Peakzilla statistics

Tool stats & trends

Looking to identify usage trends or leading experts?

Peakzilla specifications

Information


Unique identifier OMICS_00454
Name Peakzilla
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data The coordinate files of the mapped reads of the IP and-optionally-control sample.
Input format BED
Output data The TFBSs including the genomic positions, raw, distribution and final score, FDR and a peak number according to each peak’s rank.
Output format BED
Operating system Unix/Linux, Mac OS
Programming languages Python
License GNU General Public License version 2.0
Computer skills Advanced
Stability Stable
Maintained Yes

Download


conda.png

Versioning


No version available

Documentation


Maintainers


  • person_outline Alexander Stark
  • person_outline Jonas Steinmann

Publication for Peakzilla

Peakzilla citations

 (7)
library_books

Modular discovery of monomeric and dimeric transcription factor binding motifs for large data sets

2018
Nucleic Acids Res
PMCID: 5934673
PMID: 29385521
DOI: 10.1093/nar/gky027

[…] ), HNF4A (Sequence Read Archive accession SRR952427, IgG: SRR952608) () and TFAP2A (SRR952485,IgG: SRR952608) (). To find the peaks, the reads were aligned with BWA (), and peak calling was done with Peakzilla (). The genome assembly used was GRCh37 (hs37d5). From each ChIP-seq peak set, top n = 230 peaks with highest quality score were selected, and for each peak a sequence of length L = 190 bp f […]

library_books

Data exploration, quality control and statistical analysis of ChIP exo/nexus experiments

2017
Nucleic Acids Res
PMCID: 5587812
PMID: 28911122
DOI: 10.1093/nar/gkx594

[…] This is an important point with implications on the statistical analysis of ChIP-exo data. Specifically, currently available ChIP-exo specific statistical analysis methods (e.g. MACE (), CexoR () and Peakzilla ()) rely on the existence of peak-pairs formed by forward and reverse strand reads at the binding site. Finally, most of current widely used ChIP-seq quality control (QC) guidelines (–) may […]

library_books

Landscape of histone modifications in a sponge reveals the origin of animal cis regulatory complexity

2017
eLife
PMCID: 5429095
PMID: 28395144
DOI: 10.7554/eLife.22194.055

[…] .1) that contain at least one narrow peak passing a P-value of 0.01. For the diffused histone PTMs – H3K36me3 and H3K27me3 – we used the broadPeak representation. RNAPII peaks were detected using the peakzilla software (RRID:SCR_007471) (), using input DNA reads as control (-c 1.5, –s 3). The fraction of reads falling within peak regions (FRiP) was also calculated (see ). In line with ENCODE guide […]

library_books

Genome wide identification of Drosophila dorso ventral enhancers by differential histone acetylation analysis

2016
Genome Biol
PMCID: 5037609
PMID: 27678375
DOI: 10.1186/s13059-016-1057-2

[…] All ChIP-seq enrichment values were calculated as fold change over the corresponding input sample, after normalizing for differences in read count and fragment size. CBP peaks were first called with peakzilla [] using default parameters for the CBP wild-type ChIP-seq and its corresponding input control. Detected peaks were resized to 201 bp centered at the summit, and those with less than twofold […]

library_books

Genome Wide Ultrabithorax Binding Analysis Reveals Highly Targeted Genomic Loci at Developmental Regulators and a Potential Connection to Polycomb Mediated Regulation

2016
PLoS One
PMCID: 5004984
PMID: 27575958
DOI: 10.1371/journal.pone.0161997

[…] rage of the two replicates, demonstrating the reproducibility of the approach. We merged both replicates and identified genomic regions that were significantly enriched for Ubx binding (‘peaks’) with peakzilla []. We obtained 5282 peaks (peakzilla score ≥3), of which 1479 peaks were particularly strong with a score ≥5. To control for antibody-specificity and to obtain an estimate of the respective […]

library_books

Recent advances in ChIP seq analysis: from quality management to whole genome annotation

2016
Brief Bioinform
PMCID: 5444249
PMID: 26979602
DOI: 10.1093/bib/bbw023

[…] er strategies, MACS [] uses the local Poisson model that estimates the parameter λ for each local genomic position. GPS [] and PICS [] predict protein-binding events using an EM algorithm. SISSRs [], Peakzilla [] and Q [] focus on the equivalence between the read numbers of positive and negative strands to improve peak resolution. PePr [] and JAMM [] integrate information from multiple replicates […]

Citations

Looking to check out a full list of citations?

Peakzilla institution(s)
Research Institute of Molecular Pathology (IMP), Vienna, Austria; Institute of Molecular Biotechnology (IMBA), Vienna, Austria; Stowers Institute for Medical Research, Kansas City, MO, USA
Peakzilla funding source(s)
Supported by Austrian Ministry for Science and Research through the Genome Research in Austria (GEN-AU) BioinformaticsIntegration Network III; Austrian Research Fund (FWF) (Z_153_B09); NIH New Innovator (1DP2 OD004561-01, a Pew scholar); European Research Council (ERC) Starting Grant from the European Community’s Seventh Framework Programme (FP7/ 2007-2013)/ERC (242922) and Boehringer Ingelheim.

Peakzilla reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review Peakzilla