Description Usage Format Details Source References Examples
Vector of Oct4 bound genes predicted by analyzing ESC ChIP-seq data from GSE11724.
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A data frame with 5158 observations on the following 21 variables.
Ranka numeric vector
Chra character vector
Starta numeric vector
Enda numeric vector
Stranda character vector
Annotationa character vector
Genea character vector
EntrezIDa numeric vector
peak_lengtha numeric vector
FDRa numeric vector
left_peakboundarya numeric vector
right_peakboundarya numeric vector
peak_summita numeric vector
bound_centera numeric vector
bound_widtha numeric vector
maxTa numeric vector
maxT_posa numeric vector
max_log2FCa numeric vector
maxFC_posa numeric vector
minuslog10_minPoisPa numeric vector
minPoisP_posa numeric vector
To obtain the TF bound gene predictions, the ChIP-seq data is processed using CisGenome with the default parameters. Only peaks significant at a FDR of 0.10 are retained and annotated by assigning peaks to genes if the peak falls within 10kbp upstream or 5kbp downstream of the gene transcription start site. Only the highest ranking peak for each gene is retained in the data frame for input. To be clear, the Rank in the data frame corresponds to the original peak ranking by CisGenome. The ChIPx ranking is simply the order of genes in the data frame.
www.ncbi.nlm.nih.gov/geo/
Marson A. et al. (2008) Connecting microRNA genes to the core trancsriptional regulatory circuitry of embryonic stem cells. Cell 134, 521-533.
Barrett T., et al. (2007) NCBI GEO: mining tens of millions of expression profiles - database and tools update. Nucl. Acids Res. 35, D760-D765.
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