Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

3608d444-44d6-4518-b78f-80110d9ea3c1 - samples

ABSTRACT: Cancer RNA-seq consisting of FASTQ paired-end reads from 6 individuals (4 melanoma, 1 lung cancer). RNASEQ was performed on illumina, Truseq capture kit, 40M-80M clusters. 2 Melanoma datasets contain reads from 1 tumor region and from a tumor derived cell line 2 Melanoma, 1 Colon and 1 lung datasets contain each reads from a single region.

PROVIDER: EGAD00001007951 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

d08e2014-22f3-4bfe-9f92-90073483346a - samples

Project description:Cancer and germline exomes consisting of FASTQ reads from 6 individuals (4 melanoma, 1 lung and 1 colon cancer). Exome sequencing was performed on illumina with a depth of 100x to 200x. 2 Melanoma datasets contain reads from 2 different tumor regions 2 Melanoma datasets contain reads from 1 tumor region and from a tumor derived cell line 1 Melanoma dataset contains reads from 2 healthy tissues Colon and lung datasets contain both 1 matched germline-tumor pair

| EGAD00001007950 | EGA

af948a9d-c0b0-4f49-8242-f03b9ef09f24 - samples

Project description:Cancer RNA-seq consisting of FASTQ single-end reads from 1 colon-cancer individual RNA-seq was performed on illumina This dataset contains reads from a single region.

| EGAD00001007949 | EGA

Tissue Specimens from Patients with Melanoma for Genetic Analysis

Project description:<p>The purpose of this study was to obtain tissue specimens derived from patients with melanoma to generate research tools to advance our understanding of the genetics, pathogenesis, and therapeutics of melanoma. Briefly, tissue was obtained from metastatic lesions and used to generate clonal primary cell lines from melanoma cells and fibroblasts from the tumor microenvironment. RNA was extracted from low passage cell lines using Trizol reagent. cDNA libraries were prepared using the TruSeq mRNA sample preparation kit, v2 (Illumina) and sequenced on the HiSeq 2000 platform (Illumina). The submitted files are bam files that contain both unaligned and aligned reads (human genome, build hg19). </p>

| phs001115 | dbGaP

Genome-wide transcriptome profiling of SK-Mel-28, UACC-62 and HCT-116 cells stably expressing scrambled shRNA and RAB7 shRNA

Project description:Purpose: Assess the transcriptional changes induced upon RAB7 knock-down in melanoma (SK-Mel-28 and UACC-62) and in colon cancer (HCT-116) cell lines. Methods: mRNA profiles of tumor cell lines (SK-Mel-28, UACC-62, HCT-116) stably expressing scrambled shRNA or RAB7 shRNA (harvested at day 3 after lentiviral infection) were generated by deep sequencing, using three biological replicates per condition. The sequence reads that passed quality filters were analyzed with TopHat and Cufflinks. Validation of induced / silenced genes was performed by western blot. Results show a differential impact of RAB7 expression in the transcriptomic profile of melanoma vs non-melanoma cell lines, and support a lineage-specific role of this small GTPase in melanoma. Examination of the mRNA profiles RAB7-depleted vs wild type cells, performed in parallel in 3 different tumor cell lines (Melanomas: SK-Mel-28 and UACC-62, Non-melanoma: HCT-116) harvested at day 3 after lentiviral infection.

2014-04-20 | E-GEOD-42735 | biostudies-arrayexpress

Proteomic approach for searching of universal, tissue-specific and line-specific markers of extracellular vesicles in lung and colorectal adenocarcinoma cell lines: whole cell lysate vs. extracellular vesicles

Project description:The efficiency of anticancer therapy depends heavily on the molecular features of the tumor. Since tumor-derived extracellular vesicles, including exosomes, contain proteins that are characteristic for producer cells and could be detected in biological fluids, they are of great interest for screening of predictive biomarkers. We have performed label-free mass spectrometric profiling of extracellular vesicles originated from human colon cancer cell lines Caco-2, HT-26 and HCT-116, and from lung cancer cell lines NCI-H23 and A549.

