15028 results for "cancer studies using rna-seq"

in 18.43 milliseconds.

• Building a Database of Genomic Structural Variants in Japanese population

  Purified genomic DNA was purchased from Japanese B cell DNA bank; We sequenced those genomic DNAs using PacBio and 10X Genomics sequencing technologies, and analyzed genomic structural variations.

  Study JGAS000173

• Genomic Structural Variants in Japanese Malignant mesothelioma patients

  We extracted genomic DNAs from established mesothelioma cell lines from Japanese malignant mesothelioma patients. We sequenced those genomic DNAs using 10X Genomics sequencing technologies, and analyzed genomic structural variations.

  Study JGAS000176

• Building a Database of Genomic Structural Variants in Japanese population

  Purified genomic DNA was purchased from Japanese B cell DNA bank; We sequenced those genomic DNAs using PacBio Sequel and Sequel II and analyzed genomic structural variations.

  Study JGAS000286

• WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set6)

  The dataset includes FASTQ and CRAM files from diagnostic and matched remission (control) samples of one B-other ALL patients (ALLK-138). Sequencing library was made using Novogene NGS DNA Library Prep Set. Both diagnostic (90x) and remission (30x) samples were sequenced using NovaSeqX Plus.

  Dataset EGAD50000002161

• WES data of primary tumors and metastasis corresponding to three patients

  Fastq files of WES data. Primary tumor and/or metastasic samples of three chRCC patients. DNA libraries were produced using the SureSelect XT HumanAllExon V5 kit (Agilent Technologies), and sequencing was performed in a HiSeq instrument (Illumina) using a 100-bp paired-end mode.

  Dataset EGAD00001010173

• Chromatin_Profiling_in_Twins

  50 lymphoblastoid cell lines of adult female Twins which are part of the MuTHER study, subjected to Chromatin Immunoprecipitation using an antibody for H3K4me1. H3K4me1 peaks mark distal regulatory elements.

  Study EGAS00001000098

• Covid19 WGS Raw Read files

  The Samples were collected from Saint James's Hospital, Dublin and after informed consent Extracted Genomic DNA samples were prepared and sequenced using the Automated Illumina TruSeq PCR-free methodology.

  Study EGAS00001007106

• WES data generated in multifocal ileal NETs study

  This dataset includes whole-exome sequencing data for multifocal ileal tumor samples from two patients. Exonic sequences were enriched using the Agilent V2 capture probe set and sequenced by 76-bp paired-end reads using the Illumina Genome Analyzer IIx system with a mean coverage of 80x for each base

  Dataset EGAD00001006408

• Illumina whole genome sequencing data for two patients with congenital disease

  BAM files with sequencing reads derived from Illumina whole genome sequencing of two DNA samples from lymphoblastoid cell lines from two patients with congenital disease. Whole genome sequencing was performed using Illumina HiSeq X Ten and samples were prepared using TruSeq library prep.

  Dataset EGAD00001003510

• PCNSL single cell dataset

  Mononuclear cells were isolated as cell suspensions by dissociation in a BD Horizon™ Dri Tumor & Tissue Dissociation Reagent (BD Biosciences) using a gentleMACS dissociator (Miltenyi Biotec). A totalseq-C antibody cocktail (Biolegend) was used, and the cell suspensions were diluted to a concentration of 1,000 cells/μL. Library sequencing was performed using the DNBSEQ-G400 (MGI Tech), Illumina HiSeq 2000, or Illumina NovaSeq 6000 5 (Illumina). The FASTQ files were aligned to the 10x provided reference genome using 10x Genomics Cell Ranger software v7.1.0 to create unique molecular identifier count tables of gene expression of the samples.

  Dataset EGAD50000000685

• 3q-capture DNA sequencing of atypical 3q26 cases

  3q-capture DNA sequencing was performed as we described previously 13. In summary, genomic DNA was fragmented using the Covaris shearing device (Covaris), and sample libraries were assembled following the TruSeq DNA Sample Preparation Guide (Illumina). After ligation of adapters and an amplification step, target sequences of chromosomal regions 3q21.1-q26.2 were captured using custom in-solution oligonucleotide baits (Nimblegen SeqCap EZ Choice XL). The design of target sequences was based on the human genome assembly hg19: chr3q21.1:126036241-130672290 - chr3q26.2:157712147-175694147. Amplified captured sample libraries were paired-end sequenced (2x100 bp) on the HiSeq 2500 platform (Illumina) and aligned against the hg19 reference genome using the Burrows-Wheeler Aligner (BWA)25

  Dataset EGAD00001006123

• Sequencing of liver cancer cell lines

  Liver cancer is a dreadful disease with limited therapeutic options. How to translate genomic findings into biomarkers and precision treatment is challenging. A large cell line-based platform was established, termed as Liver Cancer Model Repository. Heterogeneities in patients were faithfully recapitulated by 81 liver cancer cell lines at genomic and transcriptomic levels. This platform provides a rich resource and models to study cancer drivers and drug responses in liver cancer.

  Study EGAS00001002237

• Identifying the role of ID3 in DNA repair and maintenance of genome integrity (ATAC-seq)

  Dataset EGAD00001008199

• EAC-protein

  This dataset contains single cell protein tag sequencing of EAC samples by 10x Genomics CITE-seq. Total number of files - 24. File format - FASTQ.

  Dataset EGAD50000000751

• Single-cell G&T sequencing - Transcriptomic data

  Single-cell G&T seq from an untreated PDX mouse with neuroblastoma (MYCN amplified).

