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A manually curated ChIP-seq benchmark demonstrates room for improvement in current peak-finder programs.

Rye MB, Sætrom P, Drabløs F - Nucleic Acids Res. (2010)

Bottom Line: Second, none of the programs returned peak-regions that corresponded to the actual resolution in ChIP-seq data.Our results showed that ChIP-seq peaks should be narrowed down to 100-400 bp, which is sufficient to identify unique peaks and binding sites.Based on these results, we propose a meta-approach that gives improved peak definitions.

View Article: PubMed Central - PubMed

Affiliation: Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NO-7489 Trondheim, Norway. morten.rye@ntnu.no

ABSTRACT
Chromatin immunoprecipitation (ChIP) followed by high throughput sequencing (ChIP-seq) is rapidly becoming the method of choice for discovering cell-specific transcription factor binding locations genome wide. By aligning sequenced tags to the genome, binding locations appear as peaks in the tag profile. Several programs have been designed to identify such peaks, but program evaluation has been difficult due to the lack of benchmark data sets. We have created benchmark data sets for three transcription factors by manually evaluating a selection of potential binding regions that cover typical variation in peak size and appearance. Performance of five programs on this benchmark showed, first, that external control or background data was essential to limit the number of false positive peaks from the programs. However, >80% of these peaks could be manually filtered out by visual inspection alone, without using additional background data, showing that peak shape information is not fully exploited in the evaluated programs. Second, none of the programs returned peak-regions that corresponded to the actual resolution in ChIP-seq data. Our results showed that ChIP-seq peaks should be narrowed down to 100-400 bp, which is sufficient to identify unique peaks and binding sites. Based on these results, we propose a meta-approach that gives improved peak definitions.

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Peak regions representing (A) a positive peak, (B) an ambiguous peak, (C) a negative region showing evenly distributed tags without a peak-profile and (D) a negative region with peaks lacking the characteristic shift-property on opposite strands.
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Figure 1: Peak regions representing (A) a positive peak, (B) an ambiguous peak, (C) a negative region showing evenly distributed tags without a peak-profile and (D) a negative region with peaks lacking the characteristic shift-property on opposite strands.

Mentions: Although transcription factors bind short DNA sequences, the immunoprecipitated DNA fragments are fairly large and typically cover a region of 150–600 bp around the binding site (10). As the double-stranded fragments are sequenced from either 5′-end at random, binding sites will typically appear as shifted peaks in the tag profiles on the positive and negative DNA strands (Figure 1A). Despite that such shifted peaks are characteristic of true binding sites, finding the true peaks in the tag profiles is not trivial and at least three issues must be considered when planning ChIP-seq experiments and evaluating potential binding locations.Figure 1.


A manually curated ChIP-seq benchmark demonstrates room for improvement in current peak-finder programs.

Rye MB, Sætrom P, Drabløs F - Nucleic Acids Res. (2010)

Peak regions representing (A) a positive peak, (B) an ambiguous peak, (C) a negative region showing evenly distributed tags without a peak-profile and (D) a negative region with peaks lacking the characteristic shift-property on opposite strands.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3045577&req=5

Figure 1: Peak regions representing (A) a positive peak, (B) an ambiguous peak, (C) a negative region showing evenly distributed tags without a peak-profile and (D) a negative region with peaks lacking the characteristic shift-property on opposite strands.
Mentions: Although transcription factors bind short DNA sequences, the immunoprecipitated DNA fragments are fairly large and typically cover a region of 150–600 bp around the binding site (10). As the double-stranded fragments are sequenced from either 5′-end at random, binding sites will typically appear as shifted peaks in the tag profiles on the positive and negative DNA strands (Figure 1A). Despite that such shifted peaks are characteristic of true binding sites, finding the true peaks in the tag profiles is not trivial and at least three issues must be considered when planning ChIP-seq experiments and evaluating potential binding locations.Figure 1.

Bottom Line: Second, none of the programs returned peak-regions that corresponded to the actual resolution in ChIP-seq data.Our results showed that ChIP-seq peaks should be narrowed down to 100-400 bp, which is sufficient to identify unique peaks and binding sites.Based on these results, we propose a meta-approach that gives improved peak definitions.

View Article: PubMed Central - PubMed

Affiliation: Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, NO-7489 Trondheim, Norway. morten.rye@ntnu.no

ABSTRACT
Chromatin immunoprecipitation (ChIP) followed by high throughput sequencing (ChIP-seq) is rapidly becoming the method of choice for discovering cell-specific transcription factor binding locations genome wide. By aligning sequenced tags to the genome, binding locations appear as peaks in the tag profile. Several programs have been designed to identify such peaks, but program evaluation has been difficult due to the lack of benchmark data sets. We have created benchmark data sets for three transcription factors by manually evaluating a selection of potential binding regions that cover typical variation in peak size and appearance. Performance of five programs on this benchmark showed, first, that external control or background data was essential to limit the number of false positive peaks from the programs. However, >80% of these peaks could be manually filtered out by visual inspection alone, without using additional background data, showing that peak shape information is not fully exploited in the evaluated programs. Second, none of the programs returned peak-regions that corresponded to the actual resolution in ChIP-seq data. Our results showed that ChIP-seq peaks should be narrowed down to 100-400 bp, which is sufficient to identify unique peaks and binding sites. Based on these results, we propose a meta-approach that gives improved peak definitions.

Show MeSH
Related in: MedlinePlus