New SLiMSuite, SeqSuite and RJESuite releases are now available

New releases of SLiMSuite, SeqSuite and RJESuite are now available from the Edwards Lab software page.

Please note that the documentation (particularly the manuals) are still lagging a bit behind, so do report anything that does not make sense. The default settings also need to be verified as there is a chance that some of these may have inadvertently changed over the years. (The same core code is now used for the webservers, which often have different defaults.) Checking these along with updating and checking the servers themselves are ongoing priorities.

A full list of updated modules is given below. As well as SLiMMaker now handling end of sequence characters, the biggest changes this release are updates to CompariMotif to (3.7) output unmatched input motifs and (3.8) improve handling of partially overlapping ambiguous positions (e.g. [AGS] and [ST]). The motivation behind both these changes is the ongoing benchmarking (and preparation for publication) of QSLiMFinder and the creation of SLiMBench for benchmarking motif prediction methods. A QSLiMFinder section has been added to the SLiMFinder Manual (section 5.4). SLiMBench is still a work in progress and will be documented in a later release.

Updates since last release:

• comparimotif_V3: Updated from Version 3.6.
→ Version 3.7: Added coreIC and output of unmatched motifs.
→ Version 3.8: Added overlaps=T/F : Whether to include overlapping ambiguities (e.g. [KR] vs [HK]) as match [True]
→ Version 3.8: Changed scoring of overlapping ambiguities - uses IC of all possible ambiguities. Added "Ugly" match type.

• slimbench: Created.
→ Version 0.0: Initial Compilation.
→ Version 0.1: Functional version with benchmarking dataset generation.
→ Version 1.0: Consolidation of "working" version with additional basic benchmarking analysis.
→ Version 1.1: Added simulated dataset construction and benchmarking.
→ Version 1.2: Added MinIC filtering to benchmark assessment. Sorted beginning/end of line for reduced ELMs.
→ Version 1.3: Made SimCount a list rather than Integer. Sorted CompariMotif assessment issue.
→ Version 1.4: Added ICCut and SLiMLenCut as lists and output columns.
→ Version 1.5: Added Summary Results output table. Removed PropRes.

• slimmaker: Updated from Version 1.0.
→ Version 1.1: Modified to work with end of line characters.

• slimsearch: Updated from Version 1.5.
→ Version 1.6: Minor tweaks to Log output. Add option for UPC number in occ output.

• rje: Updated from Version 4.1.
→ Version 4.2: Modified INI reading across the board to look in ../settings/ and look for defaults.ini as well as rje.ini.
→ Version 4.2: Enabled handing on -ini FILE in addition to ini=FILE.
→ Version 4.3: Added ilist and nlist types to cmdRead for objects. (Lists of integers and floats). Add ratio() function.

• rje_blast: Updated from Version 1.13.
→ Version 1.14: Added blast.checkProg(qtype,stype) to check whether blastp setting matches sequence formats.

• rje_db: Created.
→ Version 0.0: Initial Compilation.
→ Version 0.1: Added merge tables option.
→ Version 0.2: Miscellaneous updates to various methods.
→ Version 0.3: Minor doc tweaks and added keepFields().

• rje_seq: Updated from Version 3.12.
→ Version 3.13: Updated sequence type checking for use with GABLAM 2.10.

• rje_seqlist: Created.
→ Version 0.0: Initial Compilation. Based on rje_seq 3.10.
→ Version 0.1: Added basic species filtering and sequence output.
→ Version 0.2: Added upper case filtering.
→ Version 0.3: Added accnum filtering and sequence renaming.
→ Version 0.4: Added sequence redundancy filtering.
→ Version 0.5: Added newgene=X for sequence renaming (newgene_spcode__newaccXXX). NewAcc no longer fixed Upper Case.
→ Version 1.0: Upgraded to "ready" Version 1.0. Added concatenate=T and split=X options for sequence concatenation.
→ Version 1.0: Added reading of sequence type from rje_seq.py and mixed=T/F.
→ Version 1.1: Added shortName() and modified SeqDict.

• rje_sequence: Updated from Version 2.0.
→ Version 2.1: Added re_unirefprot = re.compile('^([A-Za-z0-9\-]+)\s+([A-Za-z0-9]+)_([A-Za-z0-9]+)\s+')

• rje_slim: Updated from Version 1.5.
→ Version 1.6: Fixed splitting bug introduced by lower case motifs.

