We are not affiliated with Facepunch, please don't ask things only the developers can do here.(which also apply to Discord)Interested in learning how to mod?Good! Modding is an easy and fun gateway into a wonderful world called programming you won't regret entering.If you're completely new to programming, head over to Khan Academy and take their awesome programming course:.If this isn't your first rodeo, but you need some help getting started with GLua specifically, here are some resources to get started:.A more complete and accurate list of rules may be found.Thanks to and for letting us use some css snippets of theirs. Are you using a save or a duplication? If you're hitting save to preserve your contraptions, sorry bud, but you're doing it wrong.You'll want to use duplications instead.Step one is to load up the save for your contraption and make sure that everything works. Also, make sure everything is welded/roped/whatevered together.
Then, from your tools menu, select the duplication tool. Copy your contraption, then paste it somewhere. Make sure the duplicate that you pasted is working. Once you're happy with your thingy, use the duplicator tool to copy your working model. Go to the 'dupes' category in the spawn menu, go to 'my dupes', and click 'save dupe'.
It will save whatever you copied.The advantages of using dupes for your contraptions instead of saves are extensive. First off, saves have been around since the days of DOOM(1993), and are not guaranteed to keep all your binds working. Also, when you load a save, all the enemies and things you've built in the map are cleared and only the thing you've built comes up, which can be a pain if you want to use your contraption to fight something you've already spawned in and set up. Dupes, on the other hand, are designed just with contraptions, buildings, and the like in mind, and will keep your binds functional, not disturb the rest of the map, and best (or worst) of all, can be spawned multiple times in multiple places (the 'worst' part being that on servers, it's too easy to spam laggy duplications, unless the server disabled all dupes).TL;Won't Read The Rest: Use the duplicator tool on your contraptions, rather than saving them.Now, all that doesn't mean saves are useless. You can use saves to construct level/scenario all around the map, complete with NPCS, weapons, buildings you made, and even objectives/goals if you're feeling crafty.
Contents.About MAKERMAKER is an easy-to-use genome annotation pipeline designed for small research groups with little bioinformatics experience. However, MAKER is also designed to be scalable and is thus appropriate for projects of any size including use by large sequence centers. MAKER can be used for de novo annotation of newly sequenced genomes, for updating existing annotations to reflect new evidence, or just to combine annotations, evidence, and quality control statistics for use with other GMOD programs like, and.MAKER has been used in many genome annotation projects:.
Schmidtea mediterranea - planaria (A Alvarado, Stowers Institute). Pythium ultimum oomycete (R Buell, Michigan State Univ.). Pinus taeda - Loblolly pine (A Stambolia-Kovach, Univ. California Davis). Atta cephalotes - leaf-cutter ant (C Currie, Univ. Wisconsin, Madison).
A more advanced way is to create your own animations with the SDK and filming them in the game. I'm not entirely sure how to do this, and I recommend the stop-motion technique if you're just starting out on Gmod video making. If you want to leave Ijat a tip for writing this Garrys Mod guide you can do so here. Garrys Mod Walkthrough 6.1 - Saving Own Dupes - Save Custom Made Dupes. How to Build a Car in Gmod By Tom Kantain; Updated September 15, 2017. The world of Garry's Mod is wonderfully free of the real-life needs that drive us to build vehicles to get around. In Gmod, you can move around as fast as you like without a vehicle, and your feet don't get tired. Ultimately, the only reason to drive a vehicle in Gmod is.
Linepithema humile - Argentine ant (CD Smith, San Francisco State Univ.). Pogonomyrmex barbatus - red harvester Ant (J Gadau, Arizona State Univ.). Conus bullatus - cone snail (B Olivera Univ. Utah). Petromyzon marinus - Sea lamprey (W Li, Michigan State). Fusarium circinatum - pine pitch canker (B Wingfield, Univ.
Pretoria) - Manuscript in preparation. Cardiocondyla obscurior - tramp ant (J Gadau, Arizona State Univ.) - Manuscript in preparation. Columba livia - pigeon (M Shapiro, Univ. Utah) - Manuscript in preparation. Megachile routundata alfalfa leafcutter bee - Manuscript in preparation. Latimeria menadoensis - african coelacanth -.
Nannochloropsis - micro algae (SH Shiu, Michigan State Univ.). Arabidopsis thale cress re-annotation (E Huala, TAIR) - Manuscript in preparation. Cronartium quercuum - rust fungus (JM Davis, Univ.
