ATAC-seq/ChIP part
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001006520 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Estrogen Receptor alpha (ERα) is a key driver of most breast cancers, and it is the target of endocrine therapies used in the clinic to treat women with ERα positive (ER+) breast cancer. The two methods ChIP-seq (chromatin immunoprecipitation coupled with deep sequencing) and RIME (Rapid Immunoprecipitation of Endogenous Proteins) have greatly improved our understanding of ERα function during breast cancer progression and in response to anti-estrogens. A critical component of both ChIP-seq and RIME protocols is the antibody that is used to pull down the bait protein. To date, most of the ChIP-seq and RIME experiments for the study of ERα have been performed using the sc-543 antibody from Santa Cruz Biotechnology. However, this antibody has been discontinued, thereby severely impacting the study of ERα in normal physiology as well as diseases such as breast cancer and ovarian cancer. Here, we compare the sc-543 antibody with other commercially available antibodies, and we show that 06-935 (EMD Millipore) and ab3575 (Abcam) antibodies can successfully replace the sc-543 antibody for ChIP-seq and RIME experiments.
2019-03-21 | PXD012930 | Pride
Project description:ATAC-Seq and CTCF ChIP-Seq on the OCIAML-2 cell line
| EGAS00001004741 | EGA
Project description:Changes in cellular chromatin states fine-tune transcriptional output and ultimately lead to phenotypic changes. Here we propose a novel application of our reproducibility-optimized test statistics (ROTS) to detect differential chromatin states (ATAC-seq) or differential chromatin modification states (ChIP-seq) between conditions. We compare the performance of ROTS to existing and widely used methods for ATAC-seq and ChIP-seq data using both synthetic and real datasets. Our results show that ROTS outperformed other commonly used methods when analyzing ATAC-seq data. ROTS also displayed the most accurate detection of small differences when modeling with synthetic data. We observed that two-step methods that require the use of a separate peak caller often more accurately called enrichment borders, whereas one-step methods without a separate peak calling step were more versatile in calling sub-peaks. The top ranked differential regions detected by the methods had marked correlation with transcriptional differences of the closest genes. Overall, our study provides evidence that ROTS is a useful addition to the available differential peak detection methods to study chromatin and performs especially well when applied to study differential chromatin states in ATAC-seq data.
| S-EPMC8253552 | biostudies-literature
Project description:RNA-seq, ChIP-seq, and ATAC-seq analyses of mTECs
| PRJNA605193 | ENA
Project description:Detect-seq on transfected HEK293T cells [ATAC-seq data and in situ ChIP-seq data]
| PRJNA726718 | ENA
Project description:Activation of regulatory elements is thought to be inversely correlated with DNA methylation levels. However, it is difficult to determine whether DNA methylation is compatible with chromatin accessibility or transcription factor (TF) binding if assays are performed separately. We developed a fast, low-input, low sequencing depth method, EpiMethylTag, that combines ATAC-seq or ChIP-seq (M-ATAC or M-ChIP) with bisulfite conversion, to simultaneously examine accessibility/TF binding and methylation on the same DNA. Here we demonstrate that EpiMethylTag can be used to study the functional interplay between chromatin accessibility and TF binding (CTCF and KLF4) at methylated sites.
| S-EPMC6868874 | biostudies-literature
Project description:Chromatin immunoprecipitation sequencing (ChIP-seq) and the Assay for Transposase-Accessible Chromatin with high-throughput sequencing (ATAC-seq) have become essential technologies to effectively measure protein-DNA interactions and chromatin accessibility. However, there is a need for a scalable and reproducible pipeline that incorporates proper normalization between samples, correction of copy number variations, and integration of new downstream analysis tools. Here we present Containerized Bioinformatics workflow for Reproducible ChIP/ATAC-seq Analysis (CoBRA), a modularized computational workflow which quantifies ChIP-seq and ATAC-seq peak regions and performs unsupervised and supervised analyses. CoBRA provides a comprehensive state-of-the-art ChIP-seq and ATAC-seq analysis pipeline that can be used by scientists with limited computational experience. This enables researchers to gain rapid insight into protein-DNA interactions and chromatin accessibility through sample clustering, differential peak calling, motif enrichment, comparison of sites to a reference database, and pathway analysis. CoBRA is publicly available online at https://bitbucket.org/cfce/cobra.
| S-EPMC9039557 | biostudies-literature