Home_Icon Learning Center Home

MAKER Genome Annotation using cc-tools and Jetstream(WQ-MAKER)

Part 3: Set up a MAKER run using the Terminal window. Instead IF you want to run the WQ-MAKER using Jupyter notebook please see the section below

Step 1: Navigate to the mounted volume.

Once you have logged in to your instance using webshell or ssh of your MASTER instance, you must change the directory permissions as below

#Change the ownership and group permission on the mount location
$ sudo chown -hR $USER /vol_b
$ sudo chgrp -hR $USER /vol_b

# cd into the /vol_b and then run WQ-MAKER in there
$ cd /vol_b

Step 2: Get oriented. You will find staged example data in “/opt/WQ-MAKER_example_data/” within the MASTER instance. List its contents with the ls command:

$ ls /opt/WQ-MAKER_example_data/
maker_bopts.ctl  maker_exe.ctl  maker-hosts  maker_opts.ctl  test_data  worker-launch.yml

$ ls /opt/WQ-MAKER_example_data/test_data
mRNA.fasta  msu-irgsp-proteins.fasta  Os-rRNA.fa  plant_repeats.fasta  test_genome_chr1.fasta  test_genome.fasta

2.1 maker_*.ctl file are a set of configuration files that can be used for this exercise or generated as described below.

2.2 worker-launch.yml and maker-hosts are ansible-playbook and host file for luanching jobs on WORKERS (optional for WQ-MAKER)

2.3 fasta files include a scaled-down genome (test_genome.fasta) which is comprised of the first 300kb of 12 chromosomes of rice and scaled-down genome (test_genome_chr1.fasta) which is comprised of the first 300kb of first chromosome of rice

2.4 mRNA sequences from NCBI (mRNA.fasta)

2.5 publicly available annotated protein sequences of rice (MSU7.0 and IRGSP1.0) - msu-irgsp-proteins.fasta

2.6 collection of plant repeats (plant_repeats.fasta)

2.7ribosomal RNAsequence of rice (Os-rRNA.fa)

Executables for running MAKER are located in /opt/maker/bin and /opt/maker/exe:

As the names suggest the “/opt/maker/bin” directory includes many useful auxiliary scripts. For example cufflinks2gff3 will convert output from an RNA-seq analysis into a GFF3 file that can be used for input as evidence for WQ-MAKER. RepeatMasker, augustus, blast, exonerate, and snap are programs that MAKER uses in its pipeline. We recommend reading MAKER Tutorial at GMOD for more information about these.

Step 3: Set up a WQ-MAKER run. Create a working directory called “maker_run” on your home directory using the mkdir command and use cd to move into that directory:

# Navigate to the mounted volume for creating test directory
$ cd /vol_b
$ mkdir wq_maker_run
$ cd wq_maker_run

Step 4: Copy the contents of “WQ-MAKER_example_data” into the current directory using cp -r command. Verify using the ls command. Change the permissions on that directory

$ sudo cp -r /opt/WQ-MAKER_example_data/test_data .

Step 5: Run the maker command with the –help flag to get a usage statement and list of options:

