How to Extract Differential Peaks from ATAC-seq Data Using DiffBind?
To extract differential peaks from ATAC-seq data using the DiffBind package, follow these steps:
Prepare Input Data
First, prepare the ATAC-seq data, typically in the form of peak files generated by peak calling software like MACS2. For multiple samples, prepare a peak file for each sample.
Create Sample Sheet
In DiffBind, create a sample sheet (usually in CSV or Excel format) that includes sample information, such as sample names, corresponding peak file paths, conditions (e.g., treatment and control groups), etc.
Read Data
Use DiffBind's dba() function to read the sample sheet. This step will integrate peak data from different samples into a DBA object.
“dbaObj <- dba(sampleSheet = "path/to/your/sampleSheet.csv")”
Align and Merge Peaks
Use the dba.count() function to align and merge peaks. This step counts the coverage of each peak across each sample.
“dbaObj <- dba.count(dbaObj)”
Differential Analysis
Use the dba.analyze() function to perform differential analysis. This step identifies peaks that change significantly under different conditions.
“dbaObj <- dba.analyze(dbaObj)”
Extract Results
Use the dba.report() function to extract specific information about differential peaks. This can be exported into a table, including peak locations and coverage differences across conditions.
“diffPeaks <- dba.report(dbaObj)”
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