POLK ChIP-seq data
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA911577 | ENA |
REPOSITORIES: ENA
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:modENCODE_White Lab: genome-wide ChIP-chip and ChIP-Seq data
| PRJNA131759 | ENA
Project description:Chip-seq data for HNSCC subtypes
| PRJNA769445 | ENA
Project description:ChIP-Seq Data of purified hepatocytes
| PRJNA1002232 | ENA
Project description:ChIP-seq and RNA-seq data for Glioma
| PRJNA705206 | ENA
Project description:BGISEQ-500 ChIP-Seq SE50 demo data
| PRJEB20179 | ENA
Project description:POLH ChIP-seq data in HEK293T cells
| PRJNA838014 | ENA
Project description:MotivationAlthough chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) or tiling array hybridization (ChIP-chip) is increasingly used to map genome-wide-binding sites of transcription factors (TFs), it still remains difficult to generate a quality ChIPx (i.e. ChIP-seq or ChIP-chip) dataset because of the tremendous amount of effort required to develop effective antibodies and efficient protocols. Moreover, most laboratories are unable to easily obtain ChIPx data for one or more TF(s) in more than a handful of biological contexts. Thus, standard ChIPx analyses primarily focus on analyzing data from one experiment, and the discoveries are restricted to a specific biological context.ResultsWe propose to enrich this existing data analysis paradigm by developing a novel approach, ChIP-PED, which superimposes ChIPx data on large amounts of publicly available human and mouse gene expression data containing a diverse collection of cell types, tissues and disease conditions to discover new biological contexts with potential TF regulatory activities. We demonstrate ChIP-PED using a number of examples, including a novel discovery that MYC, a human TF, plays an important functional role in pediatric Ewing sarcoma cell lines. These examples show that ChIP-PED increases the value of ChIPx data by allowing one to expand the scope of possible discoveries made from a ChIPx experiment.Availabilityhttp://www.biostat.jhsph.edu/~gewu/ChIPPED/
| S-EPMC3658457 | biostudies-literature