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SimLoRD is a read simulator for long reads from third generation sequencing and is currently focused on the Pacific Biosciences SMRT error model.

Project description

SimLoRD is a read simulator for third generation sequencing reads and is currently focused on the Pacific Biosciences SMRT error model.

Reads are simulated from both strands of a provided or randomly generated reference sequence.

Features

  • The reference can be read from a FASTA file or randomly generated with a given GC content. It can consist of several chromosomes, whose structure is respected when drawing reads. (Simulation of genome rearrangements may be incorporated at a later stage.)
  • The read lengths can be determined in four ways: drawing from a log-normal distribution (typical for genomic DNA), sampling from an existing FASTQ file (typical for RNA), sampling from a a text file with integers (RNA), or using a fixed length
  • Quality values and number of passes depend on fragment length.
  • Provided subread error probabilities are modified according to number of passes
  • Outputs reads in FASTQ format and alignments in SAM format

System requirements

We recommend using miniconda and creating an environment for SimLoRD

# Create and activate a new environment called simlord
conda create -n simlord python=3 pip numpy scipy cython
source activate simlord

# Install packages that are not available with conda from pip
pip install pysam
pip install dinopy
pip install simlord

# You now have a 'simlord' script; try it:
simlord --help

# In case of a new version update as follows:
pip install simlord --upgrade

# To switch back to your normal environment, use
source deactivate

Platform support

SimLoRD is a pure Python program. This means that it runs on any operating system (OS) for which Python 3 and the other packages are available.

Example usage

Example 1: Simulate 10000 reads for the reference ref.fasta, use the default options for simulation and store the reads in myreads.fastq and the alignment in myreads.sam.

simlord  --read-reference ref.fasta -n 10000  myreads

Example 2: Generate a reference with 10 mio bases GC content 0.6 (i.e., probability 0.3 for both C and G; thus 0.2 probability for both A and T), store the reference as random.fasta, and simulate 10000 reads with default options, store reads as myreads.fastq, do not store alignments.

simlord --generate-reference 0.6 10000000 --save-reference random.fasta\
        -n 10000 --no-sam  myreads

Example 3: Simulate reads from the given reference.fasta, using a fixed read length of 5000 and custom subread error probabilities (12% insertion, 12% deletion, 2% substitution). As before, save reads as myreads.fastq and myreads.sam.

simlord --read-reference reference.fasta  -n 10000 -fl 5000\
        -pi 0.12 -pd 0.12 -ps 0.02  myreads

A full list of parameters, as well as their documentation, can be found here.

Last Changes

Version 1.0.4 (2020-01-07)

Bugs fixed

  • Added missing else for parameter sam_output.

Other Changes

  • Changed read names.
  • New read name format: ‘m{read_number}/{read_length}/CCS read_information’
  • Added parameter –old-read-names for old read names where all information is encoded in one large string delimited by ‘;’.

Version 1.0.3 (2019-05-20)

New Features

  • Added new parameter –gzip to gzip the output reads fastq file.
  • If “-” instead of a filename is given, the reads are printed to sdt-out.
  • In this case without further specification the sam-file gets the name “reads.sam” in the current working directory.

Other Changes

  • Changed coverage parameter from int to float allowing fractional coverage values.
  • Changed delimiter in read id from _ to ;
  • Added chromosome name to read id
  • Changed id of mate read in sam file to result in “*” instead of “=”.
  • Changed fastq writing from text to byte writing to speed up I/O

Version 1.0.2 (2017-03-17)

New Features

  • Draw chromosomes for reads weighted with their length instead of equal distributed. This leads to a equal distributed read coverage over the chromosomes. Previous behaviour with equal probabilities for each chromosome can be activated with parameter –uniform-chromosome-probability.
  • Parameter –coverage: Determine number of reads depending on the desired read coverage of the whole reference genome.
  • Parameter –without-ns: Sample the reads only from regions completly without Ns.

Warning: Using –without-ns may lead to biased read coverage depending on the size of contigs without Ns and the expected readlength.

Bugs fixed

  • CIGAR string had sometimes wrong count of last match because of false extension after deletion.

Version 1.0.1 (2017-01-03)

Bugs fixed

  • Removed nargs=1 at parameter –probability-threshold leading to an error when changing the parameter.

Version 1.0.0 (2016-07-13)

API Changes

  • Changed SEQ in SAM file to reverse complemented read instead of the original read for reads mapping to the reverse complement of the reference.

Example:

reference       ATCG     read   CAAT
true alignment  ||X|
                ATTG

Before: SEQ CAAT and CIGAR string 2=1X1=
Now:    SEQ ATTG and CIGAR string 2=1X1=

License

SimLoRD is Open Source and licensed under the MIT License.

Project details


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