User Manual
Contents
1. start 2500 out of 2500 networks processed u Jul 23 10 14 53 PDT 2015 INFO Motif discovery started Thu Jul 23 10 14 53 POT 2015 INFO Input vertex file home mitra workspace WaRSwapSoftApj Thu Jul 23 10 14 53 POT 2015 INFO Input edge file home mitra workspace WaRSwapSoftApp Thu Jul 23 10 14 53 PDT 2015 INFO Motif size 3 Thu Jul 23 10 15 46 PDT 2015 INFO Randomization and enumeration of subgraphs completed Console area Thu Jul 23 10 15 46 PDT 2015 INFO Waiting for extracting motif information Thu Jul 23 10 15 47 PDT 2015 INFO Motif discovery completed Thu Jul 23 10 15 47 POT 2015 INFO Output files are generated and located at home mitra W 3 21e00 0 0000 7 04e 01 011011002 Results panel 3 13e00 0 00e00 7 09e 01 110020113 2 37e00 0 00e00 4 14e 01 000111103 2 37e00 0 00e00 4 1 4e 01 000001101 nep close Figure 2 The WaRSwapApp main layout 1 Installation and instructions 1 Make sure you have Java jdk installed on your computer 2 Download the software from http megraw cgrb oregonstate edu software WaRS wapSoftwareA pplication 3 Extract the downloaded package to a destination folder 4 Go into the directory in which you extracted the software and run the WaRSwap Software Application as follows a For windows double click on jwarswap jar b Forlinux and mac Open a command line termina2. 01 000111103 os S 2 37200 0 00e00 4 14e 01 000001101 Figure 6 Results browser Results browser Displays graphical representation of the output motifs along with their corresponding significance scores z score and p value Filter results V Z score greaterthan 2 00 W P value less than 0 01 Color options TF E3 MIR E GENE e Self loop B TET Figure 7 Filter options Save button The user can click on this button and specify a file name to save the output motifs into an HTML file The default output HTML file name is set to motifs html in the specified output directory Scoring filter options The user can switch filters on and off and set their threshold values and then click on the Refresh button to display filtered results in the results browser Color options The user can change node type colors in the visualized results using this option Self loops in the motifs are represented by a color different from the three other node types Each of the three node types and the self loop node has a pre defined color The user can assign different colors if desired Click on the color to change the color chooser dialogue will pop up and then select a color to assign to the related node type Cluster version Use the cluster version of the WaRSwap Software Application when the input network is very large running the PC version of the software may
3. E VERTEX FILE NO OF RAND NETWORKS MOTIF SIZE DETECT SELF LOOPS NETWORK NAME an arbitrary string to name the input graph EDGE FILE a valid input edge file VERTEX FILE a valid input vertex file NO OF RAND NETWORKS the number of random networks 2500 is recommended MOTIF SIZE an integer default is 3 DETECT SELF LOOPS TRUE or FALSE X X X X a The results are located in the output directory as follows a A text file named NETWORK NAME motifs out which is a human readable text format file containing output motifs b An HTML file named NETWORK NAME motifs html which is a graphical representation of output motifs Use a web browser to open this file Note load management on available cluster nodes The DRMAA Java application distributes jobs on available nodes which the user has access to If being a good neighbor on your cluster requires you to limit node usage you will need to run the program only on the appropriate queues consult your cluster admin for the advised way to do this on your cluster
4. User Manual About this SOWAT E derit reete coe cccesvevecentendcectancecwtdeadaeveantaesuusaydayedancaccebeaacusevveadccntencsacdsesea ven Download and installation ener ete rrt tnnt tust reet tpa eccoveduansasdenavesssesddeaviesscessveenssestatesens Input Sraph Tears C ER PO cC l Installation and instructions 0 cece eeeceseceseceseceseeeeeeeceeeeseeeseeeaaecaaecsuecsaecaecsseeseeseeessneseneeeaeeeaaeenaes 2 Settna the Opwmons T Input Opt ONS cite tess Pe E re ec ne e as UH o ria ten dan de den Ps OULPUE OPtLOMS EP Motif detection options in ere Hee er PEDE a EERERRL dense laden idea tied eras delenit ies 3 Performing motif dIscOVety n iere e E bins EE REEL sce DU ees IR AER DON EE RECETTE Po exc vo tuens 4 gt Vis alizine the reslis psani i m Cl ster Versi n ermee a e TT E EA A E e EEE EAE A R EEES EEE AE Figure 1 Input graph format example sese eee nee rennen eren reser nennen Figure 2 The WaRSwapApp main layout eseeseeeseeeeeeeeeee eene een ren rennen erinnern nenne Figure 3 Input output options seesseseeeeeeeseeee eene nnne nennen na oea iiis tnit entren ener enne nennen nenne Figure 4 Motif detection options sess nnne tnter enn renn
