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Status |
Public on Nov 05, 2018 |
Title |
AK142 [tumor RNA-seq] |
Sample type |
SRA |
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Source name |
adult glioblastoma tumour
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Organism |
Homo sapiens |
Characteristics |
subtype: RTK_I gender: female age: 49 survival_status: alive os (overall survival, month): 3 progression: 0 pfs (progression-free survival, month): 3 chr7_gain: 1 chr10_loss: 1 chr10q_loss: 0 chr19_gain: 0 chr20_gain: 0 idh1 mutation status: wt idh2 mutation status: wt egfr_amplification: 1 pten_deletion: 0 mdm2_amplification: 1 mdm4_amplification: 0 pdgfra_amplification: 0 cdkn2a_b_deletion: 0 cdk4_amplification: 1
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Extracted molecule |
total RNA |
Extraction protocol |
Nucleic acids were extracted from tumour tissue using Qiagen Allprep DNA/RNA/Protein Mini kit or a standard caesium chloride (CsCl) density gradient ultracentrifugation protocol. QC was performed using the Agilent Bioanalyser 2100 and the Nanodrop spectrophotometer. RNA-seq libraries were prepared as described using methods to preserve strand specificity and deplete rRNA (see Hovestadt et al., Nature (2014) 510:537-541 https://doi.org/10.1038/nature13268). Briefly, the TruSeq stranded total RNA kit was used to prepare libraries according to the manufacturer's protocol. Sequencing was carried out on the HiSeq 2000 platform with 1 lane per sample.
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Library strategy |
RNA-Seq |
Library source |
transcriptomic |
Library selection |
cDNA |
Instrument model |
Illumina HiSeq 2000 |
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Description |
processed data file RTK_I_average_RNAseq_coverage.bigWig RNAseq_expression_matrix_counts.txt.gz RNAseq_expression_matrix_TPMs.txt.gz RNAseq_subtype_signature_gene_analysis_limma_model_results.txt
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Data processing |
Reads were aligned to the human genome (hg19 build) with the Gencode reference transcriptome (v19) using STAR (v2.3.0e). Read counts for each gene were quantified as the total number of reads mapping to exons using htseq-count (0.6.0). bigWig coverage files were generated using the deepTools2 suite. Subtype average files were generated by calculating the average across all samples in that subtype. Identification of genes differentially expressed between GB subtypes and NBr: Differential expression analysis was performed using DESeq2 (1.14.1). The FDR threshold for significant differential expression was set to 0.05. For the subtype gene signature analysis in limma, raw read counts per gene were pre-filtered, retaining those genes with >10 reads in >6 samples for further analysis. Normalisation factors for the counts were calculated using the calcNormFactors function in ‘edgeR’ (3.20.1). voomWithQualityWeights from ‘limma’ (3.34.4) was used to transform the raw counts. limma differential expression analysis was used to compare the gene expression of each GBM subtype versus the other 3 (example contrast: IDH / ((MES+RTK I+RTK II)/3) ). Genes were defined as significant for a subtype if they passed a BH adjusted p-value threshold of 0.001. Genome_build: hg19 Supplementary_files_format_and_content: bigWig coverage tracks for each sample, as well as subtype average bigWig coverage tracks. Additionally, expression matrices (tab-delimited text files) of TPMs and counts are supplied for the entire cohort. The samplesheets used in the RTN GRN analysis are also included, as well as the results of the limma subtype gene signature model.
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Submission date |
Oct 24, 2018 |
Last update date |
Nov 15, 2018 |
Contact name |
Bernhard Radlwimmer |
E-mail(s) |
b.radlwimmer@dkfz-heidelberg.de
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Organization name |
Deutsches Krebsforschungszentrum / German National Cancer Research Centre
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Department |
Department of Molecular Genetics
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Street address |
Im Neuenheimer Feld 280
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City |
Heidelberg |
ZIP/Postal code |
69120 |
Country |
Germany |
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Platform ID |
GPL11154 |
Series (2) |
GSE121720 |
Glioblastoma epigenome profiling identifies SOX10 as a master regulator of molecular tumour subtype - tumour rRNA-depleted total ssRNAseq data |
GSE121723 |
Glioblastoma epigenome profiling identifies SOX10 as a master regulator of molecular tumour subtype |
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Relations |
BioSample |
SAMN10285648 |