Documentation for Sandy version 0.23

Contents

  1. Usage and option summary
    1. General Syntax
    2. Main Commands
      1. Command genome
      2. Command transcriptome
    3. Database Commands
      1. Command quality
      2. Command expression
      3. Command variation
    4. Miscellaneous Commands
      1. Command version
      2. Command citation
    5. Help Commands
  2. Docker Usage

Usage and option summary

General Syntax

Usage:

$ sandy [options]
$ sandy help <command>
$ sandy <command> [options] <FILEs>

where there are basically two commands for general help, two main commands with their own inner options, tree database management commands, some miscellaneous commands and a specific help command for each of the main commands. See:

Options Description
-h, –help brief help message
-u, –man full documentation
Help commands:  
help show application or command-specific help
man show application or command-specific documentation
Misc commands:  
version print the current version
citation export citation in BibTeX format
Database commands:  
quality manage quality profile database
expression manage expression-matrix database
variation manage structural variation database
Main commands:  
genome simulate genome sequencing
transcriptome simulate transcriptome sequencing

Some examples:

  1. If the user wants to see a brief help for the expression command, he can type both of the commands bellow: 
     $ sandy help expression

    or

     $ sandy expression -h
  2. To view the version of Sandy in use, just type: 
     $ sandy version
  3. And, to take a BibTeX entry to cite Sandy in his work, type: 
     $ sandy citation

Main Commands

Command genome

Use it to generate simulated FASTq-files from a given FASTA-file. The genome command sets these default options for a genome sequencing simulation:

  • The strand is randomly chosen;
  • The total number of reads is calculated by the coverage;
  • Chromosome reads are proportional to sequence lengths;

Usage:

$ sandy genome [options] <fasta-file>

whose options’ exhaustive list can be consulted by sandy genome -h or even sandy help genome commands. At least one fasta-file must be given as the <fasta-file> term. The results will be one or two fastq-files, depending on the sequencing-type option, -t, for single-ended or paired-ended reads, and an additional file for the reads-counts.

Options Description
-h, –help brief help message
-u, –man full documentation
-v, –verbose print log messages
-p, –prefix prefix output [default:”out”]
-o, –output-dir output directory [default:”.”]
-O, –output-format bam, sam, fastq.gz, fastq [default:”fastq.gz”]
-1, –join-paired-ends merge R1 and R2 outputs in one file
-x, –compression-level speed compression: “1” - compress faster,
“9” - compress better [default:”6”; Integer]
-i, –append-id append to the defined template id [Format]
-I, –id overlap the default template id [Format]
-j, –jobs number of jobs [default:”1”; Integer]
-s, –seed set the seed of the base generator
[default:”time()”; Integer]
-c, –coverage fastq-file coverage [default:”8”, Number]
-t, –sequencing-type single-end or paired-end reads
[default:”paired-end”]
-q, –quality-profile sequencing system profiles from quality
database [default:”poisson”]
-e, –sequencing-error sequencing error rate
[default:”0.005”; Number]
-m, –read-mean read mean size for poisson [default:”100”; Integer]
-d, –read-stdd read standard deviation size for poisson [default:”0”; Integer]
-M, –fragment-mean the fragment mean size for paired-end reads
[default:”300”; Integer]
-D, –fragment-stdd the fragment standard deviation size for paired-end reads
[default:”50”; Integer]
-a, –genomic-variation a list of structural variation entries from variation database. This option may be passed
multiple times [default:”none”]
-A, –genomic-variation-regex a list of perl-like regex to match structural
variation entries in variation database.
This option may be passed multiple times
[default:”none”]

Some examples:

  1. The following command will produce two FASTq files (default sequencing-type is “paired-end”), both with a coverage of 20x (default coverage is 8), and a plain text reads-count file in a tab-separated fashion. 
     $ sandy genome --verbose --sequencing-type=paired-end --coverage=20 hg38.fa 2> sim.log

    or, equivalently

     $ sandy genome -v -t paired-end -c 20 hg38.fa 2> sim.log
  2. For reproducibility, the user can set an integer seed for the random raffles with the -s option (seed default is environment time() value), for example: 
     $ sandy genome -s 1220 my_fasta.fa
  3. To simulate reads from a ready registered database with a specific quality profile other than default’s one, type, for example: 
     $ sandy genome --quality-profile=hiseq_101 hg19.fa

    See the quality profile section to know how can a user register a new profile on the database. Note: If the user uses the option -v, by default, the log messages will be directed to the standard error so, in the example above, it was redirected to a file. Without the -v option, only errors messages will be printed.