5. en ersten stes ten nnne Fig re 5 Mott discover progress ivcscsscsecevesscorsseadeoncasea sede cansatessessurcessasuvey N EEEREN TEESE EER ENEE KSERA Pisure 6 ReSults DIOWSED reper abe terret pepper eee tetro vein Ue oce gene issue erede aerae duet bee Ligure 7 Filter OptOnS iiie meer tee Pe aote pr re baee redeo ele pee EE eph eeu pa boves epe o Ue Pe pe HER DTA Ro REA About this software The WaRSwap Software Application WaRSwapApp is a network motif discovery tool for large multi layer biological networks The WaRSwap Software Application is implemented in Java and is available in two versions 1 A standalone PC version for MAC and desktop computers 2 A Cluster version Download and installation The software packages for desktop and cluster versions are available at http megraw cgrb oregonstate edu software WaRS wapSoftwareA pplication index html Input graph features The input graph network is described in two files as follows 1 Vertex file The vertex file is a tab delimited file that should contain one line for each node in the input network each line must contain two items one integer and one string The integer represents the vertex node label and the string represents the vertex node type The following node types are supported TF A transcription factor TF node may have a self loop and may target a microRNA node or a non TF gene node MIR A miRNA node does not have a self loop and may target a TF node
6. l and type cd WaRSwapSoftwareApplication startApplication sh 5 Totest with the existing sample input graph select the edge file and vertex file from the sample inputs directory 6 Change default options if desired otherwise click on the Start button to run the program 7 Wait while program is running It may take a few minutes 8 Find motif discovery output files in given location 2 Setting the options Input output Vertex file WaRSwapSoftApp builds build_1 0 sample_inputs graph vertices txt Edge file ice WaRSwapSoftApp builds build_1 0 sample_inputs graph edges txt G Output directory Mworkspace WaRSwapSoftApp builds build 1 0 motifs output Figure 3 Input output options Input options Edges input toolbox Click the Browse _ button to choose the edge input file Vertex file input toolbox Click the Browse button to choose the vertex input file Output options Output folder The motif discovery results will be saved in the output folder The default path for the output folder is set to the motifs out directory within the current directory which the user can specify different path as desired The output file is named as motifs OUT and will contain human readable plain text most useful for examining results in a text editor Options Motif size 3 VJ Consider self loops No of random networks 2500 Figure 4 Motif detection options Motif detectio
7. n options Sub graph size dropdown menu Using this menu the user can select the motif size The software supports an ultimate number of nodes in a motif however beyond approximately 8 nodes computing time becomes prohibitive even for modestly sized graphs Note that detecting large motifs requires much more time and memory Self loop detection checkbox The WaRSwap Software Application will consider self loops when searching for motifs if this checkbox is selected Number of random networks textbox This integer number is used by the algorithm to generate randomized background networks The default value is set to 2500 background networks and it can be changed as needed Run motif discovery m Start Lo start 2500 out of 2500 networks processed Thu Jul 23 10 14 53 PDT 2015 INFO Motif discovery started Thu Jul 23 10 14 53 PDT 2015 INFO Input vertex file home mitra workspace WaRSwapSoftApy Thu Jul 23 10 14 53 PDT 2015 INFO Input edge file home mitra workspace WaRSwapSoftApp Thu Jul 23 10 14 53 PDT 2015 INFO Motif size 3 Thu Jul 23 10 15 46 PDT 2015 INFO Randomization and enumeration of subgraphs completec Thu Jul 23 10 15 46 PDT 2015 INFO Waiting for extracting motif information Thu Jul 23 10 15 47 PDT 2015 INFO Motif discovery completed Thu Jul 23 10 15 47 PDT 2015 INFO Output files are generated and located at home mitra w ee gt Figure 5 Motif discover progress 3 Performing mo
