Showing 6 of total 6 results (show query)
bioc
HiCcompare:HiCcompare: Joint normalization and comparative analysis of multiple Hi-C datasets
HiCcompare provides functions for joint normalization and difference detection in multiple Hi-C datasets. HiCcompare operates on processed Hi-C data in the form of chromosome-specific chromatin interaction matrices. It accepts three-column tab-separated text files storing chromatin interaction matrices in a sparse matrix format which are available from several sources. HiCcompare is designed to give the user the ability to perform a comparative analysis on the 3-Dimensional structure of the genomes of cells in different biological states.`HiCcompare` differs from other packages that attempt to compare Hi-C data in that it works on processed data in chromatin interaction matrix format instead of pre-processed sequencing data. In addition, `HiCcompare` provides a non-parametric method for the joint normalization and removal of biases between two Hi-C datasets for the purpose of comparative analysis. `HiCcompare` also provides a simple yet robust method for detecting differences between Hi-C datasets.
Maintained by Mikhail Dozmorov. Last updated 5 months ago.
softwarehicsequencingnormalizationdifference-detectionhi-cvisualization
20 stars 8.63 score 51 scripts 5 dependents
bcm-uga
pcadapt:Fast Principal Component Analysis for Outlier Detection
Methods to detect genetic markers involved in biological adaptation. 'pcadapt' provides statistical tools for outlier detection based on Principal Component Analysis. Implements the method described in (Luu, 2016) <DOI:10.1111/1755-0998.12592> and later revised in (Privé, 2020) <DOI:10.1093/molbev/msaa053>.
Maintained by Florian Privé. Last updated 6 months ago.
40 stars 7.59 score 327 scripts
plantandfoodresearch
hidecan:Create HIDECAN Plots for Visualising Genome-Wide Association Studies and Differential Expression Results
Generates HIDECAN plots that summarise and combine the results of genome-wide association studies (GWAS) and transcriptomics differential expression analyses (DE), along with manually curated candidate genes of interest. The HIDECAN plot is presented in: Angelin-Bonnet, O., Vignes, M., Biggs, P. J., Baldwin, S., & Thomson, S. (2023). Visual integration of GWAS and differential expression results with the hidecan R package. bioRxiv, 2023-03.
Maintained by Olivia Angelin-Bonnet. Last updated 12 days ago.
7 stars 5.95 score 14 scripts 1 dependentsbioc
ggmanh:Visualization Tool for GWAS Result
Manhattan plot and QQ Plot are commonly used to visualize the end result of Genome Wide Association Study. The "ggmanh" package aims to keep the generation of these plots simple while maintaining customizability. Main functions include manhattan_plot, qqunif, and thinPoints.
Maintained by John Lee. Last updated 5 months ago.
visualizationgenomewideassociationgenetics
4.26 score 23 scripts
feraguate
pleiotest:Fast Sequential Pleiotropy Test
It performs a fast multi-trait genome-wide association analysis based on seemingly unrelated regressions. It tests for pleiotropic effects based on a series of Intersection-Union Wald tests. The package can handle large and unbalanced data and plot results.
Maintained by Fernando Aguate. Last updated 3 years ago.
1 stars 2.70 score 2 scripts
cran
GWASinspector:Comprehensive and Easy to Use Quality Control of GWAS Results
When evaluating the results of a genome-wide association study (GWAS), it is important to perform a quality control to ensure that the results are valid, complete, correctly formatted, and, in case of meta-analysis, consistent with other studies that have applied the same analysis. This package was developed to facilitate and streamline this process and provide the user with a comprehensive report.
Maintained by Alireza Ani. Last updated 2 days ago.
2.30 score