Florida) - Annotation in progress. Ophiophagus hannah - King cobra (T. Castoe, Univ. Colorado) - Annotation in progress. Python molurus - Burmese python (T. Castoe, Univ.
Colorado) - Annotation in progress. Lactuca sativa - Lettuce (RW Michelmore) - Annotation in progress. parasitic nematode genomes (M Mitreva, Washington Univ). Diabrotica virgifera - corn rootworm beetle (H Robertson, Univ.
Illinois). Oryza sativa - rice re-annotation (R Buell, MSU). Zea mays - maize re-annotation (C Lawrence, MaizeGDP). Cephus cinctus - wheat stem sawfly (H Robertson, Univ. Illinois).
Rhagoletis pomonella - apple maggot fly (H Robertson, Univ. Illinois)Introduction to Genome Annotation What Are Annotations?Annotations are descriptions of different features of the genome, and they can be structural or functional in nature.Examples:. Structural Annotations: exons, introns, UTRs, splice forms. Functional AnnotationsIt is especially important that all genome annotations include an evidence trail that describes in detail the evidence that was used to both suggest and support each annotation. This assists in curation, quality control and management of genome annotations.Examples of evidence supporting a structural annotation:. Ab initio gene predictions. Transcribed RNA (mRNA-Seq/ESTs/cDNA/transcript).
ProteinsImportance of Genome AnnotationsWhy should the average biologist care about genome annotations? Genome project from sequencing to experimental application of annotationsGenome sequence itself is not very useful. The first question that occurs to most of us when a genome is sequenced is, 'where are the genes?' To identify the genes we need to annotate the genome.
And while most researchers probably don't give annotations a lot of thought, they use them everyday.Examples of Annotation Databases:.Every time we use techniques such as RNAi, PCR, gene expression arrays, targeted gene knockout, or ChIP we are basing our experiments on the information derived from a digitally stored genome annotation. If an annotation is correct, then these experiments should succeed; however, if an annotation is incorrect then the experiments that are based on that annotation are bound to fail. Which brings up a major point:. Incorrect and incomplete genome annotations poison every experiment that uses them.Quality control and evidence management are therefore essential components to the annotation process.Effect of NextGen Sequencing on the Annotation ProcessIt’s generally accepted that within the next few years it will be possible to sequence even human sized genomes for as little as $1,000. As costs have drop, read lengths have increased, and assembly and alignment algorithms have matured, the genome project paradigm is shifting. Even small research groups are turning their focus from the individual reference genome to the population.
This shift in focus has already lead to great insights into the genomic effects of domestication and is very promising in helping us understand multiple host-pathogen relationships. Importantly, these population-based studies still require a well-annotated reference genome. MAKER-generated annotations, shown inWhat sets MAKER apart from other tools ( ab initio gene predictors etc.)?MAKER is an annotation pipeline, not a gene predictor. MAKER's performance on the S. Mediterranea emerging model organism genome.
MAKER can be downloaded from:. but it should already be on the imageMAKER is already installed on the Amazon Machine Image that we will be using today, so let's start an instance of that AMI.You will see the names of a number of MAKER supported executables as well as the path to their location. If you followed the installation instructions correctly, including the instructions for installing prerequisite programs, all executable paths should show up automatically for you. However if the location to any of the executables is not set in your PATH environment variable, as per installation instructions, you will have to add these manually to the makerexe.ctl file every time you run MAKER.Lines in the MAKER control files have the format key=value with no spaces before or after the equals sign(=). If the value is a file name, you can use relative paths and environment variables, i.e. Note that for all control files the comments written to help users begin with a pound sign(#).
In addition, options before the equals sign(=) can not be changed, nor should there be a space before or after the equals sign.Now let's take a look at the makerbopts.ctl file.nano makerbopts.ctlIn this file you will find values you can edit for downstream filtering of BLAST and Exonerate alignments. At the very top of the file you will see that I have the option to tell MAKER whether I prefer to use WU-BLAST or NCBI-BLAST. We want to set this to NCBI-BLAST, since that is what is installed. We can just leave the remaining values as the default.blasttype=ncbi+Now let's take a look at the makeropts.ctl file.nano makeropts.ctlThis is the primary configuration file for MAKER specific options. Here we need to set the location of the genome, EST, and protein input files we will be using. These come from the supplied example files. If you are following this in class you can replace the makeropts.ctl file with the opts.txt.
