Renormalization of GSE32442 and GSE33128
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE35878 | GEO | 2012/02/21
SECONDARY ACCESSION(S): PRJNA155711
REPOSITORIES: GEO
Similar Datasets
Project description:Raw data from GSE32442 and GSE33128 and the input dataset for GSE32442 were renormalized by using reads per million. 11 samples from GSE32442 and GSE33128
2012-02-21 | E-GEOD-35878 | biostudies-arrayexpress
Project description:Raw data from E-MTAB-1585 was normalized by using reads per million. https://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1585/
2013-09-19 | GSE50860 | GEO
Project description:Purpose: To ensure that ABX464 acted specifically on HIV splicing and did not significantly or globally affect the splicing events of human genes, we used a high-throughput RNAseq approach. Many genome-wide expression studies of HIV infection are based on analyses of total peripheral blood mononuclear cells (PBMCs), which consist of over a dozen cell subsets, including T cells, B cells, NK cells and monocytes Methods: The CD4 T cells were uninfected or infected with the YU2 strain and were untreated or treated for 6 days with ABX464, followed by high-throughput RNAseq. Each raw dataset of the samples contained between 44 and 105 million single-end reads (50 bp), with an average of approximately 60 million raw reads per sample Results: Approximately 98% of the total raw reads were mapped to the human genome sequence (GRCh38), giving an average of 60 million human reads per sample for further analyses. The reads that were correctly mapped (approximately 98% of total input reads) to the gene and transcript locations (GTF annotation file) Conclusions: The MDS of our gene expression data showed, without any outliers, that the different donors segregated well and distributed into the DMSO (untreated) and ABX464 treatments that were infected or uninfected. The displayed variance was donor-dependent (clustered by donor) but treatment-independent (no data structure related to the different treatments), which suggests that the ABX464 molecule did not induce a major difference in CD4 T cell gene expression.
2018-06-22 | GSE116073 | GEO
Project description:Purpose: To ensure that ABX464 acted specifically on HIV splicing and did not significantly or globally affect the splicing events of human genes, we used an assembly approach of HIV (YU2 strain) putative transcripts and human long non-coding sequences from paired-reads (2x75bp) captured on a NimbleGen SeqCap® EZ Developer Library (Roche/NimbleGen). Methods: Cells were infected with 80 ng of p24/106 cells of the YU-2 strain for 4 to 6 hours and then rinsed with PBS before medium renewal, followed by high-throughput RNAseq from custom SeqCap EZ capture libraries. Each raw dataset of the samples contained between 5 and 30 million paired-end reads (75 bp), with an average of approximately 12 million raw reads per sample. Results: The raw reads were then cleaned and assembled per library to generate contigs, giving an average of 930 contigs per sample for further analyses. Conclusions: Our results show that high-throughput analyses coupled with bioinformatics-specific tools offers a comprehensive and more accurate view of mRNA splicing within a cell.
2018-12-31 | GSE120109 | GEO
Project description:We report the application of single-molecule-based sequencing technology for high-throughput profiling of histone modifications in endpoint tumours from Ezh2+/+ or Ezh2-/- Tet ON PyVmT mammary gland tumours. In order to understand the H3K27me3 targets in the context of mouse mamamry gland tumorigenesis, data were generated by deep sequencing a pool of 5 tumours per genoype, in duplicate using Illumina HiSeq2500. Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm10). Raw reads were trimmed for length (n>=32), quality (phred score >= 30) and adaptor sequence using fastx v0.0.13.1.Trimmed reads were (pools of 5 different tumors per genotype) then aligned to the mouse reference genome mm10 using BWA v0.5.9 Broad peaks were called using MACS v1.4.1 software (mfold=10,30; bandwith=300; pvalue cutoff=1E-5) using sequenced libraries of input DNA as control. Peak list intersections were done using BEDTools v2.12.0. Binding peaks were considered overlapping if at least 1 base of the peaks overlapped. Our study demonstrated the first mapping of H3K27me3 in the endpint tumours of tetracycline ducible PyVmT mouse mamary tumours.
