
Segpy is a streamlined, user-friendly pipeline designed for variant segregation analysis, allowing investigators to compute allelic counts at variant sites across study subjects. The pipeline can be applied to both pedigree-based family cohorts — those involving single or multi-family trios, quartets, or extended families — and population-based case-control cohorts. Considering the scale of modern datasets and the computational power required for their analysis, the Segpy pipeline was designed for seamless integration with the users’ high-performance computing (HPC) clusters. As input, users must provide a single VCF file describing the genetic variants of all study subjects and a pedigree file describing the familial relationships among those individuals (if applicable) and their disease status. As output, Segpy computes variant carrier counts for affected and unaffected individuals, both within and outside of families, by categorizing wild-type individuals, heterozygous carriers, and homozygous carriers at specific loci. These counts are organized into a comprehensive data frame, with each row representing a single variant and labeled with the Sample IDs of the corresponding carriers to facilitate donwstream analysis.
| citations The total number of citations received by all articles of the researcher of interest. | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
