function from Seurat (Hao et al., 2021).

  Dataset EGAD00001010168

• BLUEPRINT: DNaseI-seq for monocytes

  DNaseI-seq for monocytes

  Dataset EGAD00001000674

• MMP-seq tumor samples, UDG treated (FASTQ)

  MMP-seq tumor samples, UDG treated (FASTQ)

  Dataset EGAD00001001104

• PhIP-Seq Serum 1000IBD

  PhIP-Seq experiment conducted in Eran Sigal's group at WIS.

  Dataset EGAD00001010118

• Tam-Seq of HGSOC samples for fixative comparison study

  Targeted amplicon sequencing of samples as part of the study "Methanol-based fixation is superior to buffered formalin for next-generation sequencing of DNA from clinical cancer samples. The amplicon panel consists of 48 amplicons in TP53, PTEN, EGFR, PIK3CA, KRAS and BRAF genes as described previously [Forshew, STM 2012]. All libraries were pooled and quantify using DNA 1000 kit on Agilent 2100 Bioanalyzer and KAPA SYBR FAST ABI Prism qPCR Kit (KAPA Biosystems) on 7900HT Fast Real-Time PCR System (Applied Biosystems) according to the supplier's recommendations. Reads were aligned using bwa-mem v0.7.12-r1039 to the 1000 genomes version of human genome build GRCh37, retaining duplicate reads.

  Dataset EGAD00001001937

• Metagenomic Analysis to Identify Novel Infectious Agents in Systemic Anaplastic Large Cell Lymphoma

  Anaplastic large cell lymphoma (ALCL) is a rare T-cell non-Hodgkin lymphoma (NHL). Risk of systemic ALCL is markedly increased among immunosuppressed people, such as those with human immunodeficiency virus (HIV) infection or solid organ transplant recipients. This increased risk in immunosuppressed populations suggests a viral etiology, given similar elevations for diffuse large B-cell lymphoma (DLBCL), Burkitt lymphoma, and Hodgkin lymphoma (caused by Epstein-Barr virus [EBV]) and other virus-related cancers in immunosuppressed individuals. EBV might be a plausible candidate, but most reported ALCL tumors are EBV-negative. Therefore, we conducted a metagenomic analysis of microbial associations with ALCL to determine whether a known or novel pathogen is associated with the tumor. We obtained archived formal fixed paraffin embedded (FFPE) ALCL tumor tissue from the Iowa cancer registry and an additional case from an immunosuppressed individual infected with human immunodeficiency virus. Controls included 3 diffuse large B-cell lymphomas (DLBCLs) in transplant recipients (shown to be related to Epstein-Barr virus [EBV] by in situ hybridization) and 3 breast cancers (no known viral etiology). RNA was extracted from FFPE specimens, and total RNA libraries were prepared using the KAPA RNA HyperPrep Kit (Roche). Five samples (IA01, IA53, IA57, IA07, and IA17) were sequenced on a NextSeq 500 (Illumina) and the remainder on a NovSeq 6000 (Illumina). Using novel computational approaches, we eliminated human reads and aligned residual non-human reads to known microbial references using GATK-PathSeq or conducted de novo assembly of unassigned reads using virID pipeline. Although EBV was detected in the 3 DLBCL controls, we did not detect EBV or any novel pathogen in ALCL tumors or in the breast cancers. Our study had a modest sample size and only one case arising in HIV-infected individual. Therefore, further studies are required to characterize the metagenome of systemic ALCLs, especially cases arising in immunosuppressed people.

  Study phs002064

• RCC methyl-seq data

  methyl-seq data 64 cases

  Dataset EGAD00001009867

• RCC ATAC-seq data

  ATAC-seq data 72cases

  Dataset EGAD00001009868

• Chromatin accessibility (ATAC-seq) of human acute leukemias and healthy donors

  ATAC-seq of 79 primary samples obtained from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). ATAC-seq of CD34+ HSPCs from 3 healthy donors is also included.

  Dataset EGAD00001011050

• H3K27ac ChIP-seq of human acute leukemias and healthy donors

  H3K27ac ChIP-seq of 79 primary samples derived from human acute leukemias, namely AML, T-ALL and mixed myeloid/lymphoid leukemias with CpG Island Methylator Phenotype (CIMP). In addition, 4 samples derived from CD34+ cord blood cells of healthy donors were included.

  Dataset EGAD00001011060