Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1261935 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR33531217_1.fastq.gz | Fastqsanger.gz | |||
| SRR33531217_2.fastq.gz | Fastqsanger.gz | |||
| SRR33531218_1.fastq.gz | Fastqsanger.gz | |||
| SRR33531218_2.fastq.gz | Fastqsanger.gz | |||
| SRR33531219_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 8 |
Similar Datasets
Project description:Morus alba L. Raw protein sequence reads and sequence
2024-02-08 | PXD049451 |
Project description:Purpose: The goal of this study is to compare endothelial small RNA transcriptome to identify the target of OASL under basal or stimulated conditions by utilizing miRNA-seq. Methods: Endothelial miRNA profilies of siCTL or siOASL transfected HUVECs were generated by illumina sequencing method, in duplicate. After sequencing, the raw sequence reads are filtered based on quality. The adapter sequences are also trimmed off the raw sequence reads. rRNA removed reads are sequentially aligned to reference genome (GRCh38) and miRNA prediction is performed by miRDeep2. Results: We identified known miRNA in species (miRDeep2) in the HUVECs transfected with siCTL or siOASL. The expression profile of mature miRNA is used to analyze differentially expressed miRNA(DE miRNA). Conclusions: Our study represents the first analysis of endothelial miRNA profiles affected by OASL knockdown with biologic replicates.
2022-09-06 | GSE186354 | GEO
Project description:A cDNA library was constructed by Novogene (CA, USA) using a Small RNA Sample Pre Kit, and Illumina sequencing was conducted according to company workflow, using 20 million reads. Raw data were filtered for quality as determined by reads with a quality score > 5, reads containing N < 10%, no 5' primer contaminants, and reads with a 3' primer and insert tag. The 3' primer sequence was trimmed and reads with a poly A/T/G/C were removed
2021-07-21 | GSE180131 | GEO
Project description:Whole exome sequencing of 5 HCLc tumor-germline pairs. Genomic DNA from HCLc tumor cells and T-cells for germline was used. Whole exome enrichment was performed with either Agilent SureSelect (50Mb, samples S3G/T, S5G/T, S9G/T) or Roche Nimblegen (44.1Mb, samples S4G/T and S6G/T). The resulting exome libraries were sequenced on the Illumina HiSeq platform with paired-end 100bp reads to an average depth of 120-134x. Bam files were generated using NovoalignMPI (v3.0) to align the raw fastq files to the reference genome sequence (hg19) and picard tools (v1.34) to flag duplicate reads (optical or pcr), unmapped reads, reads mapping to more than one location, and reads failing vendor QC.
2016-02-01 | E-MTAB-4313 | biostudies-arrayexpress
Project description:The GSE119906 raw data have been removed due to retraction of the associated publication and at the request of the submitter.
2019-08-01 | GSE119906 | GEO
Project description:This submission includes the sample data for a protocol covering differential expression analysis with TopHat and Cufflinks. The protocol also covers several accessory tools and utilities that aid in managing data, including CummeRbund, a tool for visualizing RNA-Seq analysis results. While the procedure assumes basic informatics skills, these tools assume little to no background with RNA-Seq analysis and are meant for novices and experts alike. The protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results.
2011-09-10 | GSE32038 | GEO
Project description:Here, A549 cells expressing the ACE2 receptor were infected with SARS-CoV2, and pCHi-C was performed at 0 (mock), 8 and 24 hours post-infection. This repository provides the raw pCHi-C sequence reads and downstream processed CHiCAGO data (Rds files).
2021-05-10 | GSE164533 | GEO
Project description:HDMYZ cells were treated with 2ug/ml ActD for 0, 4 and 12 hours. Small RNAs of 15-40 bases were gel-purified from 10 ug total RNA, and subjected to multiplex Illumina small RNA library preparation. Small RNA libraries were sequenced on a HiSeq2000 (Illumina) with 3 samples per lane. To quantify miRNA and isoform abundance, sequence reads were processed by the miRDeep2 package, with the following modifications. First, to remove adaptor sequence, we removed both the main adaptor sequence present in the sequencing reads, as well as the second most abundant adaptor variant. In addition, we did not restrict the size of small RNAs during adaptor removal. Second, we used miRBase v18 for mapping the reads. Third, for quantifying miRNA and isoform frequency, we limited reads to more or equal to 15 bases in length with zero mis-match during mapping. The number of reads that were mapped to known miRNAs was used to normalize read frequencies for each miRNA or each miRNA isoform. For quantification purposes, we only considered miRNAs or isoforms that had frequency >= 1x10e-6 in samples without ActD treatment, which correspond to ~21-30 reads in raw count. These miRNAs or isoforms were referred to as reliably quantifiable.To analyze mapping to the genome, we removed reads that mapped to miRNA precursors. The rest of the reads were then mapped to the genome with Bowtie.
2017-09-02 | GSE46968 | GEO
Project description:We use nucleosome maps obtained by high-throughput sequencing to study sequence specificity of intrinsic histone-DNA interactions. In contrast with previous approaches, we employ an analogy between a classical one-dimensional fluid of finite-size particles in an arbitrary external potential and arrays of DNA-bound histone octamers. We derive an analytical solution to infer free energies of nucleosome formation directly from nucleosome occupancies measured in high-throughput experiments. The sequence-specific part of free energies is then captured by fitting them to a sum of energies assigned to individual nucleotide motifs. We have developed hierarchical models of increasing complexity and spatial resolution, establishing that nucleosome occupancies can be explained by systematic differences in mono- and dinucleotide content between nucleosomal and linker DNA sequences, with periodic dinucleotide distributions and longer sequence motifs playing a secondary role. Furthermore, similar sequence signatures are exhibited by control experiments in which genomic DNA is either sonicated or digested with micrococcal nuclease in the absence of nucleosomes, making it possible that current predictions based on highthroughput nucleosome positioning maps are biased by experimental artifacts. Included are raw (eland) and mapped (wig) reads. The mapped reads are provided in eland and wiggle formats, and the raw reads are included in the eland file. This series includes only Mnase control data. The sonicated control is part of this already published accession, as is a in vitro nucleosome map: http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE15188 We also studied data (in vitro and in vivo maps as well as a model) from http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13622 and from: http://www.ncbi.nlm.nih.gov/sra/?term=SRA001023
2010-08-20 | E-GEOD-23712 | biostudies-arrayexpress
Project description:This project carries out the pilot CRISPR/Cas9 screens in the K562 background. Its goals are to confirm that positive controls work, and to assess the effects of experimental parameters (listed below) on the sequencing-based fitness readout. We test 1) length of selection 2) biological replicates 3) sampling variation during bottlenecks 4) sampling variation during DNA preparation 5) sequencing depth to inform the setup for the next round of experiments. To do so, we propose to sequence 13 samples (6 timepoints, 2 biological replicates, 2 severe bottlenecks during growth, 2 bottlenecks during DNA preparation, and the screening library itself) on two lanes of HiSeq, using 19bp reads. The sequencing libraries are prepared in our lab.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
2016-05-03 | E-ERAD-459 | biostudies-arrayexpress