scholarly journals Genomic feature extraction and comparison based on global alignment of ChIP-sequencing data

Bioengineered ◽  
2016 ◽  
Vol 8 (3) ◽  
pp. 248-255
Author(s):  
Binhua Tang
Keyword(s):  
Feature Extraction ◽  
Global Alignment ◽  
Genomic Feature ◽  
Sequencing Data ◽  
Chip Sequencing

scholarly journals COPAR: A ChIP-Seq Optimal Peak Analyzer

2017 ◽  
Vol 2017 ◽  
pp. 1-4
Author(s):  
Binhua Tang ◽  
Xihan Wang ◽  
Victor X. Jin
Keyword(s):  
High Throughput ◽  
Genomic Feature ◽  
Data Sets ◽  
Sequencing Data ◽  
Genomic Features ◽  
Peak Alignment ◽  
Chip Sequencing ◽  
Quality Check ◽  
User Friendly ◽  
High Throughput Experiments

Sequencing data quality and peak alignment efficiency of ChIP-sequencing profiles are directly related to the reliability and reproducibility of NGS experiments. Till now, there is no tool specifically designed for optimal peak alignment estimation and quality-related genomic feature extraction for ChIP-sequencing profiles. We developed open-sourced COPAR, a user-friendly package, to statistically investigate, quantify, and visualize the optimal peak alignment and inherent genomic features using ChIP-seq data from NGS experiments. It provides a versatile perspective for biologists to perform quality-check for high-throughput experiments and optimize their experiment design. The package COPAR can process mapped ChIP-seq read file in BED format and output statistically sound results for multiple high-throughput experiments. Together with three public ChIP-seq data sets verified with the developed package, we have deposited COPAR on GitHub under a GNU GPL license.

scholarly journals Global sequence characterization of rice centromeric satellite based on oligomer frequency analysis in large-scale sequencing data

2010 ◽  
Vol 26 (17) ◽  
pp. 2101-2108 ◽  
Author(s):  
Jiří Macas ◽  
Pavel Neumann ◽  
Petr Novák ◽  
Jiming Jiang
Keyword(s):  
Large Scale ◽  
Rice Genome ◽  
Supplementary Information ◽  
Sequencing Data ◽  
Satellite Repeat ◽  
Frequency Spectra ◽  
Consensus Sequences ◽  
Chip Sequencing ◽  
Conserved Sequence ◽  
Centromeric Satellite

Abstract Motivation: Satellite DNA makes up significant portion of many eukaryotic genomes, yet it is relatively poorly characterized even in extensively sequenced species. This is, in part, due to methodological limitations of traditional methods of satellite repeat analysis, which are based on multiple alignments of monomer sequences. Therefore, we employed an alternative, alignment-free, approach utilizing k-mer frequency statistics, which is in principle more suitable for analyzing large sets of satellite repeat data, including sequence reads from next generation sequencing technologies. Results: k-mer frequency spectra were determined for two sets of rice centromeric satellite CentO sequences, including 454 reads from ChIP-sequencing of CENH3-bound DNA (7.6 Mb) and the whole genome Sanger sequencing reads (5.8 Mb). k-mer frequencies were used to identify the most conserved sequence regions and to reconstruct consensus sequences of complete monomers. Reconstructed consensus sequences as well as the assessment of overall divergence of k-mer spectra revealed high similarity of the two datasets, suggesting that CentO sequences associated with functional centromeres (CENH3-bound) do not significantly differ from the total population of CentO, which includes both centromeric and pericentromeric repeat arrays. On the other hand, considerable differences were revealed when these methods were used for comparison of CentO populations between individual chromosomes of the rice genome assembly, demonstrating preferential sequence homogenization of the clusters within the same chromosome. k-mer frequencies were also successfully used to identify and characterize smRNAs derived from CentO repeats. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.