2018-03-01 | GSE108899 | GEO
Project description:Purpose: This study aimed to generate a whole transcriptome dataset for children with acute myeloid leukemia Methods: RNA-seq data were generated by deep sequencing using Illumina. The sequence reads that passed quality filters were analyzed. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the human genome (buildhg38) and annotated with ensemble release 100.
2022-08-16 | GSE192638 | GEO
Project description:A 122-epigenetic gene signature distinguished low- versus high-risk early stage melanomas. We sought to validate the signature, examined clinical correlates in a cohort of primary melanomas of the skin, and studied the underlying transcriptomic aberrations and changes in chromatin in cell lines representing these two groups. H3K27Ac ChipSeq profiles of primary human melanoma cell lines (n=4) as well as corresponding input samples were generated by deep sequencing using Illumina NextSeq500. Purpose: The goals of this study are to identify H3K27Ac differential peak expression between two groups of melanoma cell lines (Epgn1 and Epgn3) and relate this data to RNASeq. Methods: H3K27Ac ChipSeq was performed on 4 melanoma cell lines by deep sequencing 75bp single end reads using Illumina NextSeq500. Reads were aligned and counts called using____. The sequence reads that passed quality filters were analyzed. Results: Using an optimized data analysis workflow, we mapped about 40 million reads per Chip sample and 60 million reads per input sample to the human genome (build _____). Conclusions: Our study allowed us to identify differentially expressed peaks between two classes of melanoma cell lines and relate this information to differential gene expression. Further in vitro and in vivo assays using some of the candidate genes identified will allow us to more fully understand primary melanoma progression.
2024-05-08 | GSE197235 | GEO
Project description:Transcriptome profiling (RNA-Seq) to evaluate the connection the metabolic enzyme UGDH on gene expression. The RNA libraries were prepared and sequenced at University of Houston Seq-N-Edit Core per protocols. Total libraries were prepared with Ovation® Universal Plus mRNA-Seq (NuGen) using 200 ng input RNA. The size selection for libraries were performed using SPRIselect beads (Beckman Coulter) and purity of the libraries were analyzed using the High Sensitivity DNA chip on Bioanalyzer 2100 (Agilent). The prepared libraries pooled and sequenced using NextSeq 500 (Illumina), generating ~15 million 2×76 bp paired-end reads per samples. The RNA-seq raw fastq data were processed with RNA-Seq Express app within the Illumina BaseSpace app suite (www.basespace.illumina.com), which performed alignment with STAR aligner, assignment of aligned reads to genes, and differential gene expression with DESeq2 Analysis was performed comparing controls (shNT) against individual knockdowns (shU1 or shU2). Then, results from both analyses were compared for the intersection to identify commonly altered genes.
2018-08-21 | GSE118772 | GEO
Project description:Purpose: RNA-seq analysis to evaluate the impact of MED23 knockdown on the transcriptome of HUVEC cells.Methods: Total RNA was isolated with TRIzol from Med23 knockdown HUVECs (n = 3) or control cells (n = 3). cDNA sequencing libraries were prepared with an NEBNext® Ultra™ RNA Library Prep Kit for Illumina. The RNA-Seq FASTQ raw data were trimmed to remove low-quality reads and adapters using Trimmomatic. The trimmed reads were aligned to the mouse reference genome UCSC GRCh37/hg19 with HISAT2. Gene and transcript quantification was performed using Cutdiff. The results of the mapping of the RNA-seq reads, transcript assembly and abundance estimation were reported as fragments per kilobase of exon per million fragments mapped (FPKM).
2021-10-21 | GSE186112 | GEO
Project description:SAGA member Ada2 is required for the majority of H3K9 acetylation in C. neoformans. To identify specific genomic loci that exhibit Ada2-dependent H3K9 acetylation, we performed ChIP-Seq against H3K9ac in wildtype and ada2Δ cells. ChIP-Seq was performed using antibodies for H3K9ac in KN99 wildtype cells and ada2Δ cells. Input and IPed DNA was collected in triplicate from each strain and sequenced on an Illumnina HiSeq 2000 flow cell producing 84 million reads. Due to the lack of quality scores, raw reads are omitted from the submission.
2012-01-01 | E-GEOD-32075 | biostudies-arrayexpress