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An algorithmic perspective of de novo cis-regulatory motif finding based on ChIP-seq data

Bingqiang Liu, Jinyu Yang, Yang Li, Adam McDermaid, Qin Ma
2017 Briefings in Bioinformatics  
The purpose of this study is to review existing motif-finding methods for ChIP-seq data from an algorithmic perspective and provide new computational insight into this field.  ...  Finally, potential directions and plans for ChIP-seq-based motif-finding tools were showcased in support of future algorithm development.  ...  Motif Prediction based on ChIP-seq data | 13  ... 
doi:10.1093/bib/bbx026 pmid:28334268 fatcat:m4kvr736ojfz3jtwgxh6euisua

Assessing deep learning methods in cis-regulatory motif finding based on genomic sequencing data

Shuangquan Zhang, Anjun Ma, Jing Zhao, Dong Xu, Qin Ma, Yan Wang
2021 Briefings in Bioinformatics  
In this manuscript, we evaluated 20 DL methods for cis-regulatory motif prediction using 690 ENCODE ChIP-seq, 126 cancer ChIP-seq and 55 RNA CLIP-seq data.  ...  Identifying cis-regulatory motifs from genomic sequencing data (e.g.  ...  Based on these genomic sequencing data, substantial computational tools have been developed for de novo motifs finding [8] [9] [10] [11] [12] , allowing direct identification of significant motif patterns  ... 
doi:10.1093/bib/bbab374 pmid:34607350 pmcid:PMC8769700 fatcat:rhw4oihsvfb77jnrl2jp5tamrq

Transcription factor–DNA binding: beyond binding site motifs

Sachi Inukai, Kian Hong Kock, Martha L Bulyk
2017 Current Opinion in Genetics and Development  
While studies of TF-DNA binding have focused on TFs' intrinsic preferences for primary nucleotide sequence motifs, recent studies have elucidated additional layers of complexity that modulate TF-DNA binding  ...  Sequence-specific transcription factors (TFs) regulate gene expression by binding to cis-regulatory elements in promoter and enhancer DNA.  ...  Acknowledgments This work was funded by National Institutes of Health/National Human Genome Research Institute grant # R01 HG003985 (M.L.B.) and an A*STAR National Science Scholarship (K.H.K.).  ... 
doi:10.1016/j.gde.2017.02.007 pmid:28359978 pmcid:PMC5447501 fatcat:b3h57qji4vch5beb3u27cu5qky

RSAT 2022: regulatory sequence analysis tools

Walter Santana-Garcia, Jaime A Castro-Mondragon, Mónica Padilla-Gálvez, Nga Thi Thuy Nguyen, Ana Elizondo-Salas, Najla Ksouri, François Gerbes, Denis Thieffry, Pierre Vincens, Bruno Contreras-Moreira, Jacques van Helden, Morgane Thomas-Chollier (+1 others)
2022 Nucleic Acids Research  
This software suite performs (i) de novo motif discovery (including from genome-wide datasets like ChIP-seq/ATAC-seq) (ii) genomic sequences scanning with known motifs, (iii) motif analysis (quality assessment  ...  RSAT (Regulatory Sequence Analysis Tools) enables the detection and the analysis of cis-regulatory elements in genomic sequences.  ...  ), Luis Alberto Aguilar Bautista and Jair Garcia Sotelo (Laboratorio Nacional de Visualizaci ón Científica Avanzada, Mexico), Aurora Martín (Estaci ón Experimental de Aula dei, Zaragoza, Spain), along  ... 
doi:10.1093/nar/gkac312 pmid:35544234 fatcat:a7cjmc2okvboxnhfwwfmyoadua

An expansive human regulatory lexicon encoded in transcription factor footprints

Shane Neph, Jeff Vierstra, Andrew B. Stergachis, Alex P. Reynolds, Eric Haugen, Benjamin Vernot, Robert E. Thurman, Sam John, Richard Sandstrom, Audra K. Johnson, Matthew T. Maurano, Richard Humbert (+25 others)
2012 Nature  
the size of the human cis-regulatory lexicon.  ...  Finally, we describe a large collection of novel regulatory factor recognition motifs that are highly conserved in both sequence and function, and exhibit cell-selective occupancy patterns that closely  ...  Figure 6 . 6 De novo motif discovery expands the human regulatory lexicon. a, Overview of de novo motif discovery using DNaseI footprints. b, Annotation of the 683 de novo-derived motif models using previously  ... 
doi:10.1038/nature11212 pmid:22955618 pmcid:PMC3736582 fatcat:pjkrbgdw7nb3rdcpwddg4lvnte

