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Sample GSM2086281

Query DataSets for GSM2086281

Status

Public on Mar 12, 2016

Title

control_run56

Sample type

SRA

Source name

10 day old seedling

Organism

Arabidopsis thaliana

Characteristics

strain: Col-0
tissue: seedling
chip antibody: F3165 Sigma Monoclonal ANTI-FLAG M2

Growth protocol

liquid culture

Extracted molecule

genomic DNA

Extraction protocol

Chromatin‐immunoprecipitation experiments were carried out as described by Kwon et al. (Kwon et al, 2005), except that anti‐FLAG M2 magnetic beads (Sigma) were used and immunoprecipitations were only performed for two hours.
The ChIP‐seq libraries and the Illumina was performed as described by Yant et al. (Yant et al, 2010).

Library strategy

ChIP-Seq

Library source

genomic

Library selection

ChIP

Instrument model

Illumina Genome Analyzer II

Data processing

Standard Illumina base calling software was used to base call the 40-42 nucleotide sequence reads. We used SHORE (http://shore.sourceforge.net) as a platform for further analysis. The obtained reads were quality filtered and low quality bases at the 3’ end were pruned as described. GenomeMapper (http://1001genomes.org/software/) was used for mapping to the TAIR9 genome, allowing for up to four mismatching nucleotides and no gaps. To proceed, the mapped data were subjected to a heuristic for removal of duplicate sequence reads which were assumed to be uninformative for the detection of enriched loci. A threshold was applied limiting the number of 5’ ends mapping to the same position on the same strand. To retain the power to discriminate between multiple strongly enriched regions, the threshold for any particular position was varied depending on the coverage in close vicinity, such that the variance of the number of reads per position would roughly equal its mean in a 30 bp sliding window. We further applied a two-step procedure to identify regions significantly enriched in the positive sample when compared to the control. First, potentially enriched regions were identified based on the positive samples only. These sites were then directly compared to the corresponding control sample regions to assess statistical significance. For estimation of the depth of coverage for each position in the genome, all positive sample reads mapping to unique positions were extended in 3’ direction to 130 bp, corresponding to half the experimentally observed approximate DNA fragment size, while discarding all other reads. To detect possible peak sites, a 2 kb wide sliding window was applied to the coverage graph in single base steps. In each step a p-value was assigned to the coverage value at the central base using a one-sided Poisson test, with the distribution parameter set to the average coverage within the sliding window. Only positions with coverage greater than zero were included in the calculation of the average, assuming all other positions to be inaccessible to the experiment. Finally, any consecutive stretch of positions with p-value <0.05 and length >130 bp was retained as a potentially enriched site. To further reduce the number of regions to be considered, each was checked for unwarranted high average coverage in the control sample. A potential peak in the positive sample was discarded if the coverage mean in the control sample in the corresponding region was larger than the median average control coverage plus a tolerance of three standard deviations in all peak regions. For assignment of final p-values to each candidate region, in each replicate a one-sided binomial test was applied to the number of reads mapping to the region in the positive sample, with the distribution parameter N set to the joint read count for the site for the positive and the corresponding control sample. To estimate the probability parameter for the test, from now on called r, we computed a scaling factor s for the control sample and the chromosome containing the considered region. The complete chromosome sequence was subdivided into 400 base pair bins, and for each bin the positive sample as well as the control sample read counts were recorded. Then s was chosen such that the median ChIP sample read count for all bins equaled the median control sample read count multiplied by s. From this the binomial test parameter r was calculated as r=s/(s+1). Finally, false discovery rates were obtained through the Benjamini-Hochberg correction method. To establish a ranking of peak regions across replicates, the rank product over the per-replicate fdr ranks was used. To define the bound DNA set, we used all peaks with fdr > 0.1 in both ChIP experiments, resulting in a set of 1564 peaks.
Genome_build: TAIR9
Supplementary_files_format_and_content: text file with peak positions and signal intensity for both rev and control samples.

Submission date

Mar 11, 2016

Last update date

May 15, 2019

Contact name

Stephan Wenkel

E-mail(s)

wenkel@plen.ku.dk

Organization name

University of Copenhagen

Street address

Thorvaldsensvej 40