Profiling of Aberrant DNA Methylation In AML Reveals Subclasses of CpG Islands with Epigenetic or Genetic Association

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 2498-2498
Author(s):  
Claudia Gebhard ◽  
Mohammed Sadeh ◽  
Dagmar Glatz ◽  
Lucia Schwarzfischer ◽  
Rainer Spang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
De Novo ◽  
Conflicts Of Interest ◽  
Cpg Island ◽  
Cpg Islands ◽  
Sequencing Data ◽  
Cpg Island Methylator Phenotype ◽  
Chip Sequencing ◽  
Aberrant Dna Methylation ◽  
Methylation Patterns

Abstract Abstract 2498 CpG islands show frequent and often disease-specific epigenetic alterations during malignant transformation, however, the underlying mechanisms are poorly understood. We used methyl-CpG immunoprecipitation (MCIp) to generate comparative DNA methylation profiles of 30 patients with acute myeloid leukemia for human CpG islands across the genome. DNA methylation profiles across 23.000 CpG islands revealed highly heterogeneous methylation patterns in AML with over 6000 CpG islands showing aberrant de novo methylation in AML. Based on these profiles we selected a subset of 380 CpG islands (covering 15.000 individual CpGs) for detailed fine-mapping analyses of aberrant DNA methylation in 185 patients with AML (50% normal karyotype). We found that a proportion of patients (5/185) displayed a concerted hypermethylation at almost all studied loci, representing the rare CpG island methylator phenotype (CIMP) in AML. Meta analysis of methylation profiling and published ChIP sequencing data separated CpG islands in two groups. A highly correlated subgroup of CpG island regions was strongly associated with histone H3 lysine 27 trimethylation in human hematopoietic progenitor cells, suggesting that disease-related de novo DNA methylation at these CpG islands is linked with polycomb group protein (PcG)-mediated repression. The group of mainly non-PcG target CpG islands showed heterogeneous methylation patterns across patients and unsupervised hierarchical clustering revealed a correlation of methylation profiles with genetic disease markers, including oncofusion proteins as well as CEBPA- and NPM1-mutations. Our study suggests that both epigenetic as well as genetic aberrations may underlay AML-related changes in CpG island DNA methylation states. Disclosures: No relevant conflicts of interest to declare.

An interactive environment for agile analysis and visualization of ChIP-sequencing data

2016 ◽  
Vol 23 (4) ◽  
pp. 349-357 ◽  
Author(s):  
Mads Lerdrup ◽  
Jens Vilstrup Johansen ◽  
Shuchi Agrawal-Singh ◽  
Klaus Hansen
Keyword(s):  
Sequencing Data ◽  
Chip Sequencing ◽  
Interactive Environment

scholarly journals A strand specific high resolution normalization method for chip-sequencing data employing multiple experimental control measurements

2012 ◽  
Vol 7 (1) ◽  
pp. 2 ◽  
Author(s):  
Stefan Enroth ◽  
Claes R Andersson ◽  
Robin Andersson ◽  
Claes Wadelius ◽  
Mats G Gustafsson ◽  
...  
Keyword(s):  
High Resolution ◽  
Normalization Method ◽  
Sequencing Data ◽  
Experimental Control ◽  
Chip Sequencing

EZH2 Inhibitors Are Broadly Efficacious in Multiple Myeloma As Single Agent and in Combination with Standard of Care Therapeutics

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5672-5672 ◽  
Author(s):  
Shilpi Arora ◽  
Kaylyn Williamson ◽  
Shruti Apte ◽  
Srividya Balachander ◽  
Jennifer Busby ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Cell Lines ◽  
Single Agent ◽  
Standard Of Care ◽  
Tumor Growth Inhibition ◽  
Sequencing Data ◽  
Employment Equity ◽  
Chip Sequencing ◽  
Equity Ownership

Abstract Post-translational modifications of the histone proteins play a key role in regulating processes that require access to DNA. Specifically, methylation of lysine 27 on histone 3 (H3K27) is intimately linked with transcriptional repression. EZH2, a histone lysine methyl transferase is the catalytic component of the PRC2 complex, which catalyzes H3K27 methylation. EZH2 dysregulation has been observed in different malignancies and inhibition of its catalytic activity has emerged as a novel therapeutic approach to treat human cancers. Potent, selective and reversible EZH2 small molecule inhibitors are currently being tested in Ph. 1 clinical trials. We and others have reported EZH2 dependencies across non-Hodgkin Lymphoma subtypes in cancer cell lines, in xenograft mouse models and in lymphoma patients. We identified Multiple Myeloma as potential clinical application for EZH2 inhibitors. Treatment with EZH2 inhibitors such as CPI-360, CPI-169 and CPI-1205 cause apoptosis in multiple myeloma and plasmacytoma cell models and causes tumor growth inhibition in myeloma xenograft models at well tolerated doses. An EZH2-controlled transcriptional signature across various multiple myeloma was identified using integrated RNA-sequencing and ChIP-sequencing data. Combination studies testing EZH2 inhibitors with standard of care (SOC) agents across a panel of multiple myeloma cell lines showed synergistic responses with several of the SOC agents in vitro and in vivo. Disclosures Arora: Constellation Pharmaceuticals: Employment, Equity Ownership. Williamson:Constellation Pharmaceuticals: Employment, Equity Ownership. Apte:Constellation Pharmaceuticals: Employment, Equity Ownership. Balachander:Constellation Pharmaceuticals: Employment, Equity Ownership. Busby:Constellation Pharmaceuticals: Employment, Equity Ownership. Hatton:Constellation Pharmaceuticals: Employment, Equity Ownership. Bryant:Constellation Pharmaceuticals: Employment, Equity Ownership. Trojer:Constellation Pharmaceuticals: Employment, Equity Ownership.