We also need to set repeat masking options, as well as a number of other configurations. We'll discuss these options in more detail later on. If you are following this tutorial outside of class adjust the following values in a text editor.cp opts.txt makeropts.ctlorgenome=dppcontig.fastaest=dpptranscripts.fastaprotein=dppproteins.fastaest2genome=1Note: Do not put spaces on either side of the = on the above control file lines.Now let's run MAKER.makerYou should now see a large amount of status information flowing past your screen. If you don't want to see this you can run MAKER with the -q option for 'quiet' on future runs.Details of What is Going on Inside of MAKER Repeat MaskingThe first step in the MAKER pipeline is repeat masking. Why do we need to do this? Repetitive elements can make up a significant portion of the genome. These repeats fall into to basic classes:.
Low-complexity (simple) repeats: These consist of stretches (sometimes very long) of tandemly repeated sequences with little information content. Examples of low-complexity sequence are mononucleotide runs (AAAAAAA, GGGGGG) and the various types of satellite DNA. Interspersed (complex) repeats - Sections of sequence that have the ability to change thier location within the genome.
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These transposons and retrotransposons contain real coding genes (reverse transcriptase, Gag, Pol) and have the ability to transpose (and often duplicate) surrounding sequence with them.The low information content of the low complexity repeats sequence can produce sequence alignments with high statistical significance to low-complexity protein regions creating a false homology (think evidence for genes) throughout the genome.Because these complex repeats contain real protein coding genes they play havoc with ab initio gene predictors. For example, a transposable element that occurs within the intron of one of the organism's own protein encoding genes might cause a gene predictor to include extra exons as part of this gene. Thus, sequence which really only belongs to a transposable element is included in your final gene annotation set.Analysis of the repeat structure of a new genome is an important goal, but the presence of those repeats both simple and complex makes it nearly impossible to generate a useful annotation set of the organisms own genes. For this reason it is critical to identify and mask these repetitive regions of the genome. Identify and mask repetitive elementsMAKER identifies repeats in two steps. First MAKER runs a program called RepeatMasker is used to identify both all classes of repeats that match entries in the RepBase repeat library.
You can even create your own species specific repeat library and RepeatMasker use it in addition to its own libraries to mask repeats based on nucleotide repeats libraries. Next MAKER uses RepeatRunner to identify transposable elements and viral proteins using the RepeatRunner protein database. Because RepeatRunner uses protein sequence libraries and protein sequence diverges at a slower rate than nucleotide sequence, this step picks up many problematic regions of divergent repeats that are missed by RepeatMasker (which searches in nucleotide space).Regions identified during repeat analysis are masked out in two different ways:. Complex repeats are hard-masked - the repeat sequence is replaced with the letter N. This essentially removes this sequence from any further consideration at any later point of the annotation process. Simple repeats are soft-masked - sequences are transformed to lower case. This prevents alignment programs such as Blast from seeding any new alignments in the soft-masked region, however alignments that begin in a nearby (non-masked) region of the genome can extend into the soft-masked region.
This is important because low-complexity regions are found within many real genes, they just don't make up the majority of the gene.Masking sequence from the annotation pipeline (especially hard masking) may seem like it might cause us to lose real protein coding genes that are important for the organism's biology. It is true that repeat derived genes can be co-opted and expressed by the organism and repeat masking will affect our ability to annotate these genes. However, these genes are rare and the number of gene models and sequence alignments improved by the repeat masking step far outweighs the few gene models that may be negatively affected.
You do have the option to run ab initio gene predictors on both the masked and unmasked sequence if repeat masking worries you though. You do this by setting unmask:1 in the makeropt.ctl configuration file.Ab Initio Gene PredictionFollowing repeat masking, MAKER runs ab initio gene predictors specified by the user to produce preliminary gene models. Ab initio gene predictors produce gene predictions based on underlying mathematical models describing patterns of intron/exon structure and consensus start signals. Because the patterns of gene structure are going to differ from organism to organism, you must train gene predictors before you can use them. Align EST and protein evidenceRemember now that we are aligning against the repeat-masked genomic sequence.
How is this going to affect our alignments? For one thing we won't be able to align against low-complexity regions. Some real proteins contain low-complexity regions and it would be nice to identify those, but if I let anything align to a low-complexity region, then I will get spurious alignments all over the genome.