$ maker -h
Argument "2.53_01" isn't numeric in numeric ge (>=) at /usr/local/lib/x86_64-linux-gnu/perl/5.22.1/ line 1570.
MAKER version 2.31.9
 maker [options] <maker_opts> <maker_bopts> <maker_exe>
 MAKER is a program that produces gene annotations in GFF3 format using
 evidence such as EST alignments and protein homology. MAKER can be used to
 produce gene annotations for new genomes as well as update annotations
 from existing genome databases.
 The three input arguments are control files that specify how MAKER should
 behave. All options for MAKER should be set in the control files, but a
 few can also be set on the command line. Command line options provide a
 convenient machanism to override commonly altered control file values.
 MAKER will automatically search for the control files in the current
 working directory if they are not specified on the command line.
 Input files listed in the control options files must be in fasta format
 unless otherwise specified. Please see MAKER documentation to learn more
 about control file  configuration.  MAKER will automatically try and
 locate the user control files in the current working directory if these
 arguments are not supplied when initializing MAKER.
 It is important to note that MAKER does not try and recalculated data that
 it has already calculated.  For example, if you run an analysis twice on
 the same dataset you will notice that MAKER does not rerun any of the
 BLAST analyses, but instead uses the blast analyses stored from the
 previous run. To force MAKER to rerun all analyses, use the -f flag.
 MAKER also supports parallelization via MPI on computer clusters. Just
 launch MAKER via mpiexec (i.e. mpiexec -n 40 maker). MPI support must be
 configured during the MAKER installation process for this to work though
 -genome|g <file>    Overrides the genome file path in the control files
 -RM_off|R           Turns all repeat masking options off.
 -datastore/         Forcably turn on/off MAKER's two deep directory
  nodatastore        structure for output.  Always on by default.
 -old_struct         Use the old directory styles (MAKER 2.26 and lower)
 -base    <string>   Set the base name MAKER uses to save output files.
                     MAKER uses the input genome file name by default.
 -tries|t <integer>  Run contigs up to the specified number of tries.
 -cpus|c  <integer>  Tells how many cpus to use for BLAST analysis.
                     Note: this is for BLAST and not for MPI!
 -force|f            Forces MAKER to delete old files before running again.
                     This will require all blast analyses to be rerun.
 -again|a            recaculate all annotations and output files even if no
                     settings have changed. Does not delete old analyses.
 -quiet|q            Regular quiet. Only a handlful of status messages.
 -qq                 Even more quiet. There are no status messages.
 -dsindex            Quickly generate datastore index file. Note that this
                     will not check if run settings have changed on contigs
 -nolock             Turn off file locks. May be usful on some file systems,
                     but can cause race conditions if running in parallel.
 -TMP                Specify temporary directory to use.
 -CTL                Generate empty control files in the current directory.
 -OPTS               Generates just the maker_opts.ctl file.
 -BOPTS              Generates just the maker_bopts.ctl file.
 -EXE                Generates just the maker_exe.ctl file.
 -MWAS    <option>   Easy way to control mwas_server for web-based GUI
                          options:  STOP
 -version            Prints the MAKER version.
 -help|?             Prints this usage statement.

Step 6: Create control files that tell MAKER what to do. Three files are required:

6.1 maker_opts.ctl - gives location of input files (genome and evidence) and sets options that affect MAKER behavior

6.2 maker_exe.ctl - gives path information for the underlying executables.

6.3 maker_bopt.ctl - sets parameters for filtering BLAST and Exonerate alignment results

To create these files run the maker command with the -CTL flag. Verify with ls:

   $ maker -CTL
   $ ls
   maker_bopts.ctl  maker_exe.ctl  maker_opts.ctl  test_data

6.4 The "maker_exe.ctl" is automatically generated with the correct paths to executables and does not need to be modified.

6.5 The "maker_bopt.ctl" is automatically generated with reasonable default parameters and also does not need to be modified unless you want to experiment with optimization of these parameters.

6.6 The automatically generated "maker_opts.ctl" file needs to be modified in order to specify the genome file and evidence files to be used as input.  You can use the text editor "vi" or "nano" that is already installed in the MASTER instance
$ rm maker_opts.ctl
$ cp /opt/WQ-MAKER_example_data/maker_opts.ctl .
#-----Gene Prediction
snaphmm= #SNAP HMM file
gmhmm= #GeneMark HMM file
augustus_species= #Augustus gene prediction species model
fgenesh_par_file= #FGENESH parameter file
pred_gff= #ab-initio predictions from an external GFF3 file
model_gff= #annotated gene models from an external GFF3 file (annotation pass-through)
est2genome=1 #infer gene predictions directly from ESTs, 1 = yes, 0 = no # Change 1 to 0
protein2genome=1 #infer predictions from protein homology, 1 = yes, 0 = no # Change 1 to 0
unmask=0 #also run ab-initio prediction programs on unmasked sequence, 1 = yes, 0 = no

Otherwise open the maker_opts.ctl in a text editor of choice )

$ nano maker_opts.ctl

Here are the sections of the “maker_opts.ctl” file you need to edit. For more information about the this please check this The_MAKER_control_files_explained - Add path information to files as shown.