  4. Sequence identifiers (first lines of FASTq entries) may be customized in Sandy output using a format string passed by the user. This format is a combination of literal and escaped characters, in a similar fashion to that used in C programming language’s printf function. For example, let’s simulate a paired-end sequencing and add the read length, read position and mate position into all sequence identifiers: 
     $ sandy genome -s 123 --id="%i.%U read=%c:%t-%n mate=%c:%T-%N length=%r" hg38.fa

    In this case, results would be:

     $ sandy genome -s 123 --id="%i.%U read=%c:%t-%n mate=%c:%T-%N length=%r" hg38.fa
 ==> Into R1
 @SR.1 read=chr6:979-880 mate=chr6:736-835 length=100
 ...
 ==> Into R2
 @SR.1 read=chr6:736-835 mate=chr6:979-880 length=100
 ...
  5. To change the sequencing quality profile, use the -q option and a string value (quality-profile default is “hiseq”): 
     $ sandy genome -q myseq_150 my_fasta_file.fa
  6. It is possible to set the size of the reads with the -r option and an integer number (reads-size default is 101): 
     $ sandy genome -r 151 my_fasta_file.fa
  7. User also can set the mean size of a fragment in a paired-end sequencing with the -m option and an integer number (default is 300): 
     $ sandy genome -m 300 my_fasta_file.fa
  8. And, he can also set the standard deviation of the size of a fragment in a paired-end sequencing with the -D option and an integer number (default is 50): 
     $ sandy genome -D 30 my_fasta_file.fa
  9. The options above are the most frequently used ones for the genome command, but many more can be found in the Sandy’s documentation, with: 
     $ sandy genome --man

    Command transcriptome

Use it to generate simulated FASTq files from a given FASTA file, according to an expression profile matrix file. The transcriptome command sets these default options for a transcriptome sequencing simulation as well:

  • Choose the Minus strand;
  • The number of reads is directly passed;
  • The genes/transcripts are raffled following the expression matrix;

Usage:

$ sandy transcriptome [options] <fasta-file>

whose options’ exhaustive list can be consulted by sandy transcriptome -h or even sandy help transcriptome commands.

Options Description
-h, –help brief help message
-u, –man full documentation
-v, –verbose print log messages
-p, –prefix prefix output [default:”out”]
-o, –output-dir output directory [default:”.”]
-O, –output-format bam, sam, fastq.gz, fastq [default:”fastq.gz”]
-1, –join-paired-ends merge R1 and R2 outputs in one file
-x, –compression-level speed compression: “1” - compress faster,
“9” - compress better [default:”6”; Integer]
-i, –append-id append to the defined template id [Format]
-I, –id overlap the default template id [Format]
-j, –jobs number of jobs [default:”1”; Integer]
-s, –seed set the seed of the base generator
[default:”time()”; Integer]
-n, –number-of-reads set the number of reads [default:”1000000”, Integer]
-t, –sequencing-type single-end or paired-end reads
[default:”paired-end”]
-q, –quality-profile sequencing system profiles from quality
database [default:”poisson”]
-e, –sequencing-error sequencing error rate
[default:”0.005”; Number]
-m, –read-mean read mean size for poisson [default:”100”; Integer]
-d, –read-stdd read standard deviation size for poisson [default:”0”; Integer]
-M, –fragment-mean the fragment mean size for paired-end reads
[default:”300”; Integer]
-D, –fragment-stdd the fragment standard deviation size for paired-end reads
[default:”50”; Integer]
-f, –expression-matrix an expression-matrix entry from database

Some examples:

  1. The command: 
     $ sandy transcriptome --verbose --number-of-reads=1000000 --expression-matrix=brain_cortex gencode_pc_v26.fa.gz

    or, equivalently

     $ sandy transcriptome -v -n 1000000 -f brain_cortex gencode_pc_v26.fa.gz

    will both generate a FASTq file with 1000000 reads from the gencode_pc_v26.fa.gz file and a plain text file with the raw counts of the reads per gene, according to the expression matrix provided by the brain_cortex entry already registered in the database.