Wouldn't it be nice if there was a way to allow BLAST to extend alignments through low-complexity regions, but only if there is is already alignment somewhere else? You can do this with soft-masking. If you remember soft-masking is using lower case letters to mask sequence without losing the sequence information. BLAST allows you to use soft-masking to keep alignments from seeding in low-complexity regions, but allows you to extend through them. This of course will allow some of the spurious alignments you were trying to avoid, but overall you still end up suppressing the majority of poor alignments while letting through enough real alignments to justify the cost.
You can turn this behavior off though if it bothers you by setting softmask=0 in the makerbopt.ctl file.Polishing Evidence AlignmentsBecause of oddities associated with how BLAST statistics work, BLAST alignments are not as informative as they could be. BLAST will align regions any where it can, even if the algorithm aligns regions out of order, with multiple overlapping alignments in the exact same region, or with slight overhangs around splice sites.To get more informative alignments MAKER uses the program Exonerate to polish BLAST hits. Exonerate realigns each sequences identified by BLAST around splice sites and forces the alignments to occur in order. The result is a high quality alignment that can be used to suggest near exact intron/exon positions. Polished alignments are produced using the est2genome and protein2genome options for Exonerate. Polish BLAST alignments with ExonerateOne of the benefits of polishing EST alignments is the ability to identify the strand an EST derives from.
Because of amplification steps involved in building an EST library and limitations involved in some high throughput sequencing technologies, you don't necessarily know whether you're really aligning the forward or reverse transcript of an mRNA. However, if you take splice sites into account, you can only align to one strand correctly.Integrating Evidence to Synthesize AnnotationsOnce you have ab initio predictions, EST alignments, and protein alignments you can integrate this evidence to produce even better gene predictions. MAKER does this by communicating with the gene prediction programs. MAKER takes all the evidence, generates 'hints' to where splice sites and protein coding regions are located, and then passes these 'hints' to programs that will accept them.
Pass gene finders evidence-based ‘hints’MAKER produces hint based predictors for:. SNAP. Augustus. FGENESH.
GeneMark (under development)Selecting and Revising the Final Gene ModelMAKER then takes the entire pool of ab initio and evidence informed gene predictions, updates features such as 5' and 3' UTRs based on EST evidence, tries to determine alternative splice forms where EST data permits, produces quality control metrics for each gene model (this is included in the output), and then MAKER chooses from among all the gene model possibilities the one that best matches the evidence. This is done using a modified sensitivity/specificity distance metric. Compute support for each portion of the gene model MAKER's OutputIf you look in the current working directory, you will see that MAKER has created an output directory called dppcontig.maker.output. This example did not work during class because a conflict with the version of Apache that was installed.
The issue has since been fixed. Before beginning the example, open a terminal and remove the following files otherwise the subversion update of maker fails.rm /Documents/Software/maker/MWAS/bin/mwasserverrm /Documents/Software/maker/MWAS/cgi-bin/tttemplates/apollowebstart.ttThen update maker via subversion.svn update /Documents/Software/maker/The MWAS interface provides a very convenient method for running MAKER and viewing results; however, because compute resources are limited users are only allowed to submit a maximum of 2 megabases of sequence per job. So while MWAS might be suitable for some analyses (i.e. Annotating BACs and short preliminary assemblies), if you plan on annotating an entire genome you will need to install MAKER locally.
But if you like the convenience of the MWAS user interface, you can optionally install the interface on top of a locally installed version of MAKER for use in your own lab.First under the maker directory there is a subdirectory called MWAS. MWAS contains all the needed files to build the MAKER web interface.
The maker/MWAS/bin/mwasserver file is used to setup and run this web interface. Let's configure that now. There are three steps to setting up the server. First you must create and edit a server configuration file, then load all other configuration files, and then install all files to the appropriate web accessible directory.cd /home/gmod/Documents/Software/maker/MWAS/bin/mwasserver PREPThis will create a file in /maker/MWAS/config/ called server.ctl. We will need to edit this file before continuing.nano config/server.ctlSet:apacheuser:www-datawebaddress:we need to generate other settings that are dependent on the values inserveropts.ctl.bin/mwasserver CONFIGSeveral new configuration files should now be loaded in the config/ directory. These new files define default MAKER options for the server and the location of files for the server dropdown menus.makerbopts.ctlmakerexe.ctlmakeropts.ctlmenus.ctlWe shouldn't need to edit any of these file.
So let's copy files to the appropriate web accessible directories. This must be done as root or using sudo.sudo bin/mwasserver SETUPIf you set APOLLOROOT in the server.ctl file, then you can now setup a special Java Web Start version of to view results directly from the web interface.
Web Start will be described in more detail in the Apollo session.