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10x Genomics
Chromium De Novo Assembly

Assembly Process

Supernova generates highly-contiguous, phased, whole-genome de novo assemblies from a Chromium-prepared library.

Supernova should be run with at most 231-1 (about two billion) reads, and at 38-56x coverage of the genome. (Somewhat higher coverage is sometimes advantageous.) Please see Achieving Success with De Novo Assembly and System Requirements before creating your Chromium libraries for assembly.

Running Supernova has the following steps:

  1. Run supernova mkfastq on the Illumina BCL output folder to generate FASTQ files.

  2. Run supernova run separately for each sample to generate a whole genome de novo assembly for each.

  3. Run supernova mkoutput in order to generate various styles of FASTA output for your assemblies.

For the following example, assume that the Illumina BCL output is in a folder named /sequencing/140101_D00123_0111_AHAWT7ADXX.

Run supernova mkfastq

First, follow the instructions on running supernova mkfastq to generate FASTQ files. For example, if the flowcell serial number was HAWT7ADXX, then supernova mkfastq will output FASTQ files in HAWT7ADXX/outs/fastq_path.

Run supernova run for de novo assembly

To run Supernova, you use the supernova run command, with the following parameters:

ArgumentDescription
--idA unique run ID string: e.g. sample345
--fastqsPath of the FASTQ folder generated by supernova mkfastq
e.g. /home/jdoe/runs/HAWT7ADXX/outs/fastq_path
--sample(optional) Can be used to select only a single sample of those specified in the sample sheet supplied to mkfastq. By default, all samples are used.
--description(optional) Description of the data set. This will be included, along with the run ID string, in various output files.
--maxreads(optional) Target using approximately this number of reads.
  • To calculate the number of reads that you need, first start with an estimate of the genome size. If you don't know, make a guess. Supernova will estimate the genome size for you, and if you are far off, you can restart the assembly process.
  • Next, set the number of reads so as to achieve 56x raw coverage. This is (genome size) x 56 / 150, assuming that your reads are 150 bases long. Coverage as low as 38x is acceptable, with some degradation in quality. Coverage significantly greater than 56x can sometimes help but can also be deleterious, depending on the dataset.
  • The default value for this parameter is 1.2B, which only makes sense for ~3.2 Gb genomes. Please note that no more than 231 - 1 reads (about two billion) reads will be allowed.
  • Please note that if you specify more reads than are available, then Supernova will simply use all of your reads.
--bcfrac(optional) [DEPRECATED AND MAY BE DELETED IN A FUTURE VERSION.] Fraction of barcodes in the sample to use. This was intended to aid in the assembly of small genomes, but is no longer needed and may be harmful. Randomly chooses the specified fraction of all barcodes and retains only reads belonging to the chosen barcodes. Unbarcoded reads are selected randomly at the same rate. If --maxreads is specified as well, the data are examined after barcode subsampling and reads are randomly chosen to achieve the desired number.
--localcores(optional) limits concurrent sections of Supernova to use the specified number of cores.
--localmem(optional) limits memory use on shared systems where Supernova may attempt to use more resources than a user is allowed. Note that this is not a hard limit, but is used as a hint for high-memory portions of the assembly process that deliberately scale to the amount of memory installed in a system.

The following options are deprecated, but preserved for processing data created using the older, supernova demux data preparation step:

ArgumentDescription
--indices[deprecated and optional; demux only] Sample indices associated with this sample. Comma-separated list of:
  1. index set plate wells: SI-GA-A1,SI-GA-H12
  2. index sequences: TCGCCATA,GTATACAC
--lanes[deprecated and optional; demux only] Lanes associated with this sample

After determining these input arguments, call supernova run:

$ cd /home/jdoe/runs
$ supernova run --id=sample345 \
                --fastqs=/home/jdoe/runs/HAWT7ADXX/outs/fastq_path

Following a set of preflight checks to validate input arguments, Supernova pipeline stages will begin to run:

supernova run
Copyright (c) 2016 10x Genomics, Inc.  All rights reserved.
-----------------------------------------------------------------------------
Martian Runtime - 2.3.2
 

Running preflight checks (please wait)... 2016-01-01 00:00:08 [runtime] (ready) ID.sample345.ASSEMBLER_CS._ASSEMBLER.ASSEMBLER_PREFLIGHT 2016-01-01 00:00:08 [perform] Serializing pipestance performance data. 2016-01-01 00:00:01 [runtime] (split_complete) ID.sample345.ASSEMBLER_CS._ASSEMBLER.ASSEMBLER_PREFLIGHT 2016-01-01 00:00:01 [runtime] (run:local) ID.sample345.ASSEMBLER_CS._ASSEMBLER.ASSEMBLER_PREFLIGHT.fork0.chnk0.main 2016-01-01 00:00:07 [runtime] (chunks_complete) ID.sample345.ASSEMBLER_CS._ASSEMBLER.ASSEMBLER_PREFLIGHT 2016-01-01 00:00:10 [runtime] (join_complete) ID.sample345.ASSEMBLER_CS._ASSEMBLER.ASSEMBLER_PREFLIGHT 2016-01-01 00:00:11 [runtime] (ready) ID.sample345.ASSEMBLER_CS._ASSEMBLER._ASSEMBLER_PREP._FASTQ_PREP_NEW.SETUP_CHUNKS ...

supernova run will use all of the sequence data available in the FASTQ folder, up to the limit imposed by the --maxreads option, described above.