  2. To demonstrate some other features, think about the sequencing error rate that can be set between 0 and 1. By default, Sandy set this value to 0.005, which means 1 error every 200 bases. To set it to another value, try: 
     $ sandy transcriptome -f liver --sequencing-error=0.001 genome_pc_v26.fa.gz
  3. For reproducibility, the user can set the seed option and guarantee the reliability of all the raffles in a later simulation. 
     $ sandy transcriptome -q hiseq_101 --seed=123 transcripts.fa
  4. To have an idea of Sandy’s plurality, look to how overwhelming the number of choices could be: 
     $ sandy transcriptome \
     --expression-matrix=pancreas \
     --quality-profile=hiseq_101 \
     --sequencing-type=paired-end \
     --fragment-mean=350 \
     --fragment-stdd=100 \
     --prefix=pancreas_sim \
     --output-dir=sim_dir \
     --id="%i.%U read=%c:%t-%n mate=%c:%T-%N length=%r" \
     --verbose \
     --seed=123 \
     --jobs=30 \
     gencode_pc_v26.fa.gz

A note on parallelism: To increase the processing speed, the simulation can run in parallel, splitting the task among jobs. For example, type:

$ sandy transcriptome --jobs 15 gencode_lnc.fa.gz

and Sandy will allocate 15 jobs. This feature works for both genome and transcriptome simulations commands.

Database Commands

Command quality

Use the quality command to manage quality profiles database. With this command, it is possible to add or remove customized expression profiles in the built-in database and make simulations more suitable for your experimental data. By default, Sandy uses a Poisson distribution when compiling the quality entries, but like many other features, this behavior can be altered and restored to vendor’s profile by the user.

Usage:

$ sandy quality
$ sandy quality [options]
$ sandy quality <sub-command>

whose options’ exhaustive list can be consulted by sandy quality -h or even sandy help quality commands.

Options Description
-h, –help brief help message
-u, –man full documentation
Sub-Commands  
add add a new quality profile to database
dump dump a quality-profile from database
remove remove an user quality profile from database
restore restore the database

Some examples:

  1. To list the quality profiles already registered in the builtin database, you can simply type: 
     $ sandy quality

    and all entries will be shown:

     .------------------------------------------------------------------------------------------------------.
 | quality profile | mean  | stdd | error | type            | source            | provider | date       |
 +-----------------+-------+------+-------+-----------------+-------------------+----------+------------+
 | hiseq_101       |   101 |    0 | 0.001 | fragment        | 1000 genome       | vendor   | 2018-08-08 |
 | hiseq_150       |   150 |    0 | 0.001 | fragment        | SRA ID=SRR5805510 | vendor   | 2018-08-08 |
 | hiseq_51        |    51 |    0 | 0.001 | fragment        | SRA ID=SRR3185389 | vendor   | 2018-08-08 |
 | hiseq_76        |    76 |    0 | 0.001 | fragment        | SRA ID=SRR3355336 | vendor   | 2018-08-08 |
 | miseq_150       |   150 |    0 | 0.001 | fragment        | SRA ID=SRR6876696 | vendor   | 2018-08-08 |
 | miseq_301       |   301 |    0 | 0.001 | fragment        | SRA ID=SRR7089434 | vendor   | 2018-08-08 |
 | nextseq_51      |    51 |    0 | 0.001 | fragment        | SRA ID=SRR6131534 | vendor   | 2018-08-08 |
 | nextseq_85      |    85 |    0 | 0.001 | fragment        | SRA ID=SRR5445416 | vendor   | 2018-08-08 |
 | ont             | 15482 | 6195 |  0.25 | single-molecule | 10.1038/nbt.4060  | vendor   | 2018-08-08 |
 | pacbio          |  8817 | 3277 |  0.15 | single-molecule | 10.1038/nbt.2835  | vendor   | 2018-08-08 |
 | poisson         | -m    | -d   | -e    | both            | default           | vendor   | 2018-08-08 |
 '-----------------+-------+------+-------+-----------------+-------------------+----------+------------'
  2. To register a new probabilistic quality profile called, for example, ‘my_profile.txt’ to be used in the simulation of your FASTA-file. User can use the add sub-command, typing: 
     $ sandy quality add -q 'my_quality_id' my_profile.txt

    This quality profile can be either a FASTq file or a plain text file in a tab separated fashion (quality profile default density function is Poisson).
    Note: Before the new entry can appear in the database’s list, the new profile needs to be validated, and if it can’t, an error message will be show. Sandy prevents you before overwrite an existing entry.