This section pertains to specifying the genome assembly to be annotated and setting organism type:

#-----Genome (these are always required)
genome=./test_data/test_genome.fasta #genome sequence (fasta file or fasta embeded in GFF3 file)
organism_type=eukaryotic #eukaryotic or prokaryotic. Default is eukaryotic

The following section pertains to EST and other mRNA expression evidence. Here we are only using same species data, but one could specify data from a related species using the “altest” parameter. With RNA-seq data aligned to your genome by Cufflinks or Tophat one could use maker auxiliary scripts (cufflinks2gff3 and tophat2gff3) to generate GFF3 files and specify these using the est_gff parameter:

..code-block:: bash

#—–EST Evidence (for best results provide a file for at least one) est=./test_data/mRNA.fasta #set of ESTs or assembled mRNA-seq in fasta format altest= #EST/cDNA sequence file in fasta format from an alternate organism est_gff= #aligned ESTs or mRNA-seq from an external GFF3 file altest_gff= #aligned ESTs from a closely relate species in GFF3 format

The following section pertains to protein sequence evidence. Here we are using previously annotated protein sequences. Another option would be to use SwissProt or other database:

#-----Protein Homology Evidence (for best results provide a file for at least one)
protein=./test_data/msu-irgsp-proteins.fasta  #protein sequence file in fasta format (i.e. from mutiple oransisms)
protein_gff=  #aligned protein homology evidence from an external GFF3 file

This next section pertains to repeat identification:

#-----Repeat Masking (leave values blank to skip repeat masking)
model_org= #select a model organism for RepBase masking in RepeatMasker
rmlib=./test_data/plant_repeats.fasta #provide an organism specific repeat library in fasta format for RepeatMasker
repeat_protein= #provide a fasta file of transposable element proteins for RepeatRunner
rm_gff= #pre-identified repeat elements from an external GFF3 file
prok_rm=0 #forces MAKER to repeatmask prokaryotes (no reason to change this), 1 = yes, 0 = no
softmask=1 #use soft-masking rather than hard-masking in BLAST (i.e. seg and dust filtering)

Step 7: Run WQ-MAKER

Before running MAKER, check to make sure all worker instances have become active.

On the MASTER instance, make sure you are in the “maker_run” directory and all of your files are in place and then run:

$ nohup wq_maker -contigs-per-split 1 -cores 1 -memory 2048 -disk 4096 -N wq_test_${USER} -d all -o master.dbg -debug_size_limit=0 -stats test_out_stats.txt > log_file.txt 2>&1 &

7.1 -contigs-per-split 1: splits the genome file into 1 contig/scaffold/sequence per file. By specifiying this option, we are telling wq_maker to split the genome file into 1 sequence per file. By default, the wq_maker splits the fasta file into 10 sequences per file and this case, it is not ideal because, there will be 2 files (1 containing chromosomes from 1-10 and the other containing 11-12). This will decrease the speed at the wq_maker annotates the genome.

Warning: Unless otherwise you have a complete genome containing chromosomes or very few scaffolds, it is not recommended to use this option. For example if you have a genome that contains 10,000 sequences, then this option will create 10,000 files on your working directory which is not ideal of navigation purposes. Check to see how many contigs/scaffolds/chromosomes you have in your genome using grep “>” -c <genome fasta file> and if the number is too high, then avoid this option

7.2 N maker_run_ud sets the project name to wq_test_{USER}. This is mandatory if we need to run WQ-MAKER.

7.3 -d all Sets the debug flag for Work Queue. For all debugging output, try ‘all’ 7.4 -o master.dbg Sets the debug file for Work Queue 7.5 -debug_size_limit=0 Sets the byte wrap around on the debug file. 0 signifies it is never wrapped (Default it 1M)

Wait for the MASTER to advertise master status to the catalog server before your run WQ-MAKER on the WORKERS (see below).

INFO $ tail log_file.txt

Mon Sep 11 15:08:22 2017 :: Submitting file ./test_data/test_genome.fasta_000008 for processing. Mon Sep 11 15:08:22 2017 :: Submitted task 11 for annotating ./test_data/test_genome.fasta_000008 with command: mpiexec -n 1 maker -g ./test_data/test_genome.fasta_000008 -base test_genome -debug_size_limit=0 Mon Sep 11 15:08:22 2017 :: Submitting file ./test_data/test_genome.fasta_000006 for processing. Mon Sep 11 15:08:22 2017 :: Submitted task 12 for annotating ./test_data/test_genome.fasta_000006 with command: mpiexec -n 1 maker -g ./test_data/test_genome.fasta_000006 -base test_genome -debug_size_limit=0 warning: this work queue master is visible to the public. warning: you should set a password with the –password option.

