De novo genome assembly is a method for constructing genomes from a large number of DNA fragments, with no prior knowledge of the correct sequence or order of those fragments. This can be a very difficult computational problem and often presents issues of speed and accuracy due to the large volume of sequences, the presence of repeated regions, and the significant amount of RAM required.
Lasergene Genomics makes it easy to perform a de novo assembly by guiding you through various approaches to meet your needs. Powered by SeqMan NGen, our revolutionary genome assembly software, users can set up complex sequencing projects in mere minutes with task automation features that facilitate de novo sequence assembly with unsurpassed ease and speed, even on modestly equipped computers.
In addition to the traditional de novo workflow, often most useful with mate pair or paired-end data, Lasergene Genomics offers several genome finishing workflows, for error correction and refinement of draft genomes. We also offer several workflows (currently in beta) for de novo assembly and polishing of long read sequencing data from Oxford Nanopore and PacBio, including PacBio Hifi reads.
De novo genome assembly is also an optional but frequently-used precursor to the gene homology analysis workflow in MegAlign Pro.
Whatever your approach, Lasergene Genomics creates the most accurate, complete assemblies possible and provides you with detailed statistics for each fully-editable assembly, as well as excellent visualization and post-assembly analysis tools.
Specify sequences and parameters for assembly
Check for conflicts and evaluate coverage
Group assembled contigs into scaffolds
Add sequences to close gaps
Please see the resources below for more information on our de novo genome assembly software.
Genome Polishing Benchmarks: SeqMan NGen vs. Three Open-Source Tools
Choosing the Best Assembly Strategy for Your Genomic Sequencing Data
How to Assemble Genomes like a Bioinformatics Pro
Cloud Assemblies for NGS Sequences
Watch one of our videos or check out one of our written tutorials to learn more about using Lasergene Genomics for de novo genome assembly.
See how to quickly and easily assemble Sanger/ABI sequencing data and perform downstream analysis. This video shows you how to complete assembly setup, visualization, assembly editing and trimming, and BLAST search using SeqMan Ultra.
Learn how to complete a gap closure after completing a de novo assembly. This video walks you through three different methods you can try based on your specific data.
De novo assembly is a method for constructing genomes from a large number of DNA fragments, with no prior knowledge of the correct sequence or order of those fragments. The process involves the assembly of DNA fragments, or reads, into overlapping oriented contigs, which are then joined into scaffolds and eventually a single chromosome with the help of de novo assembly tools.
When performing de novo genome assembly, SeqMan NGen supports Illumina, Oxford Nanopore, PacBio, Sanger/ABI, and Ion Torrent sequencing technologies.
In SeqMan NGen’s “Combined reference-guided/de novo assembly” workflow, the reference sequence for a related microbial strain is used to guide the initial assembly. Novel regions are assembled de novo, automatically producing a genome scaffold of the sequence strain.
If you have a DNASTAR Cloud Assembly license, you can de novo assemble bacterial, fungal, and other small eukaryotic genomes on the cloud using any inexpensive Windows or Macintosh laptop….
If you have a DNASTAR Cloud Assembly license, you can de novo assemble bacterial, fungal, and other small eukaryotic genomes on the cloud using any inexpensive Windows or Macintosh laptop. If you are performing the assembly on a local computer, rather than the cloud, the answer depends on the computer’s available memory. Here are examples of the committed RAM necessary to de novo assemble different organisms at 50x coverage: E. coli = 12 GB, S. cervisiae = 17 GB, N. crassa = 28 GB, C. elegans = 61 GB.
Yes, our genome assembly software, SeqMan NGen, outputs fully-editable project files in .sqd format that can be edited in SeqMan Ultra. Both sequences and contigs can be edited and contigs can be organized into genome scaffolds to facilitate genome closure editing.
Yes. Lasergene 17 offers three beta workflows for de novo assembly of long read data from Oxford Nanopore and PacBio, including PacBio Hifi data:…
Yes. Lasergene 17 offers three beta workflows for de novo assembly of long read data from Oxford Nanopore and PacBio, including PacBio Hifi data:
All three workflows produce a highly accurate assembly in an editable SeqMan Ultra project file.
| Lasergene Genomics De Novo Genome Assembly Benchmarks | |||||||
|---|---|---|---|---|---|---|---|
| Genome Length (Mbases) | Illumina Read Length | Coverage | ContigN50 (kb) | Largest Contig (bp) | Assembly Time | Data Source | |
| Microbial Genomes | |||||||
| E.coli K12MG1655 | 4.7 | 301 | 100X | 155 | 360,028 | 1 hr 6 min | Illumina Basespace |
| Saccharomyces cerevisiae | 12 | 251 | 100X | 59 | 272,990 | 5 hr 32 min | ERX1598831 |
| Salmonella enterica | 4.7 | 251 | 100X | 110 | 310,809 | 0 hr 39 min | SRA SRX1250164 |
| Eukaryotic Genomes | |||||||
| Aspergillus tubingensis | 35 | 251 | 80X | 215 | 838,152 | 6 hr 40 min | ERR1823584 |
| Caenorhabditis elegans | 97 | 251 | 80X | 35 | 325,695 | 21hr 8min | DRR142763 |
| Arabidopsis thaliana | 120 | 301 | 70X | 77 | 1,056,792 | 17hr 57min | SRR7785174 |
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Structural and functional insights into the ATP-binding cassette transporter family in the corn planthopper, Peregrinus maidis
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Differential viral genome diversity of healthy and RSS-affected broiler flocks
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Transcriptome software results show significant variation among different commercial pipelines
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Genome sequences of 12 Pseudomonas lundensis strains isolated from the lungs of humans
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Clonal diversity and spatial genetic structure in the long-lived herb, Prairie trillium
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Development and validation of a reference data set for assigning Staphylococcus species based on next-generation sequencing of the 16S-23S rRNA region
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