Downstream inference

Various efforts have been made to elucidate the cooperating proteins involved in maintaining chromatin interactions; however, many are still unknown. Here, we present 3CPET, a tool based on a non-parametric Bayesian approach, to infer the set of the most probable protein complexes involved in maintaining chromatin interactions and the regions that they may control, making it a valuable downstream analysis tool in chromatin conformation studies.

16p viaristotle 29-01-2022 10 0   Download

Dropouts distort gene expression and misclassify cell types in single-cell transcriptome. Although imputation may improve gene expression and downstream analysis to some degree, it also inevitably introduces false signals. We develop DISC, a novel deep learning network with semi-supervised learning to infer gene structure and expression obscured by dropouts.

28p viarchimedes 26-01-2022 8 0   Download

Recent advances in rapid, low-cost sequencing have opened up the opportunity to study complete genome sequences. The computational approach of multiple genome alignment allows investigation of evolutionarily related genomes in an integrated fashion, providing a basis for downstream analyses such as rearrangement studies and phylogenetic inference.

20p vikentucky2711 26-11-2020 13 1   Download

A standard procedure in many areas of bioinformatics is to use a single multiple sequence alignment (MSA) as the basis for various types of analysis. However, downstream results may be highly sensitive to the alignment used, and neglecting the uncertainty in the alignment can lead to significant bias in the resulting inference.

26p vikentucky2711 24-11-2020 13 1   Download

Population structure inference using the software STRUCTURE has become an integral part of population genetic studies covering a broad spectrum of taxa including humans. The ever-expanding size of genetic data sets poses computational challenges for this analysis.

5p vioklahoma2711 19-11-2020 8 1   Download