From reads to insight: a hitchhiker's guide to ATAC-seq data analysis

Feng Yan, David R. Powell, David J. Curtis, Nicholas C. Wong
2020 Genome Biology  
We also review the reconstruction of transcriptional regulatory networks with multiomics data and highlight the current challenges of each step.  ...  Finally, we describe the potential of single-cell ATAC-seq and highlight the necessity of developing ATAC-seq specific analysis tools to obtain biologically meaningful insights.  ...  Availability of data and materials The raw sequencing data to produce the fragment size distribution, TSS enrichment plot, and peak tracks from Corces et al.  ... 
doi:10.1186/s13059-020-1929-3 pmid:32014034 fatcat:xowyj2wc5vfkvisoceizn7tdra

Motif signatures in stretch enhancers are enriched for disease-associated genetic variants

Daniel X Quang, Michael R Erdos, Stephen C J Parker, Francis S Collins
2015 Epigenetics & Chromatin  
Furthermore, de novo motif discovery not only recovers many of these motifs, but also identifies novel non-canonical motifs, providing additional insight into TF binding preferences.  ...  Conclusions: These results reinforce the role of SEs in influencing risk for diseases and suggest an expanded regulatory functional role for motifs that occur outside highly accessible chromatin.  ...  This work was supported by NIH grants 1-ZIA-HG000024 (to FSC) Additional file 4: De novo motif disocvery results. Zip archive of de novo motif discovery results.  ... 
doi:10.1186/s13072-015-0015-7 pmid:26180553 pmcid:PMC4502539 fatcat:k2pg2pncibgmdb7d52nwqyt5l4

Occupancy patterns of 208 DNA-associated proteins in a single human cell type [article]

E. Christopher Partridge, Surya B. Chhetri, Jeremy W. Prokop, Ryne C. Ramaker, Camden S. Jansen, Say-Tar Goh, Mark Mackiewicz, Kimberly M. Newberry, Laurel A. Brandsmeier, Sarah K. Meadows, C. Luke Messer, Andrew A. Hardigan (+7 others)
2018 biorxiv/medrxiv   pre-print
Here we present data and analyses of ChIP-seq experiments for 208 DNA-associated proteins (DAPs) in the HepG2 hepatocellular carcinoma line, spanning nearly a quarter of its expressed TFs, transcriptional  ...  We show that promoters and enhancers can be discriminated based on motif content and occupancy patterns.  ...  The 293 high-confidence motifs derived from analysis of the ChIP-seq data were quantitatively compared to all (human) motifs in the CIS-BP database and plotted based on similarity scores.  ... 
doi:10.1101/464800 fatcat:orwxoig4fncvpat4ttkamssewm

Chromatin accessibility pre-determines glucocorticoid receptor binding patterns

Sam John, Peter J Sabo, Robert E Thurman, Myong-Hee Sung, Simon C Biddie, Thomas A Johnson, Gordon L Hager, John A Stamatoyannopoulos
2011 Nature Genetics  
(a) The top scoring motif recovered from de novo motif discovery performed on the top 500 glucocorticoid receptor occupancy sites by ChIP-seq tag density (MEME E value = 8.6 × 10 −753 ) closely matches  ...  In summary, our results reveal the marked dominant effect of preexisting chromatin structure on de novo regulatory-factor binding.  ...  S.J., P.J.S., S.C.B. and T.A.J. conducted the DNase-seq, ChIP-seq and expression array experiments. S.J., P.J.S., R.E.T., M.-H.S. and J.A.S. analyzed the data. S.J., P.J.S., R.E.T., M.  ... 
doi:10.1038/ng.759 pmid:21258342 fatcat:whqjzpw6uva7latbrbgujuh5te

A De Novo Shape Motif Discovery Algorithm Reveals Preferences of Transcription Factors for DNA Shape Beyond Sequence Motifs

Md. Abul Hassan Samee, Benoit G. Bruneau, Katherine S. Pollard
2019 Cell Systems  
We present ShapeMF, a Gibbs sampling algorithm that identifies de novo shape motifs.  ...  Using binding data from hundreds of in vivo and in vitro experiments, we show that most DBPs have shape motifs and can occupy these in the absence of sequence motifs.  ...  An important methodological contribution of our manuscript is ShapeMF, a de novo shapemotif discovery algorithm.  ... 
doi:10.1016/j.cels.2018.12.001 pmid:30660610 pmcid:PMC6368855 fatcat:seevrrdjlfdrjhfnwbxqop65ty

Decoding a Signature-Based Model of Transcription Cofactor Recruitment Dictated by Cardinal Cis-Regulatory Elements in Proximal Promoter Regions