8. or a non TF gene node GENE A non TF gene node has no targets 2 Edge file The edge file is a tab delimited file in which each line represents a directed edge by identifying the two connected vertex labels For example the line V1 V2 is interpreted as a directed edge from vertex V1 to vertex V2 To specify a bidirectional edge add one edge in each direction An example of an input graph with its corresponding vertex file and edge file representation is shown in Figure 1 1 1 1 1 2 Figure 1 Input graph format example PC version In this section we introduce the user guide for the PC version of the WaRSwapApp Figure 2 shows the main window of the WaRSwapApp oftware Applicat 9 WaRSwap S x M Options Filter results Motif detection a z Motif size 3 im Consider self loops E Z score greater than 2 00 options Score filtering options No of random networks 2500 Ij Pelis less than 0 01 Input output Color options Color options x TF MIR GENE Selfloop Input output Vertex file WaRSwapSoftApp bullds bulld 1 0 sample inputs graph vertices bt mzz J a a D options Edge file ice WaRSwapSoftApp builds build 1 0 sample inputs graph edges bt Ws Refresh save results Output directory vworkspace WaRSwapSoftApp builds build 1 0 motfs output rs Result browser Run motif di Performing the pmet discove if discovery E Z score P value std dev Adj Matrix motif discovery D start
9. take several days to finish The cluster version is built on the DRMAA Java library and can be depolyed on gird engines including Oracle Sun Grid Engine and the GridWay framework which enables sharing of computing resources clusters servers supercomputers etc managed by different distributed resource management DRM systems such as Condor Univa Grid Engine and Son Grid Engine Login into a cluster head machine which can submit jobs to other nodes in the cluster Make sure that you have the drmaa library installed on your cluster http www drmaa org Download the cluster version of the software from the Downloads section Extract the package and change the current directory to the extracted folder and then type Jew Nor cd WaRSwapSoftwareApplication 5 DRMAA settings e Ask your cluster admin about the location of libdrmaa so and drmaa jar files in the cluster e Open startApplication sh file to change the DRMAA settings if needed o Setthe DRMAA LIB PATH variable in startApplication sh to the directory in which libdrmaa so is located the default path points to local cluster sge lib Ix24 amd64 o Save changes in the startApplication sh file o Optional Copy drmaa jar into WaRSwapSoftwareApplication lib directory Note do this step only if the current version of drmaa jar located in WaRSwapSoftwareA pplication lib didn t work on your cluster 6 Run the application startApplication sh NETWORK NAME EDGE FIL
10. tif discovery If you selected all options described in the previous subsections you are now ready to start detecting network motifs Simply click on the Start button in the running motif discovery area of the program The progress bar shows the overall algorithm progress After motif discovery starts a few intermediate files will be generated by the software These files must not be deleted or changed by the user Console area The console window shows messages related to motif search progress This includes any error messages produced by entering invalid options in the user interface errors from a file format problem or the step of the algorithm which is currently running The following errors can occur e Invalid input edge file e Invalid input vertex file e Invalid vertex label e Invalid output path e Incompatible edge and vertex files 4 Visualizing the results When the motif discovery computation finishes successfully then output motifs will be displayed in the results browser Figure 2 The user can use the scoring filter options to select a different cut off score stringency for results presentation The output motifs can be saved in an HTML file by clicking on Save button Result browser Image Z score P Value std dev Adj Matrix gt A A 3 21600 0 00600 7 04e 01 011011002 4 N 3 13600 0 00e00 7 09e 01 110020113 pi 2 37200 0 00e00 4 14e
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