ForwardStrand_excREL - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00010000674 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:ELSA genome-wide genotypes, including estimated related individuals. There are 3 files: .fam, .bim, .bed
| EGAD00010000676 | EGA
Project description:This file fileset has 4607 Greenlanders scored on the Illumina MEGA array (1,622,813 sites), and has been put on the plus strand. The data is in PLINK bed/bim/fam format. The Greenlandic individuals originate from two population surveys, B99 and IHIT.
| EGAD00010002057 | EGA
Project description:Purpose: A method for mapping chromatin accessibility genome-wide, to reveal chromatin accessibility in Intestinal stem cells. Methods: Intestinal stem cells(Lgr5-high cells) were sorted by flow cytometry from wild type mice. The samples were prepared in duplicate. HISAT2 was used to align the sequences to the mouse genome and generate bam files. bamCoverage was used to generate bigwig files from bam files. MACS2 (v2.2.5) was used for peak calling and to generate bed files from aligned reads. Conclusions: ATAC-seq analysis confirmed that Fosb binding sites in Chip-seq assay were correlated with the chromatin accessibility .
2023-04-13 | GSE186916 | GEO
Project description:Genotyping of 244 early RA patients and 44 vaccine recipient controls was performed using the Illumina InfiniumCoreExome-24-v1-1 according to the manufacturer’s SOP. Raw idats from the Illumina iScan instrument were imported into GenomeStudio (v2011.1). Samples < 90 % call rate were excluded. Data was exported to PLINK PED/MAP format on the forward strand. Data was converted from PED/MAP to BED/BIM/FAM using PLINK v1.07.
| EGAD00001006736 | EGA
Project description:Background - The coronavirus disease 2019 (COVID-19) is rapidly spreading in China and more than 30 countries over last two months. COVID-19 has multiple characteristics distinct from other infectious diseases, including high infectivity during incubation, time delay between real dynamics and daily observed number of confirmed cases, and the intervention effects of implemented quarantine and control measures. Methods - We develop a Susceptible, Un-quanrantined infected, Quarantined infected, Confirmed infected (SUQC) model to characterize the dynamics of COVID-19 and explicitly parameterize the intervention effects of control measures, which is more suitable for analysis than other existing epidemic models. Results - The SUQC model is applied to the daily released data of the confirmed infections to analyze the outbreak of COVID-19 in Wuhan, Hubei (excluding Wuhan), China (excluding Hubei) and four first-tier cities of China. We found that, before January 30, 2020, all these regions except Beijing had a reproductive number R &gt; 1, and after January 30, all regions had a reproductive number R lesser than 1, indicating that the quarantine and control measures are effective in preventing the spread of COVID-19. The confirmation rate of Wuhan estimated by our model is 0.0643, substantially lower than that of Hubei excluding Wuhan (0.1914), and that of China excluding Hubei (0.2189), but it jumps to 0.3229 after February 12 when clinical evidence was adopted in new diagnosis guidelines. The number of unquarantined infected cases in Wuhan on February 12, 2020 is estimated to be 3,509 and declines to 334 on February 21, 2020. After fitting the model with data as of February 21, 2020, we predict that the end time of COVID-19 in Wuhan and Hubei is around late March, around mid March for China excluding Hubei, and before early March 2020 for the four tier-one cities. A total of 80,511 individuals are estimated to be infected in China, among which 49,510 are from Wuhan, 17,679 from Hubei (excluding Wuhan), and the rest 13,322 from other regions of China (excluding Hubei). Note that the estimates are from a deterministic ODE model and should be interpreted with some uncertainty. Conclusions - We suggest that rigorous quarantine and control measures should be kept before early March in Beijing, Shanghai, Guangzhou and Shenzhen, and before late March in Hubei. The model can also be useful to predict the trend of epidemic and provide quantitative guide for other countries at high risk of outbreak, such as South Korea, Japan, Italy and Iran.
2024-09-02 | BIOMD0000000962 | BioModels
Project description:More researches have revealed that N4-acetylcytidine (ac4C) affected a variety of cellular and biological processes. In order to better understand the ac4C roles in biology and disease, we present an antibody-free, fluorine assisted metabolic sequencing method to detect RNA N4-acetylcytidine, called ‘FAM-seq’. We have successfully applied FAM-seq to profile ac4C landscapes in humans. By comparing with the classic ac4C antibody sequencing method, we demonstrated that FAM-seq is a convenient and specific method for transcriptome-wide detection of ac4C. This method holds promise to detect nascent RNA ac4C modifications.
