12056 results for "cancer rna-seq"

in 17.85 milliseconds.

• Locally advanced prostate cancer cohort

  Fastq files from RNA sequencing and BAM files from tNGS of normal and tumor samples from 17 patients from the locally advanced prostate cancer cohort.

  Dataset EGAD50000002380

• Development of Computational Approaches for Cell Hashing in scRNA-Seq

  As a test of cell overloading after cell hashing, a sample of peripheral blood mononuclear cells (PBMC) from a single subject was separated into naive T cells, memory T cells, and non-T cell PBMC populations using fluorescence activated cell sorting (FACS). Each population was separated into two technical replicates, then stained with BioLegend TotalSeq-A antibodies. All 6 samples were pooled, then loaded into 6 wells of a 10X Genomics Chromium 3' RNA-seq v3 chip at increasing cell counts: 16,000 (k), 24k, 32k, 48k, 64, and 80k cells per well. We also included a single sample that was not hashed or pooled, as well as a single sample that was stained with hashing antibodies, but not pooled in two separate wells.

  Study phs002695

• RNA-seq of longitudinal human blood and nose swab samples from a controlled human infection experiment with SARS-CoV-2 virus

  Controlled human infection experiments enable longitudinal profiling of immune responses to a pathogen. 36 healthy volunteers aged 18-29 years, with no evidence of previous infection or vaccination, were inoculated with SARS-CoV-2 virus and quarantined for 14 days. Blood samples for RNA sequencing were collected into PAXgene tubes before virus challenge, 6 hours after challenge, daily thereafter for 14 days and on day 28. Mid-turbinate nose swabs for RNA sequencing were collected before virus challenge, and on days 1, 3, 5, 7, 10 and 14 after challenge, preserved in RNAprotect.

  Study EGAS50000000667

• Glioblastoma stem cell lines RNA-seq (Guilhamon et al.)

  RNA was extracted from GSCs using the Qiagen RNeasy Plus kit. RNA sample quality was measured by Qubit (Life Technologies) for concentration and by Agilent Bioanalyzer for RNA integrity. All samples had RIN above 9. Libraries were prepared using the TruSeq Stranded mRNA kit (Illumina). Two hundred nanograms from each sample were purified for polyA tail containing mRNA molecules using poly-T oligo attached magnetic beads, then fragmented post-purification. The cleaved RNA fragments were copied into first strand cDNA using reverse transcriptase and random primers. This is followed by second strand cDNA synthesis using RNase H and DNA Polymerase I. A single “A” base was added and adapter ligated followed by purification and enrichment with PCR to create cDNA libraries. Final cDNA libraries were verified by the Agilent Bioanalyzer for size and concentration quantified by qPCR. All libraries were pooled to a final concentration of 1.8nM, clustered and sequenced on the Illumina NextSeq500 as a pair-end 75 cycle sequencing run using v2 reagents to achieve a minimum of ~40 million reads per sample.

  Dataset EGAD00001006813

• Adult-type Granulosa Cell Tumour of the Ovary

  A recurrent mutation in FOXL2 (c.402C>G; p.C134W) is present in over 95% of adult-type granulosa cell tumours (AGCTs). In contrast, various loss-of-function mutations in FOXL2 lead to the development of blepharophimosis, ptosis and epicanthus inversus syndrome (BPES). BPES is characterized by an eyelid malformation often accompanied with primary ovarian insufficiency but not granulosa cell tumours. Two recent studies suggest that FOXL2 C402G is a gain or change-of-function mutation with altered DNA-binding specificity. Another study proposes that FOXL2 C402G is selectively targeted for degradation inducing somatic haploinsufficiency suggesting its role as a tumour suppressor. The latter study relies on data indicative of an FOXL2 allelic imbalance in AGCTs. Here we present RNA-seq data as genetic evidence that no real allelic imbalance is observed at the transcriptomic level in AGCTs. Additionally, there is no loss of protein expression in tumours harboring the mutated allele. These data and other features of this mutation as compared to other oncogenes and tumour suppressor genes argue strongly against FOXL2 being a tumour suppressor in this context. Given the likelihood that FOXL2 C402G is oncogenic, targeting the variant protein or its downstream consequences is the most viable path forward to identifying an effective treatment for this cancer.

  Study EGAS00001005414

• Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance through Serial Biopsies and Comprehensive Analytics

  This dataset accompanies the manuscript "Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance Through Serial Biopsies and Comprehensive Analytics". In this study we discuss the clinical implications and consequences of molecular heterogeneity in a metastatic breast cancer patient identified through serial biopsies, multi-omic analysis, and longitudinal patient monitoring, performed through the precision oncology program, Serial Measurements of Molecular and Architectural Responses to Therapy (SMMART). This case study describes a metastatic breast cancer patient with a highly heterogenous tumor that began as ER positive/HER2 negative on diagnosis, then was found to be ER negative/HER2 positive in a metastatic liver lesion (Study biopsy #1), and finally triple negative (TNBC) in another metastatic liver biopsy (Study biopsy #2). Multi-omic assays included clinical genomic panel sequencing, clinical immunohistochemistry, a clinical protein profiling assay (Intracellular Signaling Protein Profiling), RNA sequencing, and RPPA. Here we provide the expression data from RNAseq and RPPA data on Study biopsy #2 for the patient discussed in this case report. Note: The first liver biopsy did not yield sufficient material for RNAseq or RPPA.Raw RNA FASTQ files from Study biopsy #2 of the liver Gene expression (RNAseq) files from Study biopsy #2Protein expression (RPPA) files (level 2, 3, 4) for Study biopsy #2

  Study phs002321

• BAM files ChIP-Seq

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001669

• Prostate cancer datasets WGS

  Low pass WGS: 48 samples (5 blood samples from 6 patient data): 22 Tumour cores and 26 normal/benign cores (Next Seq )

  Dataset EGAD00001004466

• Counts: Brain transcriptome of hereditary cerebral haemorrhage with amyloidosis–Dutch type (HCHWA-D)

  These are the log2CPM (log2 counts per million) fragments per gene counts associated with the BAM files in EGAD00001003806, in tab separated format. Counts for 36 postmortem brain samples from 9 non-demented control subjects and 9 Hereditary cerebral hemorrhage with amyloidosis-Dutch type subjects are included (1 Frontal cortex sample and 1 Occipital cortex sample per subject). RNA samples were depleted for ribosomal RNA with the Ribo Zero Gold Human kit (Illumina) and strand specific RNA-Seq libraries were generated. Paired-end sequencing was performed on a HiSeq2500 Illumina system (2x50bp reads). Alignments were performed using GSNAP v2014-12-23 with setting "--npaths 1" on GRCh38 reference genome without the alternative contigs. Fragment per gene counting was performed using HTSeq-count v0.6.1p1 with setting "--stranded reverse". The gene annotation used for quantification were UCSC RefSeq genes for GRCh38 downloaded on 2015-07-13.

  Dataset EGAD00010001457

• RNA-Seq of human longitudinal whole blood samples from PCR-positive and PCR-negative recent household contacts of COVID-19 index cases.

  Little is known about the transcriptomic profile of individuals who are exposed to SARS-CoV-2 yet resist becoming PCR positive. To investigate this, longitudinal whole-blood samples were taken (0, 7, 14, and 28 days after enrolment) from PCR positive and PCR negative SARS-CoV-2-naïve household contacts who were recently exposed to a COVID-19 index. Samples were also taken from pre- and post-pandemic unexposed controls. Total RNA was extracted from PAXgene tubes before undergoing poly(A) selection followed by globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced across 2 flowcells of an Illumina HiSeq 4000.

  Dataset EGAD50000000684