  Dataset EGAD50000001514

• Low coverage whole genome sequencing form CSF-derived cell free DNA

  Low coverage whole genome sequencing form CSF-derived cell free DNA for matching samples with EM-seq cohort

  Dataset EGAD50000002148

• Histone modifications of cfDNA

  59 samples are sequenced, 18 are HCC and beta thalassemia cases while the remaining are control case.

  Dataset EGAD00001009267

• SF10679

  SF10679 snATAC Seq. Oligodendroglioma, Anaplastic (WHO gr. 3). Tumor Location: Frontal Age: 43. Sex: Male.

  Dataset EGAD00001006312

• Nascent transcriptome in T-ALL

  Nascent transcriptome (GRO-seq) data representing bone marrow mononuclear cells of two diagnostic T-ALL samples.

  Dataset EGAD00001008410

• SF4007

  SF4007 snATAC Seq. Oligodendroglioma (WHO gr. 2) Tumor Location: Left frontotemporal. Age:33. Sex: Female.

  Dataset EGAD00001006317

• DLBCL Validation (FFPE) Cohort

  miRNA-seq Cohort of 140 Formalin Fixed Paraffin Embedded Diffuse Large B-cell Lymphoma Patient Samples

  Dataset EGAD00001001073

• Immunogenomics of colorectal cancer response to immune checkpoint blockade

  Molecular and cellular determinants of response to immune checkpoint inhibitors are mostly unknown. Here we use whole exome, RNA and T cell receptor sequencing, imaging mass cytometry, immunohistochemistry and PD1-PDL1 interaction detection to profile 543 regions from 16 colorectal cancers (CRCs) subsequently treated with Pembrolizumab or Nivolumab. Independent of treatment response, CRCs express low levels of PD1 and PDL1 proteins and form less PD1-PDL1 complex than other cancers. Non hypermutated CRCs have no benefit from treatment, show WNT activation and low T cell infiltrates. Among hypermutated CRCs, those with durable benefit have clonal immunogenic alterations, clonally expanded T cells and potential for immune escape through dysfunctional antigen presentation. Responsive tumours are enriched in PD1-expressing cytotoxic and proliferating CD8 T cells and PDL1-expressing antigen presenting macrophages, which form high-density clusters of interacting cells. Our study shows that immune checkpoint inhibitors are most effective in highly infiltrated CRCs where they may release the interactions between macrophages and CD8 T cells thus promoting their priming and expansion in intra-tumour niches.

  Study EGAS00001004438

• GoNL aligned sequence data in BAM format.

  We mapped the data to the UCSC human reference genome build 37 using BWA 0.5.9-r16. We first mapped each read pair separately using bwa aln. Then we used bwa sampe to map the paired reads together to a BAM9 file. The BAM file was then sorted by genomic position and indexed using PicardTools-1.32 SortSam. To prevent PCR artifacts from influencing the downstream analysis of our data, we used Picard to mark the duplicate reads, which were ignored in downstream analysis. We used GATK IndelRealigner on our data around known indels (from 1KG Pilot). The IndelRealigner creates all possible read alignments using the source and computes the likelihood of the data containing the indel based on the read pileup. Whenever the maximum likelihood contains an indel, the reads are realigned accordingly. Each base is associated with a phred-scaled base quality score. Calibration of Phred scores is crucial as they are used in some of the downstream analysis models. We used GATK to recalibrate the base qualities with respect to (i) the base cycle, (ii) original quality score, and (iii) dinucleotide context. To minimize issues stemming from mapping problems around indels, we decided to undergo a second round of indel realignment using the GATK IndelRealigner by family rather than by individual. For this second round, we considered two sources of possible indels: 1KG Phase 1 indels and indels aligned by BWA in the GoNL data.

  Dataset EGAD00001001038

• Basal-to-Inflammatory Transition Contributes to Basal Cell Carcinoma Therapy Resistance via Crosstalk with a Pro-Inflammatory Stromal Niche

  Overcoming tumor evolution and inducible resistance states remain the main challenge to creating successful anti-tumor therapies. The body's cancer-associated inflammatory response is a double-edged sword having ill-defined pro- and anti-tumor properties. Our group previously identified a basal cell carcinoma (BCC) tumor-intrinsic resistance pathway called basal to squamous cell carcinoma transition (BST). However, tumor resistance driven through the complex dynamics of tumor interactions with the inflammatory response remains poorly studied. Here, employing a multipronged approach combining human tumor single-cell transcriptomics, single-cell chromatin accessibility (scATAC-Seq) study, CODEX multiplexed imaging, spatial transcriptomic along with functional validation, we have identified a surprising inflammation-associated SMOi therapy enriched tumor epithelial cell state we term basal-to-inflammatory transition (BIT). Marked by CHI3L1, TAGLN, ITGAV, and VCAM1, BIT arises in spatially distinct neighborhoods from BST in a subset of naive BCCs. While BST tumor epithelium occurs within the central cores of tumor nodules, BIT tumor epithelium arises in a specialized inflammatory environment defined by a tumor associated TREM1 myeloid signature. IL1 and OSM secreted by TREM1 myeloid cells activate the inflammatory NF-kB family of transcription factors within the BIT tumor epithelium. Strikingly, IL1 and OSM ligands are sufficient not only in inducing the BIT tumor state in vitro and in vivo in a synergistic fashion but also in lowering the sensitivity of human BCC explant tumors to SMOi treatment. This work provides critical insights into the BIT-resistant state as a novel targetable tumor state driven by a specialized inflammatory microenvironment.

  Study phs003437

• DAC for BCP-LBL Kiel

  Whole exome sequencing and RNA sequencing of B-Cell Precursor Lymphoblastic Lymphoma tissue biopsies.

  Dac EGAC50000000181