2023-10-02 | GSE234988 | GEO
Project description:We have characterized allele-specific regulation of replication in human cultured primary basophilic erythroblasts using TimEX-seq. We show that in most of the genome the timing of replication of the two chromosome homologs is robustly and tightly regulated since the two alleles replicate almost at the same time. We also show that small genetic differences such as SNPs and indels do not affect replication timing. We identify two major causes of replication asynchrony: the presence of large structural variants and parental imprinting. Both are associated with the formation of asynchronously replicated domains that can reach several megabases in size. We also report that replication timing domains have a previously undetected fine structure. Compare DNA content in cells in S and G1 phase of cell cycle using TimEX-seq The goal of these experiments was to measure the timing of replication in human basophilic erythroblasts in an allele-specific manner by comparing DNA content in cells in S and G1 phase of cell cycle using TimEX-seq. Cells in S phase were obtained by sorting propidium iodide stained exponentially growing basophilic erythroblasts produce after 14 days of culture of circulating peripheral blood stem and progenitor cells. The cells in G1, which are used to normalize the results from the cells in S phase for mapability, were circulating mononuclear cells (WBCs) which are in the G1 cell for the cell cycle at 99.5%. The processed files represent S/G1 ratio values which are surrogate values for the timing of replication. Allele-specific TimEX-seq profiles and hi-resolution non-allele specific profiles are provided at different smoothing levels. The following processed files are derived from the multiple files as indicated below; >FNY01_3_2_Ery_MAT_S.bed is generated from FNY01_3_2_Ery_round *_S_Phase.bed >FNY01_3_2_Ery_PAT_S.bed is generated from FNY01_3_2_Ery_round *_S_Phase.bed >FNY01_3_2_Ery_MAT_G1.bed is generated from FNY01_3_2_WBC_round *_G1_600.bed FNY01_3_2_WBC_round *_G1_300.bed >FNY01_3_2_WBC_PAT_G1.bed is generated from FNY01_3_2_WBC_round *_G1_600.bed FNY01_3_2_WBC_round *_G1_300.bed >FNY01_3_2_Ery_S_G1 ratio_MAT_100kb_smooth.bedGraph is from FNY01_3_2_Ery_MAT_S.bed FNY01_3_2_Ery_MAT_G1.bed >FNY01_3_2_Ery_S_G1 ratio_PAT_100kb_smooth.bedGraph is from FNY01_3_2_Ery_PAT_S.bed FNY01_3_2_Ery_PAT_G1.bed >FNY01_3_2_Ery_S_G1 ratio_unsmooth.bedGraph, FNY01_3_2_Ery_S_G1 ratio_20Kb_smooth.bedGraph, and FNY01_3_2_Ery_S_G1 ratio_100Kb_smooth.bedGraph are from FNY01_3_2_Ery_round *_S_Phase.bed FNY01_3_2_WBC_round *_G1_600.bed FNY01_3_2_WBC_round *_G1_300.bed >FNY01_3_2&3_3_Ery* files are generated from 14 .bed files linked to the corresponding sample records. Please note that *3_3* files follow the same pattern as *3_2*
2014-05-01 | E-GEOD-50977 | biostudies-arrayexpress
Project description:Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. Regulation of transcript and protein abundances can affect the final phenotypes and has been related to many human diseases. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level (r = 0.165). While the protein co-expression network recapitulates the major biological functions, differential expression patterns reveal proteomic signatures related to specific populations, mainly domesticated. Most importantly, comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3.6%), with mostly common local QTL. Our results demonstrate that transcriptome and proteome are clearly two distinct layers of regulation, governed by distinct genetic bases in natural populations, and therefore highlight the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship. This submission contains the raw files for the wild isolates collection, the library used for the analysis and the corresponding DIA-NN report and associated files.
2024-04-30 | PXD044523 | Pride
Project description:This Series reports data from a CTCF ChIP-Seq experiment performed in F1-hybrid mouse trophoblast stem cells (TSCs). The data are part of a larger study examining inactive X gene expression and chromatin states, reported as GEO Series GSE39406. Included for this dataset are FASTQ files, BED alignments and WIG files with coordinates relative to UCSC genome build mm9, and _snp files that report the location of all SNP-overlapping reads
2012-09-08 | GSE40667 | GEO
Project description:Purpose: A method for identifying genome-wide DNA binding sites for Fosb. Methods: Alive cells were sorted from retro-Fosb-OE(over-expression) organoids. The samples were incubated with anti-Fosb antibody (Abcam, ab184938). Purified DNA was subjected to Tru-seq library construction using NEBNext Ultra II DNA Library Prep Kit and sequenced as paired-end with Illumina Novaseq 6000. HISAT2 was used to align the sequences to the mouse genome and generate bam files. bamCoverage (CPM normalized and extended reads) was used to generate bigwig files from bam files. MACS2 was used for peak calling and to generate bed files from aligned reads. HOMER annotatePeaks.pl was used to annotate the peaks. Conclusions: Target genes of Fosb through ChIP assay were consistent with predicted target genes. Thus, we concluded that Fosb, which is a key TF could regulate most of ISC signature genes to maintain Lgr5+ ISCs.
2023-04-13 | GSE186915 | GEO