• rje_slimcore: Updated from Version 1.8.
→ Version 1.9: Minor modifications to Log output. Updated motifSeq() function to output unmasked sequences.

• rje_slimlist: Updated from Version 0.6.
→ Version 1.0: Functional module with lower case motif splitting fixed and ? -> .{0,1} replacement.

• rje_zen: Updated from Version 1.0.
→ Version 1.1: Added a few more words here and there.

CompariMotif V3.6

Both the webserver and SLiMSuite download have now been updated to CompariMotif Version 3.6.

One of the main changes over earlier versions of CompariMotif is that ELM Class exports can now be used directly as input. Any tab-delimited file (*.tdt or *.tsv) with a "Regex" field header will be recognised and motifs extracted using the ELMIdentifier, Regex and Description fields.

To handle some of the more complex motifs now in ELM, the motif splitting function has also been expanded and strengthened. (The caveat is the small bug in the current download which will be fixed in the next release.) In addition to either/or regex elements, variable length non-wildcards are now recognised and will be reformatted for CompariMotif searching.

For example:

Motif [IL]{1,2}[^P].(RG|K)

will be split to form:

Motif_a [IL][^P].RG
Motif_b [IL][^P].K
Motif_c [IL][IL][^P].RG
Motif_d [IL][IL][^P].K

The descriptions will also be appended with "Version 1", "Version 2" etc.

The final minor update replaces ? in motif Regex patterns with .{0,1}. As it uses the same modules for motif input, these changes will also affect SLiMSearch input but not (yet) be taken into consideration for the SLiMChance statistics.

Note. The 2008 version of ELM on the bioware server was manually split and therefore the suffixes added by CompariMotif for later versions of ELM will not necessarily match up.

Minor bug in CompariMotif 3.6 download

The recent fixing up of the server has highlighted a couple of bugs that have crept in during the upgrading of CompariMotif to handle complex motifs better. (More on this in a later post.) The problem is restricted to lower case motifs, so stick to upper case and all will be well. It will be fixed in the next release. A replacement rje_slimlist.py file is available on request if anyone needs to fix it urgently. (This also features replacement of "?" characters with "{0,1}" so these motifs are no longer rejected.)

New software downloads available

SLiMsuite and SeqSuite downloads have now been updated and are available from my homepage.

The only real change of note since the last release is that CompariMotif can now recognise ELM Class downloads and the motif splitting has been updated to cope with variable-length non-wildcard repeats (e.g. R{0,1}).

The CompariMotif webserver is undergoing some final checks and should be back up shortly, with SLiMFinder and SLiMSearch to follow.

SLiMSuite servers temporarily down

Following some technical issues that have arisen due to some quite major behind-the-scenes re-organisation, the Bioware webserver implementations of SLiMSuite programs have been temporarily taken off-line.

The plan is to give them a bit of attention, iron out any wrinkles that have developed, and then hopefully get them back online over the next week or so. The servers affected are:

• CompariMotif
  
• GOPHER
  
• SLiMDisc (now part of SLiMFinder)
  
• SLiMFinder
  
• SLiMSearch
  
• SLiMSearch 2.0
  

These programs (except SLiMSearch 2.0) are available for download. If you have a particular need for any of these servers, please contact me and I will accelerate its re-appearance.

As each server becomes available, it will be posted here.

SLiMSuite servers and programs

An emerging field of biology is the role of intrinsically disordered regions in protein function and, specifically, protein-protein interactions (PPI) [1-2]. Of particular interest, Short, Linear Motifs (SLiMs) playing a vital role in disorder-mediated PPI, acting as ligands for molecular signalling, post-translational modifications and subcellular targeting [3]. SLiMs have extremely compact protein interaction interfaces, generally encoded by less than 4 major affinity-/specificity-determining residues within a stretch of 2-10 residues [4]. Their small size enables high functional density and evolutionary plasticity, which is frequently exploited by rapidly evolving pathogens that use them to hijack cellular processes [5]. These same features also make experimental discovery a challenge and considerable attention has therefore been given to computational methods for SLiM prediction and analysis [6].

A number of these tools have been developed by the Edwards and Shields labs [7-11] and made available as part of the SLiMSuite package and online as webservers (http://bioware.ucd.ie) [9-10,12-14], with two new tools, SLiMPrints and QSLiMFinder, currently in preparation for submission, and SLiMMaker to be added soon. The main tools that form the SLiMSuite package/servers are as follows:

• SLiMFinder [8,13]: de novo SLiM prediction based on a statistical model of over-represented motifs in unrelated proteins.
  
