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Landon Stewart
Landon Stewart

Ab Initio Help File Download UPDATED



Go to the GeneMark web site: _download.cgi. Check the boxes for "GeneMark-ES/ET/EP ver 4.61_lic" and "LINUX 64" next to it, fill out the form, then click "I agree". In the next page, right click and copy the two link addresses: "download program" and "64 bit" license, and paste the two link addresses in the commands below. (To be compatible with braker2 version, use the gmes_linux_64.tar.gz file we provided, which is compatible with the braker2 in our docker container. The file is located in /shared_data/genomic_2020/project2/ )




Ab Initio Help File Download



The pipeline always runs "ab initio gene prediction" step in regions with no genes predicted by other methods (using known mRNAs or known proteins), therefore it is not to set up in configuration file.


2) gene models predicted using known proteins from NR (or its subset, e.g.,eukaryotic part of NR)This corresponds to "USE_PROTEINS" block in configuration file."prot_map" (default) method predicts gene models using combination of prot_map and Fgenesh+, with additional selection of reliable models through blast2 alignments between predicted and homologous proteins.First, 'prot_map' maps known proteins from a protein database (for example, NR or its subset) to genomic sequences and good mappings are selected.Then 'fgenesh+' program predicts gene models in regions of good mappings using mapped proteins.After that predicted gene models are additionally checked / filtered by script that analyses blast2 (bl2seq) alignments between predicted and homologous proteins. Only gene models that have good coverage of predicted and homologous proteins by blast alignment are selected. Some other criteria are also checked."BLAST" (alternative) method first predicts genes ab initio (by fgenesh), then finds homologs to predicted proteins in a database (by BLAST) and then tries to refine gene models (by fgenesh+) using protein homologs found.We recommend to use "prot_map" method because it is more straightforward and gives higher accuracy in our tests while our "BLAST" method uses some heuristics to merge genes if they got split when predicted ab initio.If you want to use protein-supported (as we call them) predictions, switch ON "USE_PROTEINS" block in configuration file.For example,


3) Ab initio predictions (without mRNA or protein type of evidence) are made in regions not occupied by mRNA-supported and protein-supported predictions.To make ab initio predictions, we use 'fgenesh' and gene prediction parameterstrained for specified (or close) organism.The pipeline always runs ab initio predictions (in regions with no genespredicted by other methods) therefore it is not to set up in configuration file.


If "prediction of genes based on homology to known proteins" step is used then NR (or other protein database) is required as well as BLAST+or BLAST software.BLAST+ can be downloaded from NCBI ftp or web page: +/LATEST/ =Web&PAGE_TYPE=BlastDocs&DOC_TYPE=DownloadThe legacy BLAST executables can be downloaded from NCBI ftp: Use BLAST+ or BLAST release 2.2.13 or some higher version.NR (non-redundant protein sequence database) can be downloaded from NR or custom protein database must be present in directory provided in configuration file in both formats - as FASTA file and as formatted for BLAST by 'makeblastdb' or 'formatdb' program.Format protein database for BLAST with "makeblastdb -in -dbtype prot" (BLAST+) or "formatdb -i " (BLAST) command, e.g.:


Two more fields are added in comparison with ab initio predictions:(1) - coordinates of that part of homologous protein that corresponds to predicted CDS;(2) - homology in % between predicted CDS and corresponding part of homologous protein.Predicted proteins are listed at the end of *.resn3 files.For mRNA supported and protein supported predictions information about a homolog to a predicted protein is given in ID line of a predicted protein (after first ##),for example:


We have developed a collection of PDF files that provide detailedexamples of how to complete the various tasks involved in thedata-capture process. All of these tutorials include "screen shots"to familarize you with the program. They cover such operations asdownloading and installing the software, capturing bibliographicinformation, and specifying compounds and properties to be captured.Other help files illustrate data capture for specific properties.This collection of HELP files will be expanded over time to meet theneeds of the data community.


geneid is a program to predict genes in anonymous genomic sequencesdesigned with a hierarchical structure. In the first step, splice sites, startand stop codons are predicted and scored along the sequence usingPosition Weight Arrays (PWAs). In the second step, exons are built from the sites.Exons are scored as the sum of the scores of the defining sites, plus the thelog-likelihood ratio of a Markov Model for coding DNA. Finally, from the set of predicted exons,the gene structure is assembled, maximizing the sum of the scores of the assembled exons. geneidoffers some type of support to integrate predictions from multiple source via external gfffiles and the redefinition of the general gene structure or model is also feasible.The accuracy of geneid compares favorably to that of other existing tools, butgeneid is likely more efficient in terms of speed and memory usage.Currently, geneid v1.2 analyzes the whole human genome in 3 hours (approx. 1 Gbp / hour)on a processor Intel(R) Xeon CPU 2.80 Ghz.


  • geneid accuracy compares to that of other existing"ab initio" gene prediction tools.

  • geneid is very efficient in terms of speed and memory usage. Inpractice, geneid can analyze chromosome size sequences at a rate ofabout 1 Gbp per hour on the Intel(R) Xeon CPU 2.80 Ghz. For the largesthuman chromosome (chr1), it requires 1/2 Gbyte of RAM plus the size of the Fastasequence..

