bioconductor-tfbstools

name: bioconductor-tfbstoolsdescription: TFBSTools is a package for the analysis and manipulation of transcription factor binding sites. It includes matrices conversion between Position Frequency Matirx (PFM), Position Weight Matirx (PWM) and Information Content Matrix (ICM). It cwhen_to_use: "Use when: Matrix Conversion: Converting Position Frequency Matrices (PFMs) to Position Weight Matrices (PWMs) or Information Content Matrices (ICMs) using toPWM and toICM.; Motif Scanning: Scanning nucleotide sequences or pairwise alignments for transcription factor binding sites using searchSeq or searchAln.; Database Querying: Querying and retrieving matrix data from the JASPAR database using getMatrixSet. Not for: For high-throughput scanning of thousands of large genomic regions, use motifmatchr instead, because searchSeq is optimized for targeted DNAString or DNAStringSet objects rather than massive GRanges peak sets.; For de novo motif discovery without ext"user-invocable: false

TFBSTools

Dependencies & Environment

Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.

• Version: 1.50.0 · Bioconductor: 3.23 · R: ≥ 4.6
• Imports: Biobase, Biostrings, pwalign, BiocGenerics, BiocParallel, BSgenome, caTools, DirichletMultinomial, Seqinfo, GenomicRanges, gtools, IRanges, DBI, RSQLite, rtracklayer, seqLogo, S4Vectors, TFMPvalue, XML, XVector
• Install: BiocManager::install("TFBSTools")

When to Use

• Matrix Conversion: Converting Position Frequency Matrices (PFMs) to Position Weight Matrices (PWMs) or Information Content Matrices (ICMs) using toPWM and toICM.
• Motif Scanning: Scanning nucleotide sequences or pairwise alignments for transcription factor binding sites using searchSeq or searchAln.
• Database Querying: Querying and retrieving matrix data from the JASPAR database using getMatrixSet.
• Random Profile Generation: Generating random profile matrices via permutation or Dirichlet multinomial mixture models using permuteMatrix and rPWMDmm.
• Visualization: Visualizing sequence logos for basic PWMs or Transcription Factor Flexible Models (TFFMs) using seqLogo.

When NOT to Use

• For high-throughput scanning of thousands of large genomic regions, use motifmatchr instead, because searchSeq is optimized for targeted DNAString or DNAStringSet objects rather than massive GRanges peak sets.
• For de novo motif discovery without external dependencies, use universalmotif because runMEME requires the external MEME suite to be installed on the system.

Data Requirements

• Input Format: PFMatrix objects, DNAString or DNAStringSet for sequences, and Axt objects for alignments.
• Structure: 4-row matrices representing A, C, G, T counts or probabilities.
• Normalization State: Raw position frequency counts for PFMs, which are then converted to log2 probability ratios for PWMs.

Key Parameters

• type (default): The type of matrix conversion in toPWM (e.g., "log2probratio") or the type of p-value calculation in pvalues (e.g., "TFMPvalue").
• pseudocounts (default): Numeric value (default 0.8) added to correct small counts or eliminate zero values before log transformation in toPWM.
• bg (default): A named numeric vector representing background nucleotide frequencies (e.g., c(A=0.25, C=0.25, G=0.25, T=0.25)).
• min.score (default): Minimum score threshold (e.g., "60%" or "80%") for a sequence match to be reported in searchSeq or searchAln.
• schneider (default): Logical in toICM indicating whether to apply the Schneider correction.
• strand (default): Controls which strand is searched in searchSeq (e.g., "*" for both strands).

Best Practices

• Use pseudocounts=0.8 in toPWM rather than the square root of sequences to avoid overly harsh corrections on zero values.
• When scanning sequences with searchSeq, use pvalues with type="TFMPvalue" to calculate empirical p-values for the match scores.
• Use writeGFF3 or writeGFF2 to export SiteSet objects into standard genomic formats for downstream visualization.

Common Pitfalls

• Pitfall: runMEME fails to execute.
  Fix: Ensure the external MEME software suite is installed and the binary argument correctly points to the executable.
• Pitfall: searchSeq returns too many false positive hits.
  Fix: Increase the min.score threshold (e.g., from "60%" to "90%") to enforce stricter matching.
• Pitfall: toPWM throws an error due to zero counts.
  Fix: Ensure pseudocounts is set to a positive value (like 0.8) to eliminate zero values before log transformation.

Alternatives

• motifmatchr: For faster, parallelized motif scanning across large GRanges objects.
• universalmotif: For comprehensive motif manipulation and de novo discovery without relying strictly on external binaries like MEME.
• Biostrings: For basic PWM matching (matchPWM), though it lacks the advanced statistical models and TFFM support of TFBSTools.

Citations

• Tan G, Lenhard B (2016). TFBSTools: an R/Bioconductor package for transcription factor binding site analysis. Bioinformatics.
• Mathelier and Wasserman (2013). The next generation of transcription factor binding site, TFFM.

References

• Homepage: https://bioconductor.org/packages/TFBSTools
• Vignette: https://bioconductor.org/packages/release/bioc/vignettes/TFBSTools/inst/doc/TFBSTools.html

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