Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Odontomachus chelifer

ABSTRACT: Odontomachus chelifer Raw sequence reads

PROVIDER: PRJNA895366 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR22084210_1.fastq.gz	Fastqsanger.gz
	SRR22084210_2.fastq.gz	Fastqsanger.gz
	SRR23674720_1.fastq.gz	Fastqsanger.gz
	SRR23674720_2.fastq.gz	Fastqsanger.gz

Items per page:

1 - 4 of 4

Similar Datasets

Odontomachus brunneus

Project description:Odontomachus brunneus overview

| PRJNA433039 | ENA

Odontomachus brunneus

Project description:Odontomachus brunneus RNAseq

| PRJNA432981 | ENA

Odontomachus brunneus

Project description:Odontomachus brunneus whole genome sequencing

| PRJNA432980 | ENA

Morus alba Raw protein sequence reads

Project description:Morus alba L. Raw protein sequence reads and sequence

2024-02-08 | PXD049451 |

Quantitative profiling of differentially expressed miRNAs in siCTL- and siOASL-transfected HUVECs

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

Sequencing of siRNA from soybean containing silencing vectors and empty vectors

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

Exome sequencing in classic Hairy cell leukaemia reveals widespread variation in acquired somatic mutations between individual tumours apart from the signature BRAF V(600)E lesion

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:Bacterial Communities Associated With Odontomachus chelifer and O. hastatus (Hymenoptera: Formicidae): Evaluating Species-Specific and Interhabitat Effects

| PRJNA701315 | ENA

High-throughput sequencing reveals a simple model of nucleosome energetics

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

Promoter Capture Hi-C performed on A549 cells in a SARS-CoV2 infection timecourse

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

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