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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Liu, Qian Georgieva, Daniela C. Egli, Dieter Wang, Kai |
| Abstract | Background Recent advances in single-molecule sequencing techniques, such as Nanopore sequencing, improved read length, increased sequencing throughput, and enabled direct detection of DNA modifications through the analysis of raw signals. These DNA modifications include naturally occurring modifications such as DNA methylations, as well as modifications that are introduced by DNA damage or through synthetic modifications to one of the four standard nucleotides. Methods To improve the performance of detecting DNA modifications, especially synthetically introduced modifications, we developed a novel computational tool called NanoMod. NanoMod takes raw signal data on a pair of DNA samples with and without modified bases, extracts signal intensities, performs base error correction based on a reference sequence, and then identifies bases with modifications by comparing the distribution of raw signals between two samples, while taking into account of the effects of neighboring bases on modified bases (“neighborhood effects”). Results We evaluated NanoMod on simulation data sets, based on different types of modifications and different magnitudes of neighborhood effects, and found that NanoMod outperformed other methods in identifying known modified bases. Additionally, we demonstrated superior performance of NanoMod on an E. coli data set with 5mC (5-methylcytosine) modifications. Conclusions In summary, NanoMod is a flexible tool to detect DNA modifications with single-base resolution from raw signals in Nanopore sequencing, and will facilitate large-scale functional genomics experiments that use modified nucleotides. |
| Related Links | https://bmcgenomics.biomedcentral.com/counter/pdf/10.1186/s12864-018-5372-8.pdf |
| Ending Page | 42 |
| Page Count | 12 |
| Starting Page | 31 |
| File Format | HTM / HTML |
| ISSN | 14712164 |
| DOI | 10.1186/s12864-018-5372-8 |
| Journal | BMC Genomics |
| Issue Number | 1 |
| Volume Number | 20 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2019-02-04 |
| Access Restriction | Open |
| Subject Keyword | Life Sciences Microarrays Proteomics Animal Genetics and Genomics Microbial Genetics and Genomics Plant Genetics and Genomics DNA modifications Nanopore long-read data Statistics analysis Computational tool Nanopore signal annotation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Biotechnology Genetics |
| Journal Impact Factor | 3.5/2023 |
| 5-Year Journal Impact Factor | 4.1/2023 |
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