Normalization, bias correction, and peak calling for ChIP-seq

Diaz, Aaron A.; Park, Kiyoub; Lim, Daniel A.; Song, Jun S.

doi:10.1515/1544-6115.1750

Cited by 105 publications

(93 citation statements)

References 32 publications

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“…Interestingly, its use of Lorenz curves to estimate sample coverage is similar in mathematical principle to the signal-to-noise ratios previously used by us and others to construct estimates of the size and quality of the background fraction of IP [1,2]. By contrast, CHANCE provides statistics on coverage, as well as percentage enrichment for signal and multi-sample scaling.…”

Section: Rationalementioning

confidence: 90%

CHANCE: comprehensive software for quality control and validation of ChIP-seq data

2012

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ChIP-seq is a powerful method for obtaining genome-wide maps of protein-DNA interactions and epigenetic modifications. CHANCE (CHip-seq ANalytics and Confidence Estimation) is a standalone package for ChIP-seq quality control and protocol optimization. Our user-friendly graphical software quickly estimates the strength and quality of immunoprecipitations, identifies biases, compares the user's data with ENCODE's large collection of published datasets, performs multi-sample normalization, checks against quantitative PCR-validated control regions, and produces informative graphical reports. CHANCE is available at https://github.com/songlab/chance.

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Section: Rationalementioning

confidence: 90%

CHANCE: comprehensive software for quality control and validation of ChIP-seq data

2012

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“…After observing a strong Pearson correlation of 0.8 to 0.98 between the biological replicates of each sample, the replicates were then summed (Zynda et al, 2017). Genomic windows with artificially high or extremely low log-transformed coverage in the upper and lower 2.5% tails of a calculated gamma distribution were removed (Zynda et al, 2017), and then data were normalized using sequence depth scaling (Diaz et al, 2012). In each 1-kb window, the data from each of the S phase samples were divided by the nonreplicating G1 reference data to further normalize for sequencing biases.…”

Section: Replication Timing Data Analysismentioning

confidence: 99%

Genomic Analysis of the DNA Replication Timing Program during Mitotic S Phase in Maize (Zea mays) Root Tips

Wear

Song²,

Zynda³

et al. 2017

Plant Cell

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All plants and animals must replicate their DNA, using a regulated process to ensure that their genomes are completely and accurately replicated. DNA replication timing programs have been extensively studied in yeast and animal systems, but much less is known about the replication programs of plants. We report a novel adaptation of the "Repli-seq" assay for use in intact root tips of maize (Zea mays) that includes several different cell lineages and present whole-genome replication timing profiles from cells in early, mid, and late S phase of the mitotic cell cycle. Maize root tips have a complex replication timing program, including regions of distinct early, mid, and late S replication that each constitute between 20 and 24% of the genome, as well as other loci corresponding to ;32% of the genome that exhibit replication activity in two different time windows. Analyses of genomic, transcriptional, and chromatin features of the euchromatic portion of the maize genome provide evidence for a gradient of early replicating, open chromatin that transitions gradually to less open and less transcriptionally active chromatin replicating in mid S phase. Our genomic level analysis also demonstrated that the centromere core replicates in mid S, before heavily compacted classical heterochromatin, including pericentromeres and knobs, which replicate during late S phase.

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“…Background subtraction was performed using the bamCompare tool. SES (Diaz et al, 2012) was used to normalize for read depth differences.…”

Section: Chip-sequencing Analysismentioning

confidence: 99%

Impaired removal of H3K4 methylation affects cell fate determination and gene transcription

et al. 2016

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Methylation of histone 3 lysine 4 (H3K4) is largely associated with promoters and enhancers of actively transcribed genes and is finely regulated during development by the action of histone methyltransferases and demethylases. H3K4me3 demethylases of the KDM5 family have been previously implicated in development, but how the regulation of H3K4me3 level controls developmental processes is not fully established. Here, we show that the H3K4 demethylase RBR-2, the unique member of the KDM5 family in C. elegans, acts cell-autonomously and in a catalytic-dependent manner to control vulva precursor cells fate acquisition, by promoting the LIN-12/Notch pathway. Using genome-wide approaches, we show that RBR-2 reduces the H3K4me3 level at transcription start sites (TSSs) and in regions upstream of the TSSs, and acts both as a transcription repressor and activator. Analysis of the lin-11 genetic locus, a direct RBR-2 target gene required for vulva precursor cell fate acquisition, shows that RBR-2 controls the epigenetic signature of the lin-11 vulva-specific enhancer and lin-11 expression, providing in vivo evidence that RBR-2 can positively regulate transcription and cell fate acquisition by controlling enhancer activity.

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Normalization, bias correction, and peak calling for ChIP-seq

Cited by 105 publications

References 32 publications

CHANCE: comprehensive software for quality control and validation of ChIP-seq data

CHANCE: comprehensive software for quality control and validation of ChIP-seq data

Genomic Analysis of the DNA Replication Timing Program during Mitotic S Phase in Maize (Zea mays) Root Tips

Impaired removal of H3K4 methylation affects cell fate determination and gene transcription

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