| Autor: |
Gregory J. Zynda, Jawon Song, Lorenzo Concia, Emily E. Wear, Linda Hanley-Bowdoin, William F. Thompson, Matthew W. Vaughn |
| Jazyk: |
angličtina |
| Rok vydání: |
2017 |
| Předmět: |
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| Zdroj: |
BMC Bioinformatics, Vol 18, Iss 1, Pp 1-14 (2017) |
| Druh dokumentu: |
article |
| ISSN: |
1471-2105 |
| DOI: |
10.1186/s12859-017-1774-x |
| Popis: |
Abstract Background Replication timing experiments that use label incorporation and high throughput sequencing produce peaked data similar to ChIP-Seq experiments. However, the differences in experimental design, coverage density, and possible results make traditional ChIP-Seq analysis methods inappropriate for use with replication timing. Results To accurately detect and classify regions of replication across the genome, we present Repliscan. Repliscan robustly normalizes, automatically removes outlying and uninformative data points, and classifies Repli-seq signals into discrete combinations of replication signatures. The quality control steps and self-fitting methods make Repliscan generally applicable and more robust than previous methods that classify regions based on thresholds. Conclusions Repliscan is simple and effective to use on organisms with different genome sizes. Even with analysis window sizes as small as 1 kilobase, reliable profiles can be generated with as little as 2.4x coverage. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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