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Genome-wide maps of XBP1 binding sites in different breast cancer cell lines [ChIP-Seq]

GSE49952 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 11 samples Submitted 2013/09/26 Platform GPL11154
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 11 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
11 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
We report the application of ChIP-seq, which combines chromatin immunoprecipitation (ChIP) with massively parallel DNA sequencing, to map genome-wide XBP1 binding sites in different breast cancer cell lines. We showed that HIF1α motif was enriched in XBP1 binding sites in triple negative breast cancer (TNBC) cell lines, but not enriched in ER positive breast cancer cell line.
Read the full summary ↓
We also demonstrated that different breast cancer cell lines of the same sub-type had similar XBP1 binding sites, whereas different breast cancer sub-types had majorly different XBP1 binding sites. Finally, a model was applied to integrate XBP1 ChIP-seq data with expression data to predict XBP1's direct targets in TNBC cell line; the predicted direct targets were shown to be predictive of patient survival, and the prediction power was specific to TNBC patients. The above evidence indicates that XBP1 performs important functions in TNBC by interacting with HIF1α, and such regulation mechanism is specific to TNBC, which is later proved by follow-up experiments.This study represents the first detailed anaysis of XBP1 binding sites in different breast cancer cell lines.
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE49952_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA221365 and SRA study SRP033364. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 11 more — browse all 11 samples with per-sample file links →

Datasets on a similar topic

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