  3. To use a recently inserted quality profile over a given FASTA file to simulate a transcriptomic data, use the -q option with the id you registered: 
     $ sandy genome -q 'my_quality_id' my_fasta.fa
  4. Sometimes the user will need to update or delete some quality profile entry (my_profile.txt for example) in the database. In this situation, he can remove some actual entry and register a newer one, like this: 
     $ sandy quality remove 'my_quality_id'

    Sandy will refuse to remove any vendor’s original entry from the database.

  5. And, there could be times when users would wants to reset all the database to its original state. It’s a very simple command: 
     $ sandy quality restore

    Note that this is a dangerous command and Sandy will warn you about it before make the restoration in fact.

Note: Sandy already comes with one quality profile based on the Poisson probabilistic curve, as described by the literature (illumina, 2018).

Command expression

The expression command is used to verify and update the expression matrix database. In a transcriptome sequencing simulation, the user must provide an expression matrix indexed into this database. Sandy already comes with 52 different tissues from the GTEx project, but the user has the freedom to include his own data as well, or even clean it up to restore the vendor’s original entries state.

Usage:

$ sandy expression
$ sandy expression [options]
$ sandy expression <sub-command>

whose options’ and sub-commands’ exhaustive list can be consulted by sandy expression -h or even sandy help expression commands.

Options Description
-h, –help brief help message
-u, –man full documentation
Sub-Commands  
add add a new expression-matrix to database
dump dump an expression-matrix from database
remove remove an user expression-matrix from database
restore restore the database

Some examples:

  1. To list the expression matrices already registered in the builtin database, the user can simply type: 
     $ sandy expression

    and all registered entries will be shown:

     .----------------------------------------------------------------------------------.
 | expression-matrix                   | source             | provider | date       |
 +-------------------------------------+--------------------+----------+------------+
 | adipose_subcutaneous                | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | adipose_visceral                    | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | adrenal_gland                       | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | artery_aorta                        | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | artery_coronary                     | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | artery_tibial                       | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | bladder                             | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_amygdala                      | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_anterior_cingulate_cortex     | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_caudate                       | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_cerebellar_hemisphere         | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_cerebellum                    | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_cortex                        | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_frontal_cortex                | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_hippocampus                   | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_hypothalamus                  | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_nucleus_accumbens             | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_putamen                       | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_spinal_cord                   | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | brain_substantia_nigra              | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | breast_mammary_tissue               | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | cells_ebv_transformed_lymphocytes   | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | cells_leukemia_cell_line            | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | cells_transformed_fibroblasts       | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | cervix_ectocervix                   | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | cervix_endocervix                   | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | colon_sigmoid                       | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | colon_transverse                    | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | esophagus_gastroesophageal_junction | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | esophagus_mucosa                    | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | esophagus_muscularis                | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | fallopian_tube                      | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | heart_atrial_appendage              | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | heart_left_ventricle                | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | kidney_cortex                       | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | liver                               | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | lung                                | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | minor_salivary_gland                | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | muscle_skeletal                     | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | nerve_tibial                        | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | ovary                               | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | pancreas                            | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | pituitary                           | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | prostate                            | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | skin_not_sun_exposed                | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | skin_sun_exposed                    | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | small_intestine_terminal_ileum      | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | spleen                              | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | stomach                             | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | testis                              | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | thyroid                             | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | uterus                              | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | vagina                              | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 | whole_blood                         | Xena GTEx Kallisto | vendor   | 2018-08-08 |
 '-------------------------------------+--------------------+----------+------------'
  2. But, suppose an user wants to register a new expression matrix file called my_expression.txt to simulate the FASTA-file according to its experimentally annotated data. In this case, the sub-command add would solve your problem: 
     $ sandy expression add -f 'my_expression_id' my_expression.txt

    Note that, before the new entry can appear in the database’s list, the new matrix file needs to be validated, and if it can’t, an error message will be show. Sandy prevents you to overwrite an existing entry.