• SLiMDisc [7,12]: de novo SLiM prediction based on heuristic ranking of over-represented motifs in unrelated proteins.
  
• SLiMPred [11]: de novo SLiM/MoRF prediction in single proteins based machine learning of motif attributes.
  
• SLiMSearch [10]: biological context (disorder & conservation) for searches of pre-defined motifs with under- and over-representation statistics, correcting for evolutionary relationships.
  
• SLiMSearch 2.0 [14]: biological context (disorder & conservation) and ranking for proteome-wide searches of pre-defined motifs.
  
• SLiMPrints (in prep.): de novo SLiM/MoRF prediction in single proteins from statistical clustering of conserved disordered residues.
  
• QSLiMFinder (server coming soon): Query-based variant of SLiMFinder with increased sensitivity and specificity.
  
• CompariMotif [9]: Motif-motif comparison tool.
  
• SLiMMaker (coming soon): Simple tool for converting aligned peptides or SLiM occurrences into a regular expression motif.
  
• GOPHER [12]: Automated orthologue prediction and alignment algorithm. Used for conservation-based masking (SLiMFinder/SLiMSearch) and prediction (SLiMPrints).
  
• GABLAM [7] (server coming soon): BLAST-based protein similarity scoring and clustering. Used for SLiMFinder and SLiMSearch adjustments for evolutionary relationships.
  

Personnel (and funding applications) permitting, a number of improvements for these resources are planned, including updates to the underlying databases for proteome-wide predictions (SLiMSearch 1.0 & 2.0), conservation analyses (SLiMSearch 1.0 & 2.0, SLiMPrints, GOPHER) and SLiM comparisons (CompariMotif). We also intend to improve the integration of different tools, allowing seamless continuation of analyses. Motif predictions ((Q)SLiMFinder/SLiMPrints/SLiMPred) will be able to be searched directly against known motifs (CompariMotif) or proteomes (SLiMSearch); GOPHER alignments will be accessible for SLiMPrints analyses and even SLiMSearch/(Q)SLiMFinder input; outputs of motif occurrences ((Q)SLiMFinder/SLiMSearch) can be used to redefine motifs using SLiMMaker etc. If you have any other suggestions for improvements, please let us know.


References:

[1] Tompa P (2011) Unstructural biology coming of age. Curr Opin Struct Biol 21: 419; [2] Babu MM et al. (2011) Intrinsically disordered proteins: regulation and disease. Curr Opin Struct Biol 21:432; [3] Diella F et al. (2008) Understanding eukaryotic linear motifs and their role in cell signaling and regulation. Front Biosci 13:6580; [4] Davey NE et al. (2012) Attributes of short linear motifs. Mol Biosyst 8:268; [5] Davey NE, Trave G & Gibson TJ (2011) How viruses hijack cell regulation. Trends Biochem Sci 36:159; [6] Davey NE, Edwards RJ & Shields DC (2010) Computational identification and analysis of protein short linear motifs. Front Biosci 15:801; [7] Davey NE, Shields DC & Edwards RJ (2006): SLiMDisc: short, linear motif discovery, correcting for common evolutionary descent. Nucleic Acids Res. 34:3546; [8] Edwards RJ, Davey NE & Shields DC (2007): SLiMFinder: A probabilistic method for identifying over-represented, convergently evolved, short linear motifs in proteins. PLoS ONE 2:e967; [9] Edwards RJ, Davey NE & Shields DC (2008): CompariMotif: Quick and easy comparisons of sequence motifs. Bioinformatics 24:1307; [10] Davey NE et al. (2010): SLiMSearch: a webserver for finding novel occurrences of short linear motifs in proteins, incorporating sequence context. Lecture Notes in Bioinformatics 6282:50; [11] Mooney C et al. (2012): Prediction of short linear protein binding regions. J Mol Biol 415:193; [12] Davey NE, Edwards RJ & Shields DC (2007): The SLiMDisc server: short, linear motif discovery in proteins. Nuc Acids Res 35:W455; [13] Davey NE et al. (2010): SLiMFinder: a web server to find novel, significantly over-represented, short protein motifs. Nuc Acids Res 38:W534; [14] Davey NE et al. (2011): SLiMSearch 2.0: biological context for short linear motifs in proteins. Nuc Acids Res 39:W56.