Repliscan: a tool for classifying replication timing regions

Gregory J. Zynda, Jawon Song, Lorenzo Concia, Emily E. Wear, Linda Hanley-Bowdoin, William F. Thompson, Matthew W. Vaughn
2017 BMC Bioinformatics  
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
more » ... ormative 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.
doi:10.1186/s12859-017-1774-x pmid:28784090 pmcid:PMC5547489 fatcat:nm2dysfphbewnp3pu3nuj57hta