Once the log_file show the above output and once your WORKERS are in active state, then either ssh or use webshell into each of the WORKERS and then run

$ nohup work_queue_worker -N wq_test_${USER} --cores all --debug-rotate-max=0 -d all -o worker.dbg > log_file_2.txt 2>&1 &

7.6 -N wq_test_${USER} sets the project name to maker_run_test. This is mandatory if we need to run WQ-MAKER. This is the same id that we have specified with MASTER

7.7 –debug-rotate-max=0 Set the maximum size of the debug log (default 10M, 0 disables)

7.8 -d all Sets the debug flag for Work Queue. For all debugging output, try ‘all’ 7.9 -o worker.dbg Sets the debug file for Work Queue

7.10 –cores all Uses all the cores on the machine

Note(Advanced Users)

You can use Anisble method to launch jobs without ssh’ing into WORKERS from the MASTER itself. Once the maker run is started on the master, and once your WORKERS are in active state

Step 1: Copy ansible.cfg file into your home directory which will help you to avoid host verification

$ cp /opt/WQ-MAKER_example_data/.ansible.cfg ~

Step 2: Add ssh keys of MASTER to the JetStream atmosphere. This will allow Ansible to launch the jobs without ssh into the WORKERS. Step 3: Copy maker-hosts file into your working directory and populate it with ip addresses of the WORKERS

$ cp /opt/WQ-MAKER_example_data/maker-hosts .
$ echo "" >> maker-hosts # This ip address of the WORKER is specific to my account. This will not work for you
$ echo "" >> maker-hosts # This ip address of the WORKER is specific to my account. This will not work for you

Step 4: Copy the Ansible playbook to your working directory.

   $ cp /opt/WQ-MAKER_example_data/worker-launch.yml .
   $ cat worker-launch.yml

   - hosts : workers
       PATH: "{{ ansible_env.PATH }}:/home/${USER}/bin:/home/${USER}/.local/bin:/opt/icommands:/opt/icommands:/opt/exonerate-2.2.0-x86_64/bin/:/opt/cctools/bin:/opt/ncbi-blast-2.6.0+/bin/:/opt/snoscan-0.9.1/:/opt/tRNAscan-SE-1.3.1/:/opt/snap/:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/snap/bin:/opt/augustus-3.2.2/bin:/opt/maker/bin:/opt/RepeatMasker:/opt/snap"
       PERL5LIB: "/opt/tRNAscan-SE-1.3.1::/opt/cctools/lib/perl5/site_perl"
     tasks :
     - name : Execute the script
       shell : /opt/cctools/bin/work_queue_worker -N wq_test_${USER} -s /home/${USER} --cores all --debug-rotate-max=0 -d all -o /home/${USER}/worker.dbg

4.1 - hosts is the name of the hosts (workers in this case. It can be anything)
4.2 tasks is the task that need to be performed by the Ansible (In this case run work_queue_worker)
4.3 name is just name of the task (It can be anything)
4.4 -N maker_run_test sets the project name to maker_run_test. This is mandatory if we need to run WQ-MAKER
4.5 -s /home/upendra/ Set the location for creating the working directory of the worker
4.6 --debug-rotate-max=0 Set the maximum size of the debug log (default 10M, 0 disables)
4.7 -d all Sets the debug flag for Work Queue. For all debugging output, try 'all'
4.8 -o worker.dbg Sets the debug file for Work Queue

Step 5: Run WQ-MAKER on the WORKERS

$ nohup ansible-playbook -u ${USER} -i maker-hosts worker-launch.yml > log_file_2.txt 2>&1 &

To check the status of the WQ-MAKER job, run the following. .. code-block:: bash

$ work_queue_status -M wq_test_${USER} PROJECT HOST PORT WAITING RUNNING COMPLETE WORKERS maker_run_test js-157-131.jetstream- 9155 8 4 0 4

Step 8. Stats output from MASTER instance The log_file.txt will tell you if the job has been finished or not.

