TFBSTools specifications

Information


Unique identifier OMICS_11082
Name TFBSTools
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 2.0
Computer skills Advanced
Version 1.18.0
Stability Stable
Requirements
methods, parallel, grid, testthat, S4Vectors(>=0.9.25), R(>=3.2.2), Biobase(>=2.28), Biostrings(>=2.36.4), BiocGenerics(>=0.14.0), BiocParallel(>=1.2.21), BSgenome(>=1.36.3), caTools(>=1.17.1), CNEr(>=1.4.0), DirichletMultinomial(>=1.10.0), GenomeInfoDb(>=1.6.1), GenomicRanges(>=1.20.6), gtools(>=3.5.0), IRanges(>=2.2.7), DBI(>=0.6), RSQLite(>=1.0.0), rtracklayer(>=1.28.10), seqLogo(>=1.34.0), TFMPvalue(>=0.0.5), XML(>=3.98-1.3), XVector(>=0.8.0), BiocStyle(>=1.7.7), JASPAR2014(>=1.4.0), knitr(>=1.11), JASPAR2016(>=1.0.0)
Maintained Yes

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Documentation


Maintainer


  • person_outline Ge Tan <>

Publication for TFBSTools

TFBSTools in publications

 (9)
PMCID: 5848805
PMID: 29608722
DOI: 10.1093/gbe/evy041

[…] these sequences for known motifs that are described in the jaspar database (). we searched for all homo sapiens motifs on both + and – strands and specified a minimum score of 100% using r packages tfbstools () and jaspar2016 ()., we performed soft clustering of dhs data using mfuzz (), using standardized expression sets prepared from log2 values of mean dhs activity among replicates for shared […]

PMCID: 5796217
PMID: 29337929
DOI: 10.3390/ijms19010271

[…] gene expression. we extracted a 2000-bp upstream sequence of the promoter for all degs and dems according to the principle of promoter prediction of eukaryotic animals [,]. based on the results of tfbstools software (version 1.16.0) configured with position-weight matrices (pwm) from the jaspar2016 database, we obtained 338 transcription factors (tfs) regulating the degs in p-n1icd versus […]

PMCID: 5727488
PMID: 29235573
DOI: 10.1038/s41598-017-17730-2

[…] the cel files in each entry are presented as an excel workbook in supplementary table ., de novo motif prediction analysis was conducted using the r console (3.1.1) and the jaspar2014 (1.1.1) and tfbstools (1.4.0) packages. motifs obtained from databases have been sorted by match score. minimum scores of 80 and 90% have been considered as valid (supplementary fig. )., quantitative real-time […]

PMCID: 5371733
PMID: 28270558
DOI: 10.15252/msb.20167507

[…] jaspar2016 (tan, ). each pwm was screened against a positive and a negative set of sequences (e.g., 250 bp upstream sequences of ernas and remaining ncrnas) with the searchseq function in the tfbstools package (tan & lenhard, ). we defined a cutoff to distinguish between motif occurrence and not‐occurrence as 80% of the maximal score that the pwm could reach. the number of sequences […]

PMCID: 5316978
PMID: 28218276
DOI: 10.1038/srep42663

[…] we analyzed 20 vials for nonstress and 20 vials for zinc stress conditions. for natural strains, we used 15 vials for the zinc stress condition and 10 vials for the nonstress condition., we use tfbstools software to predict binding sites of mtf-1 in the kuz promoter region and in the kuz intron where fbti0019170 is inserted. position weight matrices for mtf-1 transcription factor […]


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TFBSTools institution(s)
Computational Regulatory Genomics, MRC Clinical Sciences Centre, Imperial College London, London, UK
TFBSTools funding source(s)
The EU FP7 grant 242048 (ZF-HEALTH); Medical Research Council UK

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