  3. So, to use the recently added expression matrix in a transcriptome simulation, use the -f option on the transcriptome command: 
     $ sandy expression -f 'my_expression_id' my_fasta.fa
  4. Sometimes an user will need to update or delete some expression-matrix entry (‘my_expression.txt’, for example) in the database. In this situation, he can remove the actual entry and register a newer one, like this: 
     $ sandy expression remove 'my_expression_id'

    Sandy will refuse to remove any vendor’s original entry from the database.

  5. Finally, there could be times when you would want to reset all the database to its original state. It’s a very simple command: 
     $ sandy expression restore

    Note that this is a dangerous command and Sandy will warn you about it before make the restoration in fact.

Command variation

Usage:

$ sandy variation
$ sandy variation [options]
$ sandy variation <sub-command>

whose options’ and sub-commands’ exhaustive list can be consulted by sandy variation -h or even sandy help variation commands.

Options Description
-h, –help brief help message
-u, –man full documentation
Sub-Commands:  
add add a new structural variation to database
dump dump structural variation from database
remove remove an user structural variation from database
restore restore the database

Some Examples:

  1. To show all variations entries in the database, type: 
     $ sandy variations

    and all entries for variations will be shown:

     .-------------------------------------------------------------------------------------.
 | structural variation      | source                          | provider | date       |
 +---------------------------+---------------------------------+----------+------------+
 | NA12878_hg38_chr1         | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr10        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr11        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr12        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr13        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr14        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr15        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr16        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr17        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr18        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr19        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr2         | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr20        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr21        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr22        | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr3         | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr4         | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr5         | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr6         | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr7         | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr8         | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chr9         | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | NA12878_hg38_chrX         | IGSR - 1000 Genomes Phase 3     | vendor   | 2018-08-08 |
 | fusion_hg38_BCR-ABL1      | COSMIC - Gene Fusions in Cancer | vendor   | 2018-08-08 |
 | fusion_hg38_CCDC6-RET     | COSMIC - Gene Fusions in Cancer | vendor   | 2018-08-08 |
 | fusion_hg38_EML4-ALK      | COSMIC - Gene Fusions in Cancer | vendor   | 2018-08-08 |
 | fusion_hg38_EWSR1-ERG     | COSMIC - Gene Fusions in Cancer | vendor   | 2018-08-08 |
 | fusion_hg38_EWSR1-FLI1    | COSMIC - Gene Fusions in Cancer | vendor   | 2018-08-08 |
 | fusion_hg38_KIAA1549-BRAF | COSMIC - Gene Fusions in Cancer | vendor   | 2018-08-08 |
 | fusion_hg38_KMT2A-AFF1    | COSMIC - Gene Fusions in Cancer | vendor   | 2018-08-08 |
 | fusion_hg38_NCOA4-RET     | COSMIC - Gene Fusions in Cancer | vendor   | 2018-08-08 |
 | fusion_hg38_NPM1-ALK      | COSMIC - Gene Fusions in Cancer | vendor   | 2018-08-08 |
 | fusion_hg38_TMPRSS2-ERG   | COSMIC - Gene Fusions in Cancer | vendor   | 2018-08-08 |
 '---------------------------+---------------------------------+----------+------------'
  2. To increase the database with user’s own data, use the add sub-command, like this: 
     $ sandy variation add -a 'my_variations_id' my_vatiations.txt

    Note that, before the new entry can appear in the database’s list, the new variation’s file needs to be validated, and if it can’t, an error message will be show. Sandy will prevent you to overwrite any existing entry, and Sandy require these variations files to be in a GTF like format, specifying coordinates on a reference genome with one variation per line (INDELs, SNVs and gene fusions).

  3. Now, to use the recently added variations specifications in a genomic project, the user can use the -a option with the id registered for that file: 
     $ sandy genome -a 'my_variations_id' hg38.fa
  4. User can remove no-vendors entries from database as well: 
     $ sandy variation remove 'my_vatiations_id'

    Note that the user can’t remove any vendor’s entry.

