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scphaser – haplotype inference using single-cell RNA-seq data

scphaser – haplotype inference using single-cell RNA-seq data

Determination of haplotypes is important for modelling the phenotypic consequences of genetic variation in diploid organisms, including cis-regulatory control and compound heterozygosity. Karolinska Institute researchers realized that single cell RNA-seq (scRNA-seq) data is well suited for phasing genetic variants, since ...

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petal – Co-expression network modelling in R

petal – Co-expression network modelling in R

Networks provide effective models to study complex biological systems, such as gene and protein interaction networks. With the advent of new sequencing technologies, many life scientists are grasping for user-friendly methods and tools to examine biological components at the whole-systems ...

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PcircRNA_finder – circRNA prediction in plants

PcircRNA_finder – circRNA prediction in plants

Recent studies reveal an important role of non-coding circular RNA (circRNA) in the control of cellular processes. Because of differences in the organization of plant and mammal genomes, the sensitivity and accuracy of circRNA prediction programs using algorithms developed for ...

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Pseudotime Estimation – Deconfounding Single Cell Time Series

Pseudotime Estimation – Deconfounding Single Cell Time Series

Repeated cross-sectional time series single cell data confound several sources of variation, with contributions from measurement noise, stochastic cell-to-cell variation and cell progression at different rates. Time series from single cell assays are particularly susceptible to confounding as the measurements ...

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