2021-09-09 | PXD020454 | Pride

Proteomic approach for searching of universal, tissue-specific and line-specific markers of extracellular vesicles in lung and colorectal adenocarcinoma cell lines:extracellular vesicles only

2021-09-09 | PXD020467 | Pride

Custom Illumina array DNA methylation analysis of 384 CpGs across five cancer types

Project description:Tumor heterogeneity is a major barrier to effective cancer diagnosis and treatment. We recently identified cancer-specific differentially DNA-methylated regions (cDMRs) in colon cancer, which also distinguish normal tissue types from each other. We therefore hypothesized that these colon cDMRs might also be cDMRs for other cancer types. For colon, lung, breast, thyroid, and Wilms tumors, we show stochastic variation in methylation within each tumor type, but involving the same loci across tumor types, with intermediate values of variation for premalignant adenomas. Seeking to increase the precision of DNA methylation measurements over our previous tiling array-based approach, termed CHARM (Comprehensive High-throughput Array for Relative Methylation), we designed a custom nucleotide-specific bead array on the Illumina GoldenGate platform to analyze 151 colon cDMRs from Irizarry et al. (PMID 19151715). The resulting 384 probes covered 139 regions, with 1-7 probes per region. We studied 290 samples, including cancers from colon (10), lung (24), breast (27), thyroid (36), and kidney (Wilms) (25), with matched normal tissues to 111 of these 122 cancers, along with 30 colon premalignant adenomas, 18 normal colon, and 9 normal breast samples.

2011-06-01 | E-GEOD-29505 | biostudies-arrayexpress

Gene expression signatures of the PRMS tumors.

Project description:Several groups identified CSCs in solid tumors, including breast, brain, thyroid, melanoma, colon, pancreatic, liver, prostate, lung, head and neck, ovarian, and stomach cancers, by adopting many biomarkers. Here, we examined PRMS by gene expression microarray analysis for them. As a result, the tumor expressed various specific genes in each CSCs, SCs, FAPs, and PICs.

2022-05-25 | GSE203596 | GEO

RNA-seq data of the Amphotericin (AmB)-resistant Aspergillus strain 211 and its AmB-susceptible sectorized derivative with and without AmB treatment

Project description:Summary taken from our paper “Aspergillus terreus Sectorization: A Morphological Phenomenon Shedding Light on Amphotericin B Resistance Mechanism”: WT and ATSec strains were grown in AMM broth for 30 h at 30 °C. Afterwards, the cultures were subjected to either DMSO (control) or 1 µg/ml AmB treatment for 1 h/4 h. Triplicates of each combination of these factors were made, resulting in a total of 24 samples. RNA was extracted with a Promega GmbH kit (Madison, Wisconsin, USA) following the manufacturer’s instructions. The RNA-seq experiment was conducted by BGI, generating a total of around 20 million 100bp paired-end reads with the DNBSEQ platform. BGI employed SOAPnuke (51) to remove rRNA, adaptor-containing sequences, low quality reads, and reads with high unknown nucleotide content, producing "clean reads" datasets that were used in the analysis. On average, clean read datasets contain 45.1 Mb of reads, while the raw read datasets contain 48.7 Mb. For clean reads, the mean Q20 value is 98.3%, and the mean Q30 value is 92.5%.

2024-09-25 | GSE277670 | GEO

MethylPurify: tumor purity deconvolution and differential methylation detection from tumor DNA methylomes

Project description:We propose a statistical algorithm MethylPurify that uses regions with bisulfite reads showing discordant methylation levels to infer tumor purity from tumor samples alone. With purity estimate, MethylPurify can identify differentially methylated regions (DMRs) from individual tumor samples without genomic variation information or prior knowledge from other datasets. In simulations with mixed bisulfite reads from cancer and normal cell lines, MethylPurify correctly inferred tumor purity and identified over 96% of the DMRs. On real patient data where tumor to normal comparison were used as golden standard, MethylPurify called DMR from tumor samples alone at over 57% sensitivity and 91% specificity. Lung adenocarcinoma cancer and normal tissues from 5 patients were captured by Agilent SureSelect Methyl-Seq system, followed by bisulfite sequencing.

2014-07-08 | E-GEOD-56712 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data