Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Richard Sandstrom mailto:sull@u.washington.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track, produced as part of the mouse ENCODE Project, contains deep sequencing DNase data that will be used to identify sites where regulatory factors bind to the genome (footprints). Footprinting is a technique used to define the DNA sequences that interact with and bind DNA-binding proteins, such as transcription factors, zinc-finger proteins, hormone-receptor complexes, and other chromatin-modulating factors like CTCF. The technique depends upon the strength and tight nature of protein-DNA interactions. In their native chromatin state, DNA sequences that interact directly with DNA-binding proteins are relatively protected from DNA degrading endonucleases, while the exposed/unbound portions are readily degraded by such endonucleases. A massively parallel next-generation sequencing technique to define the DNase hypersensitive sites in the genome was adopted. The DNase samples were sequenced using next-generation sequencing machines to significantly higher depths of 300-fold or greater. This produces a base-pair level resolution of the DNase susceptibility maps of the native chromatin state. These base-pair resolution maps represent and are dependent upon the nature and the specificity of interaction of the DNA with the regulatory/modulatory proteins binding at specific loci in the genome; thus they represent the native chromatin state of the genome under investigation. The deep sequencing approach has been used to define the footprint landscape of the genome by identifying DNA motifs that interact with known or novel DNA binding proteins. Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell/mouse). Digital DNaseI was performed by DNaseI digestion of intact nuclei, followed by isolating DNaseI "double-hit" fragments (Sabo et al., 2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Solexa platform (27 bp reads). High-quality reads were mapped to the NCBI37/mm9 mouse genome using Bowtie 0.12.5; only unique mappings were kept. DNaseI sensitivity is directly reflected in raw tag density (Raw Signal), which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI hypersensitive zones (HotSpots) were identified using the HotSpot algorithm (Sabo et al., 2004). False discovery rate thresholds of 1.0% (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36-mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within 1.0% (FDR 0.01) hypersensitive zones using a peak-finding algorithm. Only DNase Solexa libraries from unique cell types producing the highest quality data, as defined by Percent Tags in Hotspots (PTIH ~40%), were designated for deep sequencing to a depth of over 200 million tags. Results were validated by conventional DNaseI hypersensitivity assays using end-labeling/Southern blotting methods.

Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Richard Sandstrom mailto:sull@u.washington.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track is produced as part of the ENCODE Project. This track shows DNaseI sensitivity measured genome-wide in different cell lines using the Digital DNaseI methodology (see below), and DNaseI hypersensitive sites. DNaseI has long been used to map general chromatin accessibility and DNaseI hypersensitivity is a universal feature of active cis-regulatory sequences. The use of this method has led to the discovery of functional regulatory elements that include enhancers, insulators, promotors, locus control regions and novel elements. For each experiment (cell type) this track shows DNaseI sensitivity as a continuous function using sequencing tag density (Raw Signal), and discrete loci of DNaseI sensitive zones (HotSpots) and hypersensitive sites (Peaks)." For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols. Digital DNaseI was performed by DNaseI digestion of intact nuclei, isolating DNaseI 'double-hit' fragments as described in Sabo et al. (2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Solexa platform (36 bp reads). Uniquely mapping high-quality reads were mapped to the genome. DNaseI sensitivity is directly reflected in raw tag density (Raw Signal), which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI sensitive zones (HotSpots) were identified using the HotSpot algorithm described in Sabo et al. (2004). 1.0% false discovery rate thresholds (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within FDR 1.0% hypersensitive zones using a peak-finding algorithm.

Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Ross Hardison mailto:rch8@psu.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). Rationale for the Mouse ENCODE project: Knowledge of the function of genomic DNA sequences comes from three basic approaches. Genetics uses changes in behavior or structure of a cell or organism in response to changes in DNA sequence to infer function of the altered sequence. Biochemical approaches monitor states of histone modification, binding of specific transcription factors, accessibility to DNases and other epigenetic features along genomic DNA. In general, these features are associated with gene activity, but the precise relationships remain to be established. The third approach is evolutionary, using comparisons among homologous DNA sequences to find segments that are evolving more slowly or more rapidly than expected given the local rate of neutral change. Such changes are inferred to be under negative or positive selection, respectively, and interpreted as DNA sequences needed for a preserved (negative selection) or adaptive (positive selection) function. The ENCODE project aims to discover all the DNA sequences associated with various epigenetic features, with the reasonable expectation that these will also be functional (best tested by genetic methods). However, it is not clear how to relate these results with those from evolutionary analyses. The mouse ENCODE project aims to make this connection explicitly and with a moderate breadth. Assays identical to those being used in the ENCODE project are performed in cell types in mouse that are similar or homologous to those studied in the human project. The comparison will be used to discover which epigenetic features are conserved between mouse and human, and examine the extent to which these overlap with the DNA sequences under negative selection. The contribution of functional DNA preserved in mammals versus function in only one species will be discovered. The results will have a significant impact on the understanding of the evolution of gene regulation. Maps of DNaseI Sensitivity: DNaseI has long been used to map general chromatin accessibility, and DNaseI hypersensitivity is a universal feature of active cis-regulatory sequences. Maps of DNaseI sensitivity measured genome-wide are generated through DNaseI digestion, addition of linkers at the sites of cleavage, and library prep followed by massively parallel short read sequencing on the Illumina GAIIx and HiSeq platforms. The sequence tags are mapped back to the mouse genome, and a graph of the smoothed kernel density of DNaseI cleavage sites is displayed as the "Signal" track. This provides a quantitative estimate of the frequency of cleavage by DNaseI in the initial digest, which in turn is related to the accessibility of the DNA in the chromatin. Segments of greatest cleavage site density represent DNase hypersensitive sites (DHSs) and are identified as peaks by the F-seq program (Boyle et al. 2008). DHSs are candidates for any cis-regulatory module, including promoters, enhancers, insulators, and novel elements. The sequence reads, quality scores, and alignment coordinates from these experiments are available for download. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf

Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Richard Sandstrom mailto:sull@u.washington.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track, produced as part of the ENCODE Project, contains deep sequencing DNase data that will be used to identify sites where regulatory factors bind to the genome (footprints). Footprinting is a technique used to define the DNA sequences that interact with and bind DNA-binding proteins, such as transcription factors, zinc-finger proteins, hormone-receptor complexes, and other chromatin-modulating factors like CTCF. The technique depends upon the strength and tight nature of protein-DNA interactions. In their native chromatin state, DNA sequences that interact directly with DNA-binding proteins are relatively protected from DNA degrading endonucleases, while the exposed/unbound portions are readily degraded by such endonucleases. A massively parallel next-generation sequencing technique to define the DNase hypersensitive sites in the genome was adopted. Sequencing these next-generation-sequencing DNase samples to significantly higher depths of 300-fold or greater produces a base-pair level resolution of the DNase susceptibility maps of the native chromatin state. These base-pair resolution maps represent and are dependent upon the nature and the specificity of interaction of the DNA with the regulatory/modulatory proteins binding at specific loci in the genome; thus they represent the native chromatin state of the genome under investigation. The deep sequencing approach has been used to define the footprint landscape of the genome by identifying DNA motifs that interact with known or novel DNA binding proteins. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols. Digital DNaseI was performed by DNaseI digestion of intact nuclei, followed by isolating DNaseI 'double-hit' fragments as described in Sabo et al. (2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Solexa platform (27 bp reads). High-quality reads were mapped to the GRCh37/hg19 human genome using Bowtie 0.12.5 (Eland was used to map to NCBI36/hg18); only unique mappings were kept. DNaseI sensitivity is directly reflected in raw tag density (Signal), which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI hypersensitive zones (HotSpots) were identified using the HotSpot algorithm described in Sabo et al. (2004). False discovery rate thresholds of 1.0% (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36-mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within 1.0% (FDR 0.01) hypersensitive zones using a peak-finding algorithm. Only DNase Solexa libraries from unique cell types producing the highest quality data, as defined by Percent Tags in Hotspots (PTIH ~40%) were designated for deep sequencing to a depth of over 200 million tags.

Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Yijun Ruan mailto:ruanyj@gis.a-star.edu.sg). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). This track, produced as part of the ENCODE Project, contains deep sequencing DNase data that will be used to identify sites where regulatory factors bind to the genome (footprints). Footprinting is a technique used to define the DNA sequences that interact with and bind DNA-binding proteins, such as transcription factors, zinc-finger proteins, hormone-receptor complexes, and other chromatin-modulating factors like CTCF. The technique depends upon the strength and tight nature of protein-DNA interactions. In their native chromatin state, DNA sequences that interact directly with DNA-binding proteins are relatively protected from DNA degrading endonucleases, while the exposed/unbound portions are readily degraded by such endonucleases. A massively parallel next-generation sequencing technique to define the DNase hypersensitive sites in the genome was adopted. Sequencing these next-generation-sequencing DNase samples to significantly higher depths of 300-fold or greater produces a base-pair level resolution of the DNase susceptibility maps of the native chromatin state. These base-pair resolution maps represent and are dependent upon the nature and the specificity of interaction of the DNA with the regulatory/modulatory proteins binding at specific loci in the genome; thus they represent the native chromatin state of the genome under investigation. The deep sequencing approach has been used to define the footprint landscape of the genome by identifying DNA motifs that interact with known or novel DNA binding proteins. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols. Digital DNaseI was performed by DNaseI digestion of intact nuclei, followed by isolating DNaseI 'double-hit' fragments as described in Sabo et al. (2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Solexa platform (27 bp reads). High-quality reads were mapped to the GRCh37/hg19 human genome using Bowtie 0.12.5 (Eland was used to map to NCBI36/hg18); only unique mappings were kept. DNaseI sensitivity is directly reflected in raw tag density (Signal), which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI hypersensitive zones (HotSpots) were identified using the HotSpot algorithm described in Sabo et al. (2004). False discovery rate thresholds of 1.0% (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36-mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within 1.0% (FDR 0.01) hypersensitive zones using a peak-finding algorithm. Only DNase Solexa libraries from unique cell types producing the highest quality data, as defined by Percent Tags in Hotspots (PTIH ~40%) were designated for deep sequencing to a depth of over 200 million tags.

Project description:This track is produced as part of the mouse ENCODE Project. This track shows DNaseI sensitivity measured genome-wide in mouse tissues and cell lines using the Digital DNaseI methodology (see below), and DNaseI hypersensitive sites. DNaseI has long been used to map general chromatin accessibility and DNaseI hypersensitivity is a universal feature of active cis-regulatory sequences. The use of this method has led to the discovery of functional regulatory elements that include enhancers, insulators, promotors, locus control regions and novel elements. For each experiment (tissue/cell type) this track shows DNaseI sensitivity as a continuous function using sequencing tag density (Signal), and discrete loci of DNaseI sensitive zones (HotSpots) and hypersensitive sites (Peaks). For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell/mouse). Fresh tissues were harvested from mice and the nuclei prepared according to the tissue appropriate protocol (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell/mouse). Digital DNaseI was performed by DNaseI digestion of intact nuclei, isolating DNaseI 'double-hit' fragments as described in Sabo et al. (2006), and direct sequencing of fragment ends (which correspond to in vivo DNaseI cleavage sites) using the Illumina IIx (and Illumina HiSeq by early 2011) platform (36 bp reads). Uniquely mapping high-quality reads were mapped to the genome using the bowtie aligner. DNaseI sensitivity is directly reflected in raw tag density, which is shown in the track as density of tags mapping within a 150 bp sliding window (at a 20 bp step across the genome). DNaseI sensitive zones (HotSpots) were identified using the HotSpot algorithm described in Sabo et al. (2004). 1.0% false discovery rate thresholds (FDR 0.01) were computed for each cell type by applying the HotSpot algorithm to an equivalent number of random uniquely mapping 36mers. DNaseI hypersensitive sites (DHSs or Peaks) were identified as signal peaks within FDR 1.0% hypersensitive zones using a peak-finding algorithm (I-max).

Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Terry Furey mailto:tsfurey@duke.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). These tracks display DNaseI hypersensitivity (HS) evidence as part of the four Open Chromatin track sets. DNaseI is an enzyme that has long been used to map general chromatin accessibility, and DNaseI "hypersensitivity" is a feature of active cis-regulatory sequences. The use of this method has led to the discovery of functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions, and novel elements. DNaseI hypersensitivity signifies chromatin accessibility following binding of trans-acting factors in place of a canonical nucleosome. Together with FAIRE and ChIP-seq experiments, these tracks display the locations of active regulatory elements identified as open chromatin in multiple cell types (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?type=cellType) from the Duke, UNC-Chapel Hill, UT-Austin, and EBI ENCODE group. Within this project, open chromatin was identified using two independent and complementary methods: these DNaseI HS assays and Formaldehyde-Assisted Isolation of Regulatory Elements (FAIRE), combined with chromatin immunoprecipitation (ChIP) for select regulatory factors. DNaseI HS and FAIRE provide assay cross-validation with commonly identified regions delineating the highest confidence areas of open chromatin. ChIP assays provide functional validation and preliminary annotation of a subset of open chromatin sites. Each method employed Illumina (formerly Solexa) sequencing by synthesis as the detection platform. The Tier 1 and Tier 2 cell types were additional verified by a second platform, high-resolution 1% ENCODE tiled microarrays supplied by NimbleGen. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell). DNaseI hypersensitive sites were isolated using methods called DNase-seq or DNase-chip (Song and Crawford, 2010; Boyle et al., 2008a; Crawford et al., 2006). Briefly, cells were lysed with NP40, and intact nuclei were digested with optimal levels of DNaseI enzyme. DNaseI digested ends were captured from three different DNase concentrations, and material was sequenced using Illumina (Solexa) sequencing. DNase-seq data for Tier 1 and Tier 2 cell lines were verified by comparing multiple independent growths (replicates) and determining the reproducibility of the data. In general, cell lines were verified if 80% of the top 50,000 peaks in one replicate are detected in the top 100,000 peaks of a second replicate. For some cell types, additional verification was performed using similar material hybridized to NimbleGen Human ENCODE tiling arrays (1% of the genome) along with the input DNA as reference (DNase-chip). A more detailed protocol is available at http://hgwdev.cse.ucsc.edu/ENCODE/protocols/general/Duke_DNase_protocol.pdf. The read length for sequences from DNase-seq are 20 bases long due to a MmeI cutting step of the approximately >50kb DNA fragments extracted after DNaseI digestion. Sequences from each experiment were aligned to the genome using BWA (Li et al., 2010) for the NCBI 36 (hg19) assembly. The command used for these alignments was > bwa aln -t 8 genome.fa s_1.sequence.txt.bfq > s_1.sequence.txt.sai Where genome.fa is the whole genome sequence and s_1.sequence.txt.bfq is one lane of sequences convert into the required bfq format. Sequences from multiple lanes are combined for a single replicate using the bwa samse command, and converted in the sam/bam format using samtools. Only those that aligned to 4 or fewer locations were retained. Other sequences were also filtered based on their alignment to problematic regions (such as satellites and rRNA genes - see supplemental materials at http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeOpenChromDnase/supplemental/). The mappings of these short reads to the genome are available for download at http://hgwdev.cse.ucsc.edu/cgi-bin/hgFileUi?g=wgEncodeOpenChromDnase. The resulting digital signal was converted to a continuous wiggle track using F-Seq that employs Parzen kernel density estimation to create base pair scores (Boyle et al., 2008b). Input data has been generated for several cell lines. These are used directly to create a control/background model used for F-Seq when generating signal annotations for these cell lines. These models are meant to correct for sequencing biases, alignment artifacts, and copy number changes in these cell lines. Input data is not being generated directly for other cell lines. Instead, a general background model was derived from the available Input data sets. This should provide corrections for sequencing biases and alignment artifacts, but will not correct for cell type specific copy number changes. The exact command used for this step is > fseq -l 600 -v -f 0 -b <bff files> -p <iff files> aligments.bed where the (bff files) are the background files based on alignability, the (iff files) are the background files based on the Input experiments, and alignments.bed are a bed file of filtered sequence alignments. Discrete DNaseI HS sites (peaks) were identified from DNase-seq F-seq density signal. Significant regions were determined by fitting the data to a gamma distribution to calculate p-values. Contiguous regions where p-values were below a 0.05/0.01 threshold were considered significant. Data from the high-resolution 1% ENCODE tiled microarrays supplied by NimbleGen were normalized using the Tukey biweight normalization, and peaks were called using ChIPOTle (Buck, et al., 2005) at multiple levels of significance. Regions matched on size to these peaks that were devoid of any significant signal were also created as a null model. These data were used for additional verification of Tier 1 and Tier 2 cell lines by ROC analysis. Files containing this data can be found in the Downloads directory (http://hgwdev.cse.ucsc.edu/cgi-bin/hgFileUi?db=hg19&g=wgEncodeOpenChromDnase) labeled Validation view. Release 1 (April 2011) of this track consists of a remapping of all previously released experiments to the human reference genome GRCh37/hg19 (these data were previously mapped to NCBI36/hg18; please see the Release Notes section of the hg18 Open Chromatin track (http://hgwdev.cse.ucsc.edu/cgi-bin/hgTrackUi?db=hg18&g=wgEncodeChromatinMap) for information on the NCBI36/hg18 releases of the data). There are 21 new DNaseI experiments in this release, on 19 new cell lines. New to this release is a reconfiguration of how this track is displayed in relation to other tracks from the Duke/UNC/UT-Austin/EBI group. A synthesis of open chromatin evidence from the three assay types was compiled for Tier 1 and 2 cell lines plus NHEK will also be added in this release and can be previewed in: Open Chromatin Synthesis (http://genome-preview.cse.ucsc.edu/cgi-bin/hgTrackUi?db=hg19&g=wgEncodeOpenChromSynth). Enhancer and Insulator Functional assays: A subset of DNase and FAIRE regions were cloned into functional tissue culture reporter assays to test for enhancer and insulator activity. Coordinates and results from these experiments can be found at http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeOpenChromDnase/supplemental/.

