scholarly journals CCSeq: Clusters of Colocalized Sequences

2019 ◽  
Author(s):  
Stefan Golas
Keyword(s):  
Transcription Factor ◽  
Genome Annotation ◽  
R Package ◽  
Chromosome 17 ◽  
One Dimensional ◽  
Link Type ◽  
Transcription Factor Complexes ◽  
Random Distributions ◽  
Enhancer Sequences ◽  
Binding Sequence

Abstract0.1MotivationPotential transcription factor (TF) complexes may be identified by testing whether the binding sequences of individual TF proteins form clusters with each other. These clusters may also indicate TF inhibition due to competitive occupancy of enhancer regions. Genome annotation data containing the coordinates of enhancer sequences is highly accessible via position-weight matrix tools.0.2ResultsAn algorithm called CCSeq (Clusters of Colocalized Sequences) was developed for identifying clusters of sequences along a one-dimensional line, such as a chromosome, given genome annotation files and a cut-off distance as inputs. The algorithm was applied to the binding sequences of the constituent proteins of two known transcription factor complexes, the HSF1 homotrimer and one form of the NF-κB complex, a dimer of NFKB2 and RELB. 28 clusters of HSF1 trimer binding sequences were identified on chromosome Y, and 16 clusters of the NFKB2 and RELB dimer were identified on chromosome 17, compared to 0 clusters identified in any of the five simulated random distributions for each of the two sets of TF proteins. Additionally, structural patterns of these binding sequence clusters are described.0.3Availability and ImplementationThis algorithm is freely available as an R package on the open source R repository CRAN at the following link: https://cran.r-project.org/package=colocalized. Genome annotation files were obtained from the PWMScan tool at https://ccg.epfl.ch/pwmtools/pwmscan.php hosted by the Swiss Insitute of Bioinformatics (2) (3).

scholarly journals marge: An API for Analysis of Motifs Using HOMER in R

2018 ◽  
Author(s):  
Robert A. Amezquita
Keyword(s):  
Transcription Factor ◽  
De Novo ◽  
R Package ◽  
Transcription Factor Binding ◽  
Open Chromatin ◽  
Motif Analysis ◽  
Sequence Composition ◽  
Chip Sequencing ◽  
Factor Binding ◽  
Link Type

Profiling of open chromatin regions through the assay for transposase-accessible chromatin (ATAC) and transcription factor binding via chromatin immunoprecipitation (ChIP) sequencing has increased our ability to resolve patterns of putative transcription factor binding sites at the genome-wide level. Popular tools such as [HOMER (http://homer.ucsd.edu/homer/) and [MEME] (http://meme-suite.org/) have driven forward the analyses of sequence composition, deriving de novo motifs and searching for the enrichment of known motifs. However, their interfaces do not allow for the construction of parallel inquiries of multiple datasets. Furthermore, their results do not conform to formats amenable to ‘tidy’ analyses, presenting a significant bottleneck in motif analysis. Here, I present ‘marge’, a companion ‘R’ package that interfaces with HOMER to facilitate the construction of queries and to tidy results for further downstream analyses.

scholarly journals AB0210 ACREULAR: AN R PACKAGE FOR THE CALCULATION AND VISUALISATION OF ACR/EULAR RELATED RHEUMATOID ARTHRITIS MEASURES

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1405.1-1406
Author(s):  
F. Morton ◽  
J. Nijjar ◽  
C. Goodyear ◽  
D. Porter
Keyword(s):  
Rheumatoid Arthritis ◽  
Functional Status ◽  
Rheumatic Diseases ◽  
Web Application ◽  
R Package ◽  
Diagnostic Classification ◽  
Microsoft Excel ◽  
Link Type ◽  
Large Joint ◽  
Programming Skills