$ tail log_file.txt

WQ-MAKER Start_time:    1505157588000000
WQ-MAKER End_time:      1505157849000000
WQ-MAKER Elapsed:       0d 0:04:21.000000
Work Queue Wall Time:   0d 0:04:00.427755
Cumulative Task Wall Time:      0d 0:36:25.377304
Cumulative Task Good Execute Time:      0d 0:36:25.377304
Work Queue Send Time:   0d 0:00:01.437632
Work Queue Receive Time:        0d 0:00:03.863163
Mon Sep 11 15:24:09 2017 :: MPI used :: Cores 1 :: Memory 1024 :: Disk 2048

The following are the output files from WQ-MAKER

$ ls test_genome.maker.output/test_genome.maker.output
maker_bopts.log  maker_exe.log  maker_opts.log  mpi_blastdb  test_genome_datastore  test_genome_master_datastore_index.log

8.1 The maker_opts.log, maker_exe.log, and maker_bopts.log files are logs of the control files used for this run of MAKER. 8.2 The mpi_blastdb directory contains FASTA indexes and BLAST database files created from the input EST, protein, and repeat databases. 8.3 test_genome_master_datastore_index.log contains information on both the run status of individual contigs and information on where individual contig data is stored. 8.4 The test_genome_datastore directory contains a set of subfolders, each containing the final MAKER output for individual contigs from the genomic fasta file.

Check the test_genome_master_datastore_index.log and task_outputs.txt to see if there were any failures:

$ cat test_genome.maker.output/test_genome_master_datastore_index.log
Chr1    test_genome_datastore/41/30/Chr1/       STARTED
Chr10   test_genome_datastore/7C/72/Chr10/      STARTED
Chr11   test_genome_datastore/1E/AA/Chr11/      STARTED
Chr12   test_genome_datastore/1B/FA/Chr12/      STARTED
Chr2    test_genome_datastore/E9/36/Chr2/       STARTED
Chr3    test_genome_datastore/CC/EF/Chr3/       STARTED
Chr4    test_genome_datastore/A3/11/Chr4/       STARTED
Chr5    test_genome_datastore/8A/9B/Chr5/       STARTED
Chr6    test_genome_datastore/13/44/Chr6/       STARTED
Chr7    test_genome_datastore/91/B7/Chr7/       STARTED
Chr8    test_genome_datastore/9A/9E/Chr8/       STARTED
Chr9    test_genome_datastore/87/90/Chr9/       STARTED
Chr1    test_genome_datastore/41/30/Chr1/       FINISHED
Chr10   test_genome_datastore/7C/72/Chr10/      FINISHED
Chr11   test_genome_datastore/1E/AA/Chr11/      FINISHED
Chr12   test_genome_datastore/1B/FA/Chr12/      FINISHED
Chr2    test_genome_datastore/E9/36/Chr2/       FINISHED
Chr3    test_genome_datastore/CC/EF/Chr3/       FINISHED
Chr4    test_genome_datastore/A3/11/Chr4/       FINISHED
Chr5    test_genome_datastore/8A/9B/Chr5/       FINISHED
Chr6    test_genome_datastore/13/44/Chr6/       FINISHED
Chr7    test_genome_datastore/91/B7/Chr7/       FINISHED
Chr8    test_genome_datastore/9A/9E/Chr8/       FINISHED
Chr9    test_genome_datastore/87/90/Chr9/       FINISHED

All completed. Other possible status entries include:

  • FAILED - indicates a failed run on this contig, MAKER will retry these
  • RETRY - indicates that MAKER is retrying a contig that failed
  • SKIPPED_SMALL - indicates the contig was too short to annotate (minimum contig length is specified in maker_opt.ctl)
  • DIED_SKIPPED_PERMANENT - indicates a failed contig that MAKER will not attempt to retry (number of times to retry a contig is specified in maker_opt.ctl)

The actual output data is stored in in nested set of directories under* test_genome_datastore* in a nested directory structure.

A typical set of outputs for a contig looks like this:

$ ls test_genome.maker.output/test_genome_datastore/*/*/*
Chr6.gff                                                Chr6.maker.proteins.fasta                 Chr6.maker.transcripts.fasta
Chr6.maker.non_overlapping_ab_initio.proteins.fasta     Chr6.maker.snap_masked.proteins.fasta     run.log
Chr6.maker.non_overlapping_ab_initio.transcripts.fasta  Chr6.maker.snap_masked.transcripts.fasta  theVoid.Chr6
  • The Chr6.gff file is in GFF3 format and contains the maker gene models and underlying evidence such as repeat regions, alignment data, and ab initio gene predictions, as well as fasta sequence. Having all of these data in one file is important to enable visualization of the called gene models and underlying evidence, especially using tools like Apollo which enable manual editing and curation of gene models.
  • The fasta files Chr6.maker.proteins.fasta and Chr6.maker.transcripts.fasta contain the protein and transcript sequences for the final MAKER gene calls.
  • The Chr6.maker.non_overlapping_ab_initio.proteins.fasta and Chr6.maker.non_overlapping_ab_initio.transcripts.fasta files are models that don’t overlap MAKER genes that were rejected for lack of support.
  • The Chr6.maker.snap_masked.proteins.fasta and Chr6.maker.snap_masked.transcript.fasta are the initial SNAP predicted models not further processed by MAKER

The output directory theVoid.Chr1 contains raw output data from all of the pipeline steps. One useful file found here is the repeat-masked version of the contig, query.masked.fasta.