  • geneid offers support to integrate predictions from multiple sources(ESTs, blast HSPs) and to reannotate genomic sequences, via external gff filesand together with the redefinition of the "gene model".

  • geneid output can be customized to different levels ofdetail, including exhaustive listing of potential signals and exons. Furthermore,several output formats as gff or XML are available.

  • There are available parameter files in geneid v 1.2 for Drosophila Melanogaster,human (which can be also used for vertebrate genomes), Dictyostelium discoideumand Tetraodon nigroviridis (which can be used for Fugu rubripes) among many others for species spanning the four "classical" kingdoms. The additional currently available parameter files can be found under the section "geneid parameter files" .



  • geneid v 1.4.4 (current development version):geneid v 1.4.4 full distribution: source code and documentation(documentation does not yet reflect new features; for help, type geneid -h)[DOWNLOAD]

Note: Please, verify the check-sum file valueType: md5sum geneid_v1.4.4.Jan_13_2011.tar.gz-> 05c00f283a8fa996418aff0bc8db1c6d


  • geneid v 1.4.4 full distribution: source code and documentation(documentation does not yet reflect new features; for help, type geneid -h)[DOWNLOAD]

Note: Please, verify the check-sum file valueType: md5sum geneid_v1.4.4.Jan_13_2011.tar.gz-> 05c00f283a8fa996418aff0bc8db1c6d


  • geneid v 1.3 preview release 3 (version used for NGASP phase II category 4):geneid v 1.3 full distribution: source code and documentation(documentation does not yet reflect new features; for help, type geneid -h)[DOWNLOAD]

Note: Please, verify the check-sum file valueType: md5sum geneid_v1.3.Mar_30_2007.tar.gz-> 10cad4e6ae25a57fcc6bb062692626ae


  • geneid v 1.3 preview release 1 (version used for NGASP phase I category 1):geneid v 1.3 full distribution: source code and documentation(documentation does not yet reflect new features; for help, type geneid -h)[DOWNLOAD]

Note: Please, verify the check-sum file valueType: md5sum geneid_v1.3.Dec_21_2006.tar.gz-> 1ff0f870e5ec5a553e4603102a9d7c62


geneid has been trained on several species and it is being trainedon other genomes as well. See this helpfor more details about the different parts of parameter files as well as their statistical meaning.- - The parameter files for geneid v 1.2 are not compatible with previous versions - -- - The parameter files for geneid v 1.3 and 1.4 are not back-compatible with previous versions, however, version 1.2 parameter files ARE forward-compatible with version 1.3 and 1.4 - -


Use the steps in this section to download and install the Amazon Redshift ODBC drivers on a supported Linux distribution. The installation process installs the driver files in the following directories:


Use the steps in this section to download and install the Amazon Redshift ODBC driver on a supported version of macOS X. The installation process installs the driver files in the following directories:


  • A space group is identified by its unique sequential number. For the crystallographic space groups, this index is a number in the range of [1,230]. For the magnetic space groups, depending on the notation (BNS or OG) it can consist of two numbers (in the case of BNS) or three numbers (OG). Structure Data Converter & Editor program uses the BNS notation ("###.###" format - the first index being the corresponding Federov space group index; the second being the overall index, i.e. [1,1651]) to identify the magnetic space groups.File types>> InputThe Structure Data Converter & Editor program accepts input data in one of the following file formats: BCS: The Bilbao Crystallographic Server (BCS) file format is the standard format used throughout the server's tools. It contains the space-group, lattice and sites information (for the asymmetric unit shell) assumed to be given in standard setting (one can use our SETSTRU tool to convert to other settings). As of the moment, the occupational and magnetic information are not supported.

  • CIF: The Crystallographic Information File format is developed by the International Union of Crystallography and is a widely used, standard-assumed file format. Although it has many supported tags for defining additional structural information, unfortunately a consensus on the representation of magnetic information hasn't been reached yet.

  • mCIF: As the ISOCIF program, developed by Harold T. Stokes and Branton J. Campbell started supporting magnetic space groups and magnetic moment information, Stokes and Campbell extended the CIF dictionaries by adding magnetic related tags such as "_magnetic_space_group_BNS_number", "_magnetic_space_group_symop_operation_timereversal", "_magnetic_atom_site_moment_crystalaxis_mx", etc.. To discern this extended CIF file, they also relabeled the existing tags like "_magnetic_cell_length_a", "_magnetic_space_group_symop_operation_xyz" and thus the mCIF format came into being. Although one can store all magnetic related information to a mCIF file, its -for the moment- incompatibility with most of the crystallographic software makes it difficult to import the magnetic data contained within.

  • VESTA: Developed by Koichi Momma, VESTA is a highly advanced, yet simple to use 3D visualization program for structural data. Even though it has no direct support for magnetic space groups / magnetic moments, nevertheless they can be represented by assigning vectors to atomic sites.

  • VASP: The Vienna Ab initio Simulation Package, developed by Jürgen Hafner, Georg Kresse, Doris Vogtenhuber & Martijn Marsman, is mainly an ab-initio calculation software, accepting its structure input data in P1. Currently our Structure Data Converter & Editor tool only supports the POSCAR/CONTCAR files with "Direct/Fractional" atomic coordinates.


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