Background:The American College of Rheumatology (ACR) and the European League Against Rheumatism (EULAR) individually and collaboratively have produced/recommended diagnostic classification, response and functional status criteria for a range of different rheumatic diseases. While there are a number of different resources available for performing these calculations individually, currently there are no tools available that we are aware of to easily calculate these values for whole patient cohorts.Objectives:To develop a new software tool, which will enable both data analysts and also researchers and clinicians without programming skills to calculate ACR/EULAR related measures for a number of different rheumatic diseases.Methods:Criteria that had been developed by ACR and/or EULAR that had been approved for the diagnostic classification, measurement of treatment response and functional status in patients with rheumatoid arthritis were identified. Methods were created using the R programming language to allow the calculation of these criteria, which were incorporated into an R package. Additionally, an R/Shiny web application was developed to enable the calculations to be performed via a web browser using data presented as CSV or Microsoft Excel files.Results:acreular is a freely available, open source R package (downloadable fromhttps://github.com/fragla/acreular) that facilitates the calculation of ACR/EULAR related RA measures for whole patient cohorts. Measures, such as the ACR/EULAR (2010) RA classification criteria, can be determined using precalculated values for each component (small/large joint counts, duration in days, normal/abnormal acute-phase reactants, negative/low/high serology classification) or by providing “raw” data (small/large joint counts, onset/assessment dates, ESR/CRP and CCP/RF laboratory values). Other measures, including EULAR response and ACR20/50/70 response, can also be calculated by providing the required information. The accompanying web application is included as part of the R package but is also externally hosted athttps://fragla.shinyapps.io/shiny-acreular. This enables researchers and clinicians without any programming skills to easily calculate these measures by uploading either a Microsoft Excel or CSV file containing their data. Furthermore, the web application allows the incorporation of additional study covariates, enabling the automatic calculation of multigroup comparative statistics and the visualisation of the data through a number of different plots, both of which can be downloaded.Figure 1.The Data tab following the upload of data. Criteria are calculated by the selecting the appropriate checkbox.Figure 2.A density plot of DAS28 scores grouped by ACR/EULAR 2010 RA classification. Statistical analysis has been performed and shows a significant difference in DAS28 score between the two groups.Conclusion:The acreular R package facilitates the easy calculation of ACR/EULAR RA related disease measures for whole patient cohorts. Calculations can be performed either from within R or by using the accompanying web application, which also enables the graphical visualisation of data and the calculation of comparative statistics. We plan to further develop the package by adding additional RA related criteria and by adding ACR/EULAR related measures for other rheumatic disorders.Disclosure of Interests:Fraser Morton: None declared, Jagtar Nijjar Shareholder of: GlaxoSmithKline plc, Consultant of: Janssen Pharmaceuticals UK, Employee of: GlaxoSmithKline plc, Paid instructor for: Janssen Pharmaceuticals UK, Speakers bureau: Janssen Pharmaceuticals UK, AbbVie, Carl Goodyear: None declared, Duncan Porter: None declared

scholarly journals kataegis: an R package for identification and visualization of the genomic localized hypermutation regions using high-throughput sequencing

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xue Lin ◽  
Yingying Hua ◽  
Shuanglin Gu ◽  
Li Lv ◽  
Xingyu Li ◽  
...  
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Somatic Mutations ◽  
R Package ◽  
Frequency Of Occurrence ◽  
Link Type ◽  
Genomic Landscape ◽  
One Step ◽  
Flanking Regions

Abstract Background Genomic localized hypermutation regions were found in cancers, which were reported to be related to the prognosis of cancers. This genomic localized hypermutation is quite different from the usual somatic mutations in the frequency of occurrence and genomic density. It is like a mutations “violent storm”, which is just what the Greek word “kataegis” means. Results There are needs for a light-weighted and simple-to-use toolkit to identify and visualize the localized hypermutation regions in genome. Thus we developed the R package “kataegis” to meet these needs. The package used only three steps to identify the genomic hypermutation regions, i.e., i) read in the variation files in standard formats; ii) calculate the inter-mutational distances; iii) identify the hypermutation regions with appropriate parameters, and finally one step to visualize the nucleotide contents and spectra of both the foci and flanking regions, and the genomic landscape of these regions. Conclusions The kataegis package is available on Bionconductor/Github (https://github.com/flosalbizziae/kataegis), which provides a light-weighted and simple-to-use toolkit for quickly identifying and visualizing the genomic hypermuation regions.