Christopher Benner, Sergiy Konovalov, Carlos Mackintosh, Kasey R. Hutt, Rieka Stunnenberg, Ivan Garcia-Bassets, Gregory S. Barsh
2013 PLoS Genetics  
In this study, furthermore, we have focused on promoters containing the nuclear respiratory factor 1 (NRF1) motif as the cardinal cis-regulatory element and have identified the pervasive association of  ...  Here, we provide evidence for a general model in which a series of cis-regulatory elements (here termed 'cardinal' motifs) prefer acting individually, rather than in fixed combinations, within the 2150  ...  Angels Almenar-Queralt for critical reading of the manuscript. We would like to also thank Dr. Amy Sullivan at Obrizus Communications for help in manuscript  ... 
doi:10.1371/journal.pgen.1003906 pmid:24244184 pmcid:PMC3820735 fatcat:73id74xwkfgzxg6tgox2kg4ng4

RNA-seq and ChIP-seq as Complementary Approaches for Comprehension of Plant Transcriptional Regulatory Mechanism

Isiaka Ibrahim Muhammad, Sze Ling Kong, Siti Nor Akmar Abdullah, Umaiyal Munusamy
2019 International Journal of Molecular Sciences  
In particular, we discuss how integration of ChIP-seq and RNA-seq data can help to unravel transcriptional regulatory networks.  ...  We show how the data from ChIP-seq can strengthen information generated from RNA-seq in elucidating gene regulatory mechanisms.  ...  ChIP-seq Workflow (Data Analysis) ChIP-sequencing data contain millions of short nucleotide sequences based on sequencing depth.  ... 
doi:10.3390/ijms21010167 pmid:31881735 pmcid:PMC6981605 fatcat:yv25lasn65cnrpkho2bx5asbgy

Computational methodology for ChIP-seq analysis

Hyunjin Shin, Tao Liu, Xikun Duan, Yong Zhang, X. Shirley Liu
2013 Quantitative Biology  
As more and more experimental laboratories are adopting ChIP-seq to unravel the transcriptional and epigenetic regulatory mechanisms, computational analyses of ChIP-seq also become increasingly comprehensive  ...  In this article, we review current computational methodology for ChIP-seq analysis, recommend useful algorithms and workflows, and introduce quality control measures at different analytical steps.  ...  Enriched sequence motifs can be identified from either de novo methods or known motif scanning [87] [88] [89] [90] at TF ChIPseq peaks.  ... 
doi:10.1007/s40484-013-0006-2 pmid:25741452 pmcid:PMC4346130 fatcat:zvglmsyhqjhrxi6ozfzv2yhw5m

Occupancy maps of 208 chromatin-associated proteins in one human cell type

E. Christopher Partridge, Surya B. Chhetri, Jeremy W. Prokop, Ryne C. Ramaker, Camden S. Jansen, Say-Tar Goh, Mark Mackiewicz, Kimberly M. Newberry, Laurel A. Brandsmeier, Sarah K. Meadows, C. Luke Messer, Andrew A. Hardigan (+8 others)
2020 Nature  
Here we present, as part of the ENCODE (Encyclopedia of DNA Elements) project, data and analyses from chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) experiments using the  ...  For example, FOX family motifs are enriched in ChIP-seq peaks of 37 other CAPs. We show that motif content and occupancy patterns can distinguish between promoters and enhancers.  ...  Data quality All validation and QC are described on the ENCODE portal. Software Software listed above, described in the methods section of the manuscript, and on the ENCODE portal.  ... 
doi:10.1038/s41586-020-2023-4 pmid:32728244 fatcat:vhzfnqjerrerfjcp72rmp6chxq

Next generation sequencing technology and genomewide data analysis: Perspectives for retinal research

Vijender Chaitankar, Gökhan Karakülah, Rinki Ratnapriya, Felipe O. Giuste, Matthew J. Brooks, Anand Swaroop
2016 Progress in retinal and eye research  
Acknowledgements We thank Jung-Woong Kim, Hyun-Jin Yang, Tiziana Cogliati and Lina Zelinger for discussions and comments on the manuscript.  ...  Some of the NGS analysis required the computational resources of the NIH HPC Biowulf cluster (http:// hpc.nih.gov).  ...  Transcript assembly De novo Trinity Full-length transcript assembler for the identification of novel transcripts from Illumina RNA-seq data.  ... 
doi:10.1016/j.preteyeres.2016.06.001 pmid:27297499 pmcid:PMC5112143 fatcat:ticudbtjlff6tgrmq4i5w3eq7y
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