Project description:This data was generated by ENCODE. If you have questions about the data, contact the submitting laboratory directly (Terry Furey mailto:tsfurey@duke.edu). If you have questions about the Genome Browser track associated with this data, contact ENCODE (mailto:genome@soe.ucsc.edu). These tracks display a synthesis of evidence from different assays as part of the four Open Chromatin track sets. This track displays open chromatin regions and/or transcription factor binding sites identified in multiple cell types by one or more complementary methodologies, DNaseI hypersensitivity (HS) (Duke DNaseI HS), Formaldehyde-Assisted Isolation of Regulatory Elements (FAIRE) (UNC FAIRE), and chromatin immunoprecipitation (ChIP) for select regulatory factors (UTA TFBS). Each methodology was performed on the same cell type using identical growth conditions. (Note: Data for some or all ChIP experiments may not be available for all cell types). Regions that overlap between methodologies identify regulatory elements that are cross-validated indicating high confidence regions. In addition, multiple lines of evidence suggest that regions detected by a single assay (e.g., DNase-only or FAIRE-only) are also biologically relevant (Song et al., submitted). DNaseI HS data: DNaseI is an enzyme that has long been used to map general chromatin accessibility, and DNaseI "hypersensitivity" is a feature of active cis-regulatory sequences.The use of this method has led to the discovery of functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions, and novel elements. DNaseI hypersensitivity signifies chromatin accessibility following binding of trans-acting factors in place of a canonical nucleosome. FAIRE data: FAIRE (Formaldehyde Assisted Isolation of Regulatory Elements) is a method to isolate and identify nucleosome-depleted regions of the genome. FAIRE was initially discovered in yeast and subsequently shown to identify active regulatory elements in human cells (Giresi et al., 2007). Similar to DNaseI HS, FAIRE appears to identify functional regulatory elements that include promoters, enhancers, silencers, insulators, locus control regions and novel elements. ChIP data: ChIP (Chromatin Immunoprecipitation) is a method to identify the specific location of proteins that are directly or indirectly bound to genomic DNA. By identifying the binding location of sequence-specific transcription factors, general transcription machinery components, and chromatin factors, ChIP can help in the functional annotation of the open chromatin regions identified by DNaseI HS mapping and FAIRE. Input data: As a background control experiment, we sequenced the input genomic DNA sample that was used for ChIP. Crosslinked chromatin is sheared and the crosslinks are reversed without carrying out the immunoprecipitation step. This sample is otherwise processed in a manner identical to the ChIP sample as described below. The input track is useful in revealing potential artifacts arising from the sequence alignment process such as copy number differences between the reference genome and the sequenced samples, as well as regions of poor sequence alignability. For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf For each site, the maximum F-Seq Density Signal value has been calculated for each assay that was performed in that cell type. F-Seq employs Parzen kernel density estimation to create base pair scores (Boyle et al., 2008b). Significant regions, or peaks, were determined by fitting the data to a gamma distribution to calculate p-values. Contiguous regions where p-values were below a 0.05 (DNaseI HS, ChIP) or 0.1 (FAIRE) threshold were considered significant. See assay specific description pages ( Duke DNaseI HS, UNC FAIRE and UTA TFBS) for more details. A Fisher's Combined P-value for DNaseI HS and FAIRE was calculated using Fisher's combined probability test. First, a test statistic is calculated using the formula x^2 = -2*sum(ln(pi)) where pi are the p-values calculated for DNaseI HS and FAIRE. X2 follows a chi-squared distribution, thus a combined p-value can be assigned to this test statistic.

Dataset Information

DNaseI Hypersensitivity by Digital DNaseI from ENCODE/PSU

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