scholarly journals EspM Is a Conserved Transcription Factor That Regulates Gene Expression in Response to the ESX-1 System

mBio ◽  
2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Kevin G. Sanchez ◽  
Micah J. Ferrell ◽  
Alexandra E. Chirakos ◽  
Kathleen R. Nicholson ◽  
Robert B. Abramovitch ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Protein Transport ◽  
Transcriptional Response ◽  
Secretion System ◽  
Pathogenic Species ◽  
Macrophage Infection ◽  
Content Type ◽  
Link Type ◽  
Phagosomal Membrane

ABSTRACT Pathogenic mycobacteria encounter multiple environments during macrophage infection. Temporally, the bacteria are engulfed into the phagosome, lyse the phagosomal membrane, and interact with the cytosol before spreading to another cell. Virulence factors secreted by the mycobacterial ESX-1 (ESAT-6-system-1) secretion system mediate the essential transition from the phagosome to the cytosol. It was recently discovered that the ESX-1 system also regulates mycobacterial gene expression in Mycobacterium marinum (R. E. Bosserman, T. T. Nguyen, K. G. Sanchez, A. E. Chirakos, et al., Proc Natl Acad Sci U S A 114:E10772–E10781, 2017, https://doi.org/10.1073/pnas.1710167114), a nontuberculous mycobacterial pathogen, and in the human-pathogenic species M. tuberculosis (A. M. Abdallah, E. M. Weerdenburg, Q. Guan, R. Ummels, et al., PLoS One 14:e0211003, 2019, https://doi.org/10.1371/journal.pone.0211003). It is not known how the ESX-1 system regulates gene expression. Here, we identify the first transcription factor required for the ESX-1-dependent transcriptional response in pathogenic mycobacteria. We demonstrate that the gene divergently transcribed from the whiB6 gene and adjacent to the ESX-1 locus in mycobacterial pathogens encodes a conserved transcription factor (MMAR_5438, Rv3863, now espM). We prove that EspM from both M. marinum and M. tuberculosis directly and specifically binds the whiB6-espM intergenic region. We show that EspM is required for ESX-1-dependent repression of whiB6 expression and for the regulation of ESX-1-associated gene expression. Finally, we demonstrate that EspM functions to fine-tune ESX-1 activity in M. marinum. Taking the data together, this report extends the esx-1 locus, defines a conserved regulator of the ESX-1 virulence pathway, and begins to elucidate how the ESX-1 system regulates gene expression. IMPORTANCE Mycobacterial pathogens use the ESX-1 system to transport protein substrates that mediate essential interactions with the host during infection. We previously demonstrated that in addition to transporting proteins, the ESX-1 secretion system regulates gene expression. Here, we identify a conserved transcription factor that regulates gene expression in response to the ESX-1 system. We demonstrate that this transcription factor is functionally conserved in M. marinum, a pathogen of ectothermic animals; M. tuberculosis, the human-pathogenic species that causes tuberculosis; and M. smegmatis, a nonpathogenic mycobacterial species. These findings provide the first mechanistic insight into how the ESX-1 system elicits a transcriptional response, a function of this protein transport system that was previously unknown.

scholarly journals Xenopus Smad4β Is the Co-Smad Component of Developmentally Regulated Transcription Factor Complexes Responsible for Induction of Early Mesodermal Genes

1999 ◽  
Vol 214 (2) ◽  
pp. 354-369 ◽  
Author(s):  
Michael Howell ◽  
Fumiko Itoh ◽  
Christophe E. Pierreux ◽  
Sigridur Valgeirsdottir ◽  
Susumu Itoh ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Developmentally Regulated ◽  
Transcription Factor Complexes

scholarly journals MADAP, a flexible clustering tool for the interpretation of one-dimensional genome annotation data

2007 ◽  
Vol 35 (Web Server) ◽  
pp. W201-W205 ◽  
Author(s):  
C. D. Schmid ◽  
T. Sengstag ◽  
P. Bucher ◽  
M. Delorenzi
Keyword(s):  
Genome Annotation ◽  
One Dimensional ◽  
Annotation Data
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