scholarly journals mBISON: Finding miRNA target over-representation in gene lists from ChIP-sequencing data

2015 ◽  
Vol 8 (1) ◽  
Author(s):  
Marie Luise Gebhardt ◽  
Arvind Singh Mer ◽  
Miguel Angel Andrade-Navarro
Keyword(s):  
Mirna Target ◽  
Sequencing Data ◽  
Chip Sequencing

scholarly journals Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework

2019 ◽  
Vol 47 (15) ◽  
pp. 7809-7824 ◽  
Author(s):  
Jinyu Yang ◽  
Anjun Ma ◽  
Adam D Hoppe ◽  
Cankun Wang ◽  
Yang Li ◽  
...  
Keyword(s):  
Deep Learning ◽  
Dna Binding ◽  
Binding Sites ◽  
Motif Discovery ◽  
Distribution Model ◽  
Sequencing Data ◽  
Shape Information ◽  
Chip Sequencing ◽  
Regulatory Motifs ◽  
Learning Framework

Abstract The identification of transcription factor binding sites and cis-regulatory motifs is a frontier whereupon the rules governing protein–DNA binding are being revealed. Here, we developed a new method (DEep Sequence and Shape mOtif or DESSO) for cis-regulatory motif prediction using deep neural networks and the binomial distribution model. DESSO outperformed existing tools, including DeepBind, in predicting motifs in 690 human ENCODE ChIP-sequencing datasets. Furthermore, the deep-learning framework of DESSO expanded motif discovery beyond the state-of-the-art by allowing the identification of known and new protein–protein–DNA tethering interactions in human transcription factors (TFs). Specifically, 61 putative tethering interactions were identified among the 100 TFs expressed in the K562 cell line. In this work, the power of DESSO was further expanded by integrating the detection of DNA shape features. We found that shape information has strong predictive power for TF–DNA binding and provides new putative shape motif information for human TFs. Thus, DESSO improves in the identification and structural analysis of TF binding sites, by integrating the complexities of DNA binding into a deep-learning framework.

scholarly journals COMPARING MULTIPLE ChIP-SEQUENCING EXPERIMENTS

2011 ◽  
Vol 09 (02) ◽  
pp. 269-282 ◽  
Author(s):  
HATICE GULCIN OZER ◽  
YI-WEN HUANG ◽  
JIEJUN WU ◽  
JEFFREY D. PARVIN ◽  
TIM HUI-MING HUANG ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Enrichment Analysis ◽  
Real Data ◽  
Illumina Genome Analyzer ◽  
Sequencing Data ◽  
Promoter Regions ◽  
Experimental Conditions ◽  
Single Experiment ◽  
Chip Sequencing ◽  
Variable Genes

New high-throughput sequencing technologies can generate millions of short sequences in a single experiment. As the size of the data increases, comparison of multiple experiments on different cell lines under different experimental conditions becomes a big challenge. In this paper, we investigate ways to compare multiple ChIP-sequencing experiments. We specifically studied epigenetic regulation of breast cancer and the effect of estrogen using 50 ChIP-sequencing data from Illumina Genome Analyzer II. First, we evaluate the correlation among different experiments focusing on the total number of reads in transcribed and promoter regions of the genome. Then, we adopt the method that is used to identify the most stable genes in RT-PCR experiments to understand background signal across all of the experiments and to identify the most variable transcribed and promoter regions of the genome. We observed that the most variable genes for transcribed regions and promoter regions are very distinct. Gene ontology and function enrichment analysis on these most variable genes demonstrate the biological relevance of the results. In this study, we present a method that can effectively select differential regions of the genome based on protein-binding profiles over multiple experiments using real data points without any normalization among the samples.

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