Abstract Summary Transcription factors regulate gene expression by binding to specific short DNA sequences of 5-20 bp to regulate the rate of transcription of genetic information from DNA to messenger RNA. We present PWMScan, a fast web-based tool to scan server-resident genomes for matches to a user-supplied PWM or transcription factor binding site model from a public database. Availability and implementation The web server and source code are available at http://ccg.vital-it.ch/pwmscan and https://sourceforge.net/projects/pwmscan, respectively. Supplementary information Supplementary data are available at Bioinformatics online

Ambrosini, Giovanna

Bucher, Philipp

Groux, Romain

Hancock, John

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Genome analysisPWMScan: a fast tool for scanning entiregenomes with a position-specific weight matrixGiovanna Ambrosini1,2,*, Romain Groux1,2 and Philipp Bucher1,2,*1The Swiss Institute for Experimental Cancer Research (ISREC), Swiss Federal Institute of Technology Lausanne(EPFL) and 2Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland*To whom correspondence should be addressed.Associate Editor: John HancockReceived on November 10, 2017; revised on February 27, 2018; editorial decision on March 1, 2018; accepted on March 2, 2018AbstractSummary: Transcription factors regulate gene expression by binding to specific short DNAsequences of 5–20 bp to regulate the rate of transcription of genetic information from DNA tomessenger RNA. We present PWMScan, a fast web-based tool to scan server-resident genomes formatches to a user-supplied PWM or transcription factor binding site model from a public database.Availability and implementation: The web server and source code are available at http://ccg.vital-it.ch/pwmscan and https://sourceforge.net/projects/pwmscan, respectively.Contact: giovanna.ambrosini@epfl.ch or philipp.bucher@epfl.chSupplementary information: Supplementary data are available at Bioinformatics online.1 IntroductionKnowing where transcription factors (TFs) bind to the genome isthe key to understanding gene regulation. The binding specificity of aTF is commonly represented by a numerical matrix, either as aposition weight matrix (PWM), a position frequency matrix (PFM) ora letter probability matrix (LPM). The three representations areinformation-wise equivalent and inter-convertible. A PWM containsweights for each base at each motif position. By summing up weightsat corresponding positions, a binding score can be computed for anybase sequence of the same length as the PWM. Large collections of TFspecificity matrices are nowadays available from public libraries suchas JASPAR (Khan et al., 2017) or HOCOMOCO (Kulakovskiy et al.,2017).PWMScan is a web-server for rapid scanning of large genomes forhigh-scoring matches to a user-supplied or server-resident PWM.Compared to other web-based PWM scanning tools, PWMScan isunique in that it scans server-resident whole genomes rather thanuser-uploaded DNA sequences. Other key features are: (i) menu-drivenaccess to genomes of >30 model organisms; (ii) menu-driven access to>300 public PWM libraries; (iii) support of various PWM representa-tions and formats; (iv) cut-off values can be specified as match scoresor P-values; (v) output in BEDdetail format with match scores andP-values; (vi) links to UCSC genome browser for visualization of results;and (vii) action buttons to transfer match lists to analysis tools.A short description of the PWMScan server follows. Technicaldetails about algorithms, programs and data are provided underSupplementary Material.2 Data and methodsGenome sequences were downloaded from the NCBI in FASTA format.Indexed versions for rapid scanning were generated for Bowtie(Langmead et al., 2009). The motif databases offered by PWMScanhave been downloaded from the MEME Suite website (Bailey et al.,2009). LPMs have been converted to integer PWMs (see SupplementaryMaterial).The input form of the PWMScan server is shown in Figure 1.The user chooses a genome assembly from a menu. Optionally, aBED file may be uploaded to restrict the search to genomic regionsof particular interest, e.g. open chromatin regions. The right side ofthe form offers several ways to specify a DNA motif. PWMs from aserver-resident database are chosen from a pull-down menu.Alternatively, matrices can be entered into a text area or uploaded.Accepted motif types are: PFMs, LPMs, real or integer PWMs andIUPAC consensus sequences. PFMs can be entered in several for-mats, including TRANSFAC and JASPAR.All motif types have to be converted into integer PWMs for input tothe genome search engines (see Supplementary Material). Default con-version parameters are proposed and can be changed by the user.VC The Author(s) 2018. Published by Oxford University Press. 