Step 9: Merge the gff files

$ gff3_merge -n -d test_genome.maker.output/test_genome_master_datastore_index.log

9.1 -d The location of the MAKER datastore index log file. 9.2 -n Do not print fasta sequence in footer


By default, the output of the gff3_merge is test_genome.all.gff, but you can have an alternate base name for the output files using “-o” option

If you want to perform abinition gene predictions then you should skip -n option. Run

$ gff3_merge -d test_genome_master_datastore_index.log

And follow the rest of the steps of abinitio gene predictions in here

The final output from gff3_merge is “test_genome.all.gff”

##gff-version 3
Chr6    maker   gene    43764   46139   .   -   .   ID=maker-Chr6-snap-gene-0.3;Name=maker-Chr6-snap-gene-0.3
Chr6    maker   mRNA    43764   46139   .   -   .   ID=maker-Chr6-snap-gene-0.3-mRNA-1;Parent=maker-Chr6-snap-gene-0.3;Name=maker-Chr6-snap-gene-0.3-mRNA-1;_AED=0.12;_eAED=0.50;_QI=64|0|0|1|0|0.33|3|0|76
Chr6    maker   exon    43764   43846   .   -   .   ID=maker-Chr6-snap-gene-0.3-mRNA-1:exon:2;Parent=maker-Chr6-snap-gene-0.3-mRNA-1
Chr6    maker   exon    44833   44896   .   -   .   ID=maker-Chr6-snap-gene-0.3-mRNA-1:exon:1;Parent=maker-Chr6-snap-gene-0.3-mRNA-1
Chr6    maker   exon    45992   46139   .   -   .   ID=maker-Chr6-snap-gene-0.3-mRNA-1:exon:0;Parent=maker-Chr6-snap-gene-0.3-mRNA-1
Chr6    maker   five_prime_UTR  46076   46139   .   -   .   ID=maker-Chr6-snap-gene-0.3-mRNA-1:five_prime_utr;Parent=maker-Chr6-snap-gene-0.3-mRNA-1
Chr6    maker   CDS 45992   46075   .   -   0   ID=maker-Chr6-snap-gene-0.3-mRNA-1:cds;Parent=maker-Chr6-snap-gene-0.3-mRNA-1
Chr6    maker   CDS 44833   44896   .   -   0   ID=maker-Chr6-snap-gene-0.3-mRNA-1:cds;Parent=maker-Chr6-snap-gene-0.3-mRNA-1
Chr6    maker   CDS 43764   43846   .   -   2   ID=maker-Chr6-snap-gene-0.3-mRNA-1:cds;Parent=maker-Chr6-snap-gene-0.3-mRNA-1

Moving data from CyVerse Datastore using iCommands

iCommands is a collection of commands for Linux and Mac OS operating systems that are used in the iRODS system to interact with the CyVerse Data Store. Many commands are very similar to Unix utilities. For example, to list files and directories, in Linux you use ls, but in iCommands you use ils. While iCommands are great for all transfers and for automating tasks via scripts, they are the best choice for large files (2-100 GB each) and for bulk file transfers (many small files). For a comparison of the different methods of uploading and downloading data items, see Downloading and Uploading Data. iCommands can be used by CyVerse account users to download files that have been shared by other users and to upload files to the Data Store, as well as add metadata, change permissions, and more. Commonly used iCommands are listed below. Follow the instructions on Setting Up iCommands for how to download and configure iCommands for your operating system. A CyVerse account is not required to download a public data file via iCommands. To see instructions just for public data download with iCommands, see the iCommands section on Downloading Data Files Without a User Account. For configuring icommands and the different commands that can be used to move the data in and out of datastore, please refer this link. You may want to watch a CyVerse video about iCommands.

Home_Icon Learning Center Home