If you are processing data prepared with the older, deprecated supernova demux process, you can also specify --indices and --lanes to further select the data to be processed. For new datasets, this selection is performed in the samplesheet provided to supernova mkfastq.

supernova run assumes that all of the cores on your system are available for its use, but you can use the --localcores option to limit this. Similarly, supernova run assumes that all of the memory on your system is available for its use. You can use --localmem to suggest limits, however memory utilization in certain sections of the code will scale with the size of the genome, the number of input reads and the quality of the data, and may exceed this limit.

The pipeline will create a new folder named with the sample ID you specified (e.g. /home/jdoe/runs/sample345) for its output. If this folder already exists, supernova run will assume it is an existing pipestance and attempt to resume running it.

Watching Supernova Progress

The standard output from supernova run displays lines that indicate the progress through pipeline stages as shown in Map of the Pipeline. The standard output will pause during individual stages with a message such as:

...
2016-01-03 00:00:01 [runtime] (run:local)       ID.sample345.ASSEMBLER_CS._ASSEMBLER.ASSEMBLER_DF.fork0.chnk0.main

and may appear to have stalled. However you should see a heartbeat message every 6 minutes, such as:

2016-01-03 00:06:01 [runtime] (update)          ID.sample345.ASSEMBLER_CS._ASSEMBLER.ASSEMBLER_DF.fork0 chunks_running
If you wish to monitor the progress of one of these stages, you can view the stage-specific standard output:

e.g.

$ cd /home/jdoe/runs
$ tail sample345/ASSEMBLER_CS/_ASSEMBLER/ASSEMBLER_DF/fork0/chnk0/_stdout

and likewise for other ASSEMBLER stages.

Output Files

A successful supernova run execution should conclude with a message that looks similar to this:

...
2016-01-03 00:00:01 [runtime] (run:local)       ID.sample345.ASSEMBLER_CS._ASSEMBLER.ASSEMBLER_PR.fork0.join
2016-01-03 00:00:01 [runtime] (chunks_complete) ID.sample345.ASSEMBLER_CS._ASSEMBLER.ASSEMBLER_PR
2016-01-03 00:00:03 [runtime] (join_complete)   ID.sample345.ASSEMBLER_CS._ASSEMBLER.ASSEMBLER_PR
 
Outputs:
- Run summary:        /home/jdoe/runs/sample345/outs/summary.csv
- Run report:         /home/jdoe/runs/sample345/outs/report.txt
- Raw assembly files: /home/jdoe/runs/sample345/outs/assembly
 
Pipestance completed successfully!
Saving pipestance info to sample345/sample345.mri.tgz

The output of the pipeline will be contained in a folder named with the sample ID you specified (e.g. sample345). The subfolder named outs will contain the main pipeline output files that are described in more detail in Output Overview.

Run supernova mkoutput for FASTA output

First, familiarize yourself with the representation of a genome assembly as a graph structure. Next, follow the instructions on running supernova mkoutput to generate FASTA files.

Frequently asked questions about running Supernova

Why did you deprecate the barcode subsampling option?
Two things changed. We generated data from several new small genomes, and made major changes to the Supernova algorithm. Contrary to our expectation, the new algorithm yielded in aggregate somewhat worse results when barcode subsampling was applied. In addition, using barcode subsampling wastes data and is confusing. So we no longer recommend its use.
Can I change the value of K?
Supernova uses multiple heuristics to define minimal overlaps between reads, not just a single value, although the assembly graph is represented using a single fixed K value of 48. Changing just one of these heuristics is unlikely to be effective, and might cause Supernova to crash. For most cases where Supernova results do not meet the needs of a given project, deeper changes would be needed to boost performance. These could include improvements to the input data (for example, molecule length), and could include changes to the algorithm architecture.
Should I trim reads before running Supernova?
We recommend against trimming reads. It complicates the process, and no advantage has been demonstrated. However, we have not carried out controlled experiments, and it is conceivable that trimming reads could be advantageous in some cases. If you have an example where trimming greatly improves assembly quality, please share it with us.