ChIP-Seq

ChIP-Cor Analysis Module

Feature Correlation Tool

ChIP-Seq Input Data (Reference Feature)
Select available Data Sets
      Genome :   
      Data Type :   
      Series   :
      Sample :   

Server-resident SGA Files by Filename

Upload custom Data
     
      from a FILE (gzip or zip formats are also accepted):
     
      or from a URL:
     
      Sort Input :        off     on      
      Experiment :
      Feature  :      
 Genomes

Additional Input Data Options
      Strand :    +    -    any    oriented
      Centering :      
 Repeat Masker      
ChIP-Seq Input Data (Target Feature)
Select available Data Sets
      Genome :   
      Data Type :   
      Series :   
      Sample :   

Server-resident SGA Files by Filename

Upload custom Data
     
      from a FILE (gzip or zip formats are also accepted):
     
      or from a URL:
     
      Sort Input :        off     on      
      Experiment :
      Feature  :      
 Genomes

Additional Input Data Options
      Strand :    +    -    any
      Centering :      
 Repeat Masker      
Analysis Parameters
Range
      Beginning :       End :
Histogram Parameters
Window Width :
Count Cut-off :
      Normalization :
      raw       count density       global      

Background: this tool reads ChIP-Seq tag positions and generates a positional correlation histogram for two genomic features. Input features maybe ChIP-Seq tag positions, peaks found by Chip_Peak, or any type of genome annotation data that can be mapped to a single base on the genome. The input of ChIP-Cor is a set of tag positions mapped to a reference genome produced by a ChIP-Seq experiment. We use as a working format a simplified GFF format, called SGA (Simplified Genome Annotation), which is sorted by sequence name and position. In addition to SGA, ChIP-Cor supports other input data formats such as BED, GFF, BAM, and FPS. Compressed input data in gzip or zip format is also accepted.
The output is a tag correlation histogram showing the abundance of the 'target' feature as a function of the distance from the 'reference' feature. At output, we also provide a 'feature extraction' option that includes DNA sequence extraction for selecting ChIP-enriched regions of interest.
Last update 7 Mar. 2012