Yale ChIP RFBR Track Settings
 
Yale ChIP-chip Regulatory Factor Binding Regions Analysis   (Yale ChIP)

This track is part of a parent called 'Yale ChIP'. To show other tracks of this parent, go to the Yale ChIP configuration page.

Display mode:       Reset to defaults

List subtracks: only selected/visible    all  
dense
 Yale RFBR Clusters  Yale ChIP-chip Regulatory Factor Binding Regions (RFBR) Clusters   schema 
dense
 Yale RFBR Deserts  Yale ChIP-chip Regulatory Factor Binding Regions (RFBR) Deserts   schema 
Data version: Dec 2005 Freeze
Data coordinates converted via liftOver from: May 2004 (NCBI35/hg17)

Description

Regulatory Factor Binding Regions (RFBRs) were identified from ChIP-Chip experimental data; they are non-randomly distributed in the ENCODE regions with local enrichment and depletion. By mapping the full set of RFBRs onto the human genome sequence, we identified 689 genomic subregions with RFBR enrichment and 726 subregions with RFBR depletion (the RFBR clusters and deserts, respectively) in the ENCODE regions.

Methods

The data set analyzed in this study consists of 105 lists of transcriptional regulatory elements (TREs) in the ENCODE regions. It was released on December 13, 2005 by the Transcriptional Regulation Group. TRE lists made available after this data freeze were not included in this study. A total of 29 transcription factors (BAF155, BAF170, Brg1, CEBPe, CTCF, E2F1, E2F4, H3ac, H4ac, H3K27me3, H3K27me3, H3K4me1, H3K4me2, H3K4me3, H3K9K14me2, HisH4, c-Jun, c-Myc, P300, P63, Pol2, PU1, RARecA, SIRT1, Sp1, Sp3, STAT1, Suz12, and TAF1) were assayed by seven laboratories (Affymetrix, Sanger, Stanford, UCD, UCSD, UT, Yale) using ChIP-chip experiments on three different microarray platforms (Affymetrix tiling array, NimbleGen tiling array, and traditional PCR array) in nine cell lines (HL-60, HeLa, GM06990, K562, IMR90, HCT116, THP1, Jurkat, and fibroblasts) or at two different experimental time points (P0, before addition of gamma-interferon, and P30, 30 minutes after the addition of gamma-interferon).

The raw data from these 105 ChIP-chip experiments was uniformly processed using a method based on the false discovery rate (Efron, 2004). Three sets of TRE lists were generated at 1%, 5%, and 10% false discovery rates respectively, and the list generated at the lowest (1%) false discovery rate was used in this study. The non-redundant factor-specific RFBR lists were mapped onto the ENCODE regions. Uninterrupted genomic regions that are covered by one or more RFBRs were identified as RFBR groups. Neighboring groups that are less than 1 kb apart were collected into RFBR clusters. Un-clustered groups that are covered by more than three RFBRs were promoted into clusters. Further details of the method may be found in Zhang et al. (2007).

Credits

The data set was made available by the Transcriptional Regulation Group of the ENCODE Project Consortium. The RFBR cluster and desert tracks were generated by Zhengdong Zhang from Mark Gerstein's group at Yale University.

References

Efron B. Large-scale simultaneous hypothesis testing: The choice of a null hypothesis. Journal of the American Statistical Association. 2004;99(465):96-104.

Zhang ZD, Paccanaro A, Fu Y, Weissman S, Weng Z, Chang J, Snyder M, Gerstein M. Statistical analysis of the genomic distribution and correlation of regulatory elements in the ENCODE regions. Genome Res. 2007 Jun;17(6):787-97.