Human p53 ChIP-seq depth and (SISSR) peaks datasets excluded from analysis

Description

This composite track contains the p53 ChIP-seq studies in IMR90 cells (that were generated by another lab), which were excluded from further assessment due to an abnormally low frequency of peaks with a p53 motif (3%) or low number of total peaks (only 17) (and identified as outliers in Nguyen et al. (2018)). The tracks represent peak calls and signals that were generated based on a uniform processing pipeline of the published raw data.

The colors for each classification are as follows:

coverage track depth

SISSRs peak calls

Methods

Please note: For a full description of the methods used, refer to Nguyen et al. (2018) in the References section below.

ChIP-seq analysis workflow

Relevant ChIP-seq and associated input data sets were downloaded from publicly-available resources as listed in Supplemental Table ST1. All reads were clipped to a maximum length of 36 nucleotides (nt), then filtered to retain only sequences with a mean base quality score of at least 20. Filtered reads were aligned against the hg19 reference genome (excluding haplotype chromosomes) via Bowtie v0.12.8 with parameters “-m1 -v2” to accept only uniquely-mapped hits with a maximum of 2 mismatched bases. Multiple replicates from the same sample were merged, then duplicate reads were removed with MergeSamFiles.jar and MarkDuplicates.jar from the Picard tool suite v1.86 (http://broadinstitute.github.io/picard). Depth tracks were generated with BEDTools genomeCoverageBed v2.17.0 and UCSC utility bedGraphToBigWig, after extending each uniquely-mapped, non-duplicate read to a length of 200 nt.

p53 peak calls

The SISSRs program was used to identify p53 bound peaks for each p53 ChIP-seq data set using its associated input data set (or a surrogate input) as a control at default parameters (p<0.001). The SISSRs output peaks were subsequently redefined as 200-mers centered on the called peak’s midpoint. Merged peak lists were generated for the 41 activated p53 ChIP-seq data sets and for the 17 control p53 ChIP-seq data sets by BEDTools mergeBed v2.24.0, where regions that had at least one nt overlap or were book-ended were merged.

Credit

These data were analyzed by Nguyen et al., at the National Institutes of Health/National Institute of Environmental Health Sciences (NIH/NIEHS) in Research Triangle Park, North Carolina, USA. Please direct all questions to menendez@niehs.nih.gov.

https://www.niehs.nih.gov/research/resources/databases/p53/index.cfm

References

Nguyen TT, Grimm SA, Bushel PR, Li J, Li Y, Bennett BD, Lavender CA, Ward JM, Fargo DC, Anderson CW, Li L, Resnick MA, Menendez D. Revealing a human p53 universe. Nucleic Acids Res. 2018;46:8153-8167