2483This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/),which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contactjournals.permissions@oup.comBioinformatics, 34(14), 2018, 2483–2484doi: 10.1093/bioinformatics/bty127Advance Access Publication Date: 5 March 2018Applications NoteFor instance, real PWMs can be rescaled on input by a multiplicationfactor to ensure sufficient resolution after integer conversion. IUPACconsensus sequences are converted into binary matrices consisting of0 and 1.For all matrix formats, the cut-off value can be specified asPWM score, as P-value or as percentage of the score range(0%¼minimal score and 100%¼maximal score). For IUPAC con-sensus sequences, the cut-off value is specified as a maximal numberof mismatches allowed.The P-value of a PWM score x is defined as the probability thata random k-mer sequence of the length of the PWM has a bindingscorex given the base composition of the genome.The whole genome scan takes as input an integer PWM and acorresponding cut-off. The output is a list of sequence regions thatmatch the PWM with a match score higher or equal to the cut-offvalue. Depending on the length of the PWM and the cut-off, oneof the following search strategies is chosen: (i) Bowtie, a fastmemory-efficient short read aligner using indexed genomes and(ii) matrix_scan, a C program developed by our group using a con-ventional search algorithm.The first strategy is more efficient for short PWMs and high cut-off values. It requires as a first step the generation of a list of allk-mers that match the PWM with the given cut-off. The list ofk-mers is then mapped to the genome using Bowtie.The second strategy takes genome sequences in FASTA format asinput. Individual chromosomes are processed in parallel and distrib-uted to multiple cores by a Python script. We empirically found thatthis approach becomes more efficient if the number of k-mers ex-ceeds 105 sequences. matrix_scan was benchmarked for speed to-gether with five other matrix scanners and was found to be thefastest (see Supplementary Material).The basic search step outputs a list of PWM matches, includingthe genomic coordinates, the DNA sequence and the match score.Post-processing of this list involves computation of the corres-ponding P-values, addition of the matrix name and, optionally,elimination of overlapping matches. The final match list is providedin BEDdetail format. The output page further shows the totalnumber of PWM matches and a sequence logo reflecting the letter-probabilities of the input matrix. Action buttons are provided for:(i) sending the match lists to analysis tools of the ChIP-Seq and SSAservers (Ambrosini et al., 2016), (ii) extracting DNA sequencesaround the matches, (iii) sending the output to the UCSC genomebrowser for visualization and (iv) liftover of the match coordinatesto other assemblies of the same or related species.PWMScan is meant to support many types of genomic data ana-lysis and designed to be interoperable with other tools from ourgroup and elsewhere. An example of a typical workflow involvingChIP-seq data is presented in Supplementary Material.PWMScan is also available as a command-line software packagefrom SourceForge, including a master script scheduling all computa-tional steps running during a web job.3 BenchmarkThe runtime of PWMScan was measured by scanning the humangenome (UCSC assembly hg19) with two different PWMs fromJASPAR, STAT1 with length 11 bp and CTCF with length 19 bp,and different cut-off values expressed as P-values. Results are shownin Table 1. Note that for longer motifs and higher P-values, theBowtie-based approach becomes inefficient, whereas matrix_scanremains reasonably fast.AcknowledgementsThe PWMScan server is hosted by Vital-IT, the SIB Swiss Institute ofBioinformatics’ Competence Centre in Bioinformatics and Computational Biology.FundingThis work was supported by the Swiss Institute of Bioinformatics and SwissFederal Institute of Technology Lausanne (EPFL).Conflict of Interest: none declared.ReferencesAmbrosini,G. et al. (2016) The ChIP-Seq tools and web server: a resourcefor analyzing ChIP-seq and other types of genomic data. BMC Genomics, 17, 938.Bailey,T.L. et al. (2009) MEME Suite: tools for motif discovery and searching.Nucleic Acids Res., 37, W202–W208.Khan,A. et al. (2017) JASPAR 2018: update of the open-access database oftranscription factor binding profiles and its web framework. Nucleic AcidsRes., 46, D260–D266.Kulakovskiy,I.V. et al. (2017) HOCOMOCO: towards a complete collectionof transcription factor binding models for human and mouse via large-scaleChIP-Seq analysis. Nucleic Acids Res., 46, D252–D259.Langmead,B. et al. (2009) Ultrafast and memory-efficient alignment of shortDNA sequences to the human genome. Genome Biol., 10, R25.Fig. 1. Screen shot of the PWMScan graphical user interfaceTable 1. Benchmark results with different PWMs and P-valuesPWM/P-value Bowtie speed Matrix_scan speedSTAT1(len ¼ 11 bp)/105 3 30/5aSTAT1(len ¼ 11 bp)/104 8 40/8aSTAT1(len ¼ 11 bp)/103 60 65/30aCTCF(len ¼ 19 bp)/105 12 40/6aCTCF(len ¼ 19 bp)/104 90 50/10aCTCF(len ¼ 19 bp)/103 720 90/35aNote: Speed is expressed in seconds. The benchmarking tests have beenrun on a Linux/CentOS7/x86_64 workstation with 48 CPU-cores and 256 GBof DRAM.aPerformance measurements using matrix_scan in parallel over 10 CPU-cores.2484 G.Ambrosini et al.

PWMScan: a fast tool for scanning entire genomes with a position-specific weight matrix

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