  5. Also, to reset all your variation entries to the original state (only with the vendor’s data), use the restore sub-command. 
     $ sandy variation restore
  6. Finally, when an user wants to simulate a reference genome with a high coverage (ex. 50x) and insert some variations in it (maybe to obtain a positive control for some other algorithm he’s using), he can try this: 
     $ sandy genome -c 50 -a NA12878_hg38_chrX hg38.fa

    In this example, he has simulated reads for the whole genome, but the variations are only in the X chromosome of the NA12878 individual in Sandy’s database. An even better way to insert variations to simulations is to use a regular expression to search the entire database, like this:

     $ sandy genome -c 50 -A NA12878* -a fusion_hg38_BCR-ABL1 hg38.fa

    This way, all entries that match NA12878 variations will be taken and, additionally, a well studied gene fusion fusion_hg38_BCR-ABL1 introduced.

See? Notwithstanding the succinct way that Sandy’s commands are constructed, it is possible to construct near real and complex genomes with on demand variations in it with a few words!

Miscellaneous Commands

Command version

Sandy project is made in a rolling release way, so the user can easily find the version number he’s using:

$ sandy version

Command citation

If Sandy was somehow useful, please cite its authors. With the citation command, you can obtain a correct BibTeX entry and/or DOI number for the version of Sandy you’re using:

$ sandy citation

Help Commands

Usage: To get a simple general help, user can type any of these commands:

$ sandy --help

or for short

$ sandy -h

or simply call it without any arguments.

$ sandy

But, if a more comprehensive explanation is needed, invoke Sandy’s manual:

$ sandy --man

or for short

$ sandy -u

For help about specific commands, its options and inputs, type:

$ sandy help <command>

or

$ sandy <command> -h

We always exhort users to get help by consulting Sandy’s builtin documentations with man sandy or info sandy commands in their terminals.

Docker Usage

The user can run many instances of Sandy in a scalable way by pulling its Docker image from Docker Hub in a way aforementioned in the Installation section.

Here, we describe how to port all the commands shown above to be used in a Docker container in a very straightforward way. For example, given the command:

$ sandy help genome

All user has to do is substitute the word sandy by docker run --rm -ti [options] galantelab/sandy, like:

$ docker run --rm -ti [options] galantelab/sandy help genome

And the options are about the folders which the user wants to map inside the container.

Let’s see another example, suppose the user is in a directory like host_path/folder1/ containing the file gencode_pc_v26.fai.gz on which he is trying to use the command bellow:

$ sandy transcriptome \
		--expression-matrix=pancreas \
		--quality-profile=hiseq_101 \
		--sequencing-type=paired-end \
		--fragment-mean=350 \
		--fragment-stdd=100 \
		--prefix=pancreas_sim \
		--output-dir=sim_dir \
		--id="%i.%U read=%c:%t-%n mate=%c:%T-%N length=%r" \
		--verbose \
		--seed=123 \
		--jobs=30 \
		gencode_pc_v26.fa.gz

So, to adapt such a command to a Docker usage looking up to the correct path of the directories containing the data, only substitute the first line with:

$ docker run --rm -ti -v /ABSOLUTE/host_path/folder1:/ABSOLUTE/container_path/folder2 galantelab/sandy transcriptome \
		--expression-matrix=pancreas \
		--quality-profile=hiseq_101 \
		--sequencing-type=paired-end \
		--fragment-mean=350 \
		--fragment-stdd=100 \
		--prefix=pancreas_sim \
		--output-dir=sim_dir \
		--id="%i.%U read=%c:%t-%n mate=%c:%T-%N length=%r" \
		--verbose \
		--seed=123 \
		--jobs=30 \
		gencode_pc_v26.fa.gz

The -v /ABSOLUTE/host_path:/ABSOLUTE/container_path/folder1 option maps the directory folder1 (adding its absolute path) in the host to the folder2, in the container, at /ABSOLUTE/container_path/ directory. Obviously those paths could be something like /home/user/dataset/, we are just highlighting the importance of using the absolute paths here, otherwise it won’t work correctly. Additionally, the -v option can be used repeatedly in the same command, as many times as the number of directories the data needs.

See Docker documentation for more information about options and commands for Docker.