DiscoSnp
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Application data |
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| Created by | Raluca Uricaru, Pierre Peterlongo, Claire Lemaitre, Rayan Chikhi, Guillaume Rizk |
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| Biological application domain(s) | Population Genomics, Comparative genomics, Sequencing, Sequence assembly (de novo assembly), Genotyping, High-throughput sequencing |
| Principal bioinformatics method(s) | Sequence assembly (de-novo assembly), Read depth analysis |
| Technology | All |
| Created at | INRIA Rennes - Bretagne Atlantique GenScale team |
| Maintained? | Yes |
| Input format(s) | fasta, fastq, compressed fasta, compressed fastq |
| Output format(s) | fasta |
| Software features | de novo (reference free) SNP calling |
| Programming language(s) | C++ |
| Licence | CeCILL |
| Operating system(s) | Unix-like, iOS |
| Contact: | pierre.peterlongo@inria.fr |
Summary: discoSnps : qualitative de-novo SNP caller. Extremely low memory and time efficient. No reference genome needed. Call both homozygous and heterozygous SNPs.
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Description
discoSnps calls both heterozygous and homozygous genotypable SNPs from any number of sequencing datasets, without a reference genome, and with very low memory and time footprints (billions of reads can be analyzed with a standard computer). We established that calling SNPs directly from sequenced reads gives better results than a state-of-the-art assembly and mapping approach, mostly due to the fact that our approach better discriminates SNPs from inexact repeats, while still detecting SNPs in repeated regions. On simulated human data, discoSnp calls 86.4% of simulated SNPs with 99.9% precision. On an arthropod species, 96% of the predicted SNPs that were tested in vitro were confirmed.
Links
References
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