Bedshift: perturbation of genomic interval sets

Functional genomics experiments, like ChIP-Seq or ATAC-Seq, produce results that are summarized as a region set. There is no way to objectively evaluate the effectiveness of region set similarity metrics. We present Bedshift, a tool for perturbing BED files by randomly shifting, adding, and dropping regions from a reference file. The perturbed files can be used to benchmark similarity metrics, as well as for other applications. We highlight differences in behavior between metrics, such as that the Jaccard score is most sensitive to added or dropped regions, while coverage score is most sensitive to shifted regions.

Bedshift: perturbation of genomic interval sets

Results of functional genomics experiments such as ChIP-Seq or ATAC-Seq produce data summarized as a region set. Many tools have been developed to analyze region sets, including computing similarity metrics to compare them. However, there is no way to objectively evaluate the effectiveness of region set similarity metrics. In this paper we present bedshift, a command-line tool and Python API to generate new BED files by making random perturbations to an original BED file. Perturbed files have known similarity to the original file and are therefore useful to benchmark similarity metrics. To demonstrate, we used bedshift to create an evaluation dataset of 3,600 perturbed files generated by shifting, adding, and dropping regions from a reference BED file. Then, we compared four similarity metrics: Jaccard score, coverage score, Euclidean distance, and cosine similarity. The results show that the Jaccard score is most sensitive to detecting adding and dropping regions, while the coverage score is more sensitive to shifted regions.AvailabilityBSD2-licensed source code and documentation can be found at https://bedshift.databio.org.

Assessment of various treatment modalities for isolated gingival recession defect- A retrospective study

Esthetic demands among the patients have increased markedly over the past few years. The Gingival recession is one of the prime concerns, and there are various treatment modalities in managing recession defects. Most often, outcomes following root coverage procedures are not assessed. Thus the current article aims to determine the aesthetic outcome following various treatment modalities for root coverage procedures using Recession Score (RES). In the present study, seventeen patients with Miller Class I, II and III recession defects treated with root coverage procedures were evaluated retrospectively. Esthetic outcomes were assessed using the root coverage score (RES) . Among 17 managed recession sites, 6(35%) had complete root coverage. Three of six patients who attained complete root coverage had a perfect score (RES-10). Free Gingival Graft showed better root coverage and recession score (RES); however, there was no significant association between root coverage, RES and various treatment modalities used for recession coverage (p>0.05).