Download HITS Txt

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Download HITS txt

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Alternatively you can also use a docker / singularity container to run OMA standalone in any environment that allows running containers. You need to bind mount the folder with your dataset into the docker's /oma path, i.e. assuming you want to run the ToyExample with the genomes in /tmp/OMA/ToyExample/DB/*fa, you would need to execute the following command to download and execute OMA standalone:

Additionally it is possible to export the precomputed all-against-all for any of the >2000 genomes currently in the oma database. This can result in a massive speedup of time to run omastandalone. To export genomes, go to and select the genomes you wish to include in your omastandalone run. The resulting compressed tar file should be downloaded and uncompressed in the root directory of your analysis. Then simply run omastandalone as normal.

ESPRIT stores its output files in a directory calledEspritOutput in your working directory. The output consists of three text files and one tarball. In the tarball, FASTA files with the MSAs of the hits ESPRIT found are stored. The other three files are explained in detail in Table 2.

All hits found by ESPRIT are listed in this file. It is a list of contigs, ordered according to their position relative to the putative ortholog. Each line describes one contig, the fields are separated by tabs. In the first field, the fragment pair ID is printed; the next two fields contain the labels of the first and second fragments found in this hit. The forth and fifth fields contain the label of the corresponding full gene and its genome name. Then follows the distance difference between the two fragments and the number of positions between them (i.e. the gap); at last, an array is listed containing the IDs of all s3 genes corresponding to this hit.

ESPRIT often detects more candidate pairs than it will list in the hits.txt file, but not all of them survive the quality check. Still, if you want to see which triplets have been filtered out, have a look at dubious.txt where they are still listed. The file format is the same as for hits.txt.

As we noted in a previous blog post, the default configuration for SRA-Toolkit will store temporary files generated during sequence download in your home directory. Since your home space is just 100GB, we need to change it to a more suitable location.

The standard way of obtaining the latest main annotation, containing: GO, KEGG, Pfam, GSEA, Keywords, CORUM and many other terms found in UniProt is by downloading the mainPerseusAnnot.txt.gz file from dropbox. This is an easy four step process:

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End of byte range to use for downloading a section of the file. If --end-range is given, --start-range must be provided. The --start-range and --end-range params are inclusive. Ex: --start-range=0, --end-range=511 will download first 512 bytes of file.

Start of byte range to use for downloading a section of the file. If no --end-range is given, all bytes after the --start-range will be downloaded. The --start-range and --end-range params are inclusive. Ex: --start-range=0, --end-range=511 will download first 512 bytes of file.

Note that the -evalue option sets the significance threshold for reporting hits. This can be modified depending on how stringent/permissive you would like to be with your search. There are 5027 proteins in the Salmonella file, so this will run 5027 separate BLAST searches. The -num_threads option tells the program to use multiple cores (in this case 4) to make the search go a little faster. It should take about 1 min. For more information on BLAST settings you can type: blastp -help

And then make an XY scatter plot showing the locations of the BLASTN hits in the two genomes with the following command. Note that the cex options simply sets the size of the points. We will save the plot to a PDF file by calling pdf() and the closing the file with dev.off(). The output should look like the image below. To view the output PDF file you will neen to transfer my_dotplot.pdf to your own computer with Cyberduck.

Each of these scripts will attempt to download information from various sources using wget to fetch files over your internet connection. Most of it comes from NCBI Gene Database and the UCSC Genome Browser, but other sources are included as well. The organisms, genomes, etc. that are incorporated are determined by initial manifest tables that are provided as the primary input file to each of the commands. Examples are in the update/ directory and described in greater detail below. In each case, the update programs will download the appropriate data, parse it and perform any initial data organization or manipulation that is necessary, and then automatically autoconfigure the data for use with HOMER's configuration management. It will then be ready to use with the rest of HOMER.

Gene identifiers are build around the NCBI Gene Database, which depending on your point of view is one of the more complete databases of information on gene accession information available across a wide range of species. The script will basically raid all of the files on the NCBI Gene FTP site ( ) and process them to create ID conversion tables for each of the organisms in the input manifest file (i.e. taxids.tsv). It will also download the primary uniprot data files( _release/knowledgebase/complete/).

The most resource intensive aspect of the updateGeneIdentifiers.pl script is the time it takes to download the uniprot/trembl data files and parse them. The script that does this is relatively inefficient and uses up to 30Gb of RAM. Downloading the file itself can also take several hours - if you download it once and leave it in the update/ directory, the program will NOT download it again if it finds it. This can save time... 041b061a72