VennDiagram - Generate High-Resolution Venn and Euler Plots

A set of functions to generate high-resolution Venn and Euler plots. Includes handling for several special cases, including two-case scaling, and extensive customization of plot shape and structure.

Last updated 3 years ago

8.55 score 3 stars 41 packages 5.9k scripts 16k downloads

BoutrosLab.plotting.general - Functions to Create Publication-Quality Plots

Contains several plotting functions such as barplots, scatterplots, heatmaps, as well as functions to combine plots and assist in the creation of these plots. These functions will give users great ease of use and customization options in broad use for biomedical applications, as well as general purpose plotting. Each of the functions also provides valid default settings to make plotting data more efficient and producing high quality plots with standard colour schemes simpler. All functions within this package are capable of producing plots that are of the quality to be presented in scientific publications and journals. P'ng et al.; BPG: Seamless, automated and interactive visualization of scientific data; BMC Bioinformatics 2019 <doi:10.1186/s12859-019-2610-2>.

Last updated 2 months ago

8.35 score 11 stars 6 packages 268 scripts 784 downloads

CancerEvolutionVisualization - Publication Quality Phylogenetic Tree Plots

Generates tree plots with precise branch lengths, gene annotations, and cellular prevalence. The package handles complex tree structures (angles, lengths, etc.) and can be further refined as needed by the user.

Last updated 2 days ago

5.81 score 2 stars 4 scripts 230 downloads

bedr - Genomic Region Processing using Tools Such as 'BEDTools', 'BEDOPS' and 'Tabix'

Genomic regions processing using open-source command line tools such as 'BEDTools', 'BEDOPS' and 'Tabix'. These tools offer scalable and efficient utilities to perform genome arithmetic e.g indexing, formatting and merging. bedr API enhances access to these tools as well as offers additional utilities for genomic regions processing.

Last updated 6 years ago

4.19 score 2 packages 257 scripts 780 downloads

ISOpureR - Deconvolution of Tumour Profiles

Deconvolution of mixed tumour profiles into normal and cancer for each patient, using the ISOpure algorithm in Quon et al. Genome Medicine, 2013 5:29. Deconvolution requires mixed tumour profiles and a set of unmatched "basis" normal profiles.

Last updated 6 years ago

3.61 score 3 stars 34 scripts 214 downloads

iSubGen - Integrative Subtype Generation

Multi-data type subtyping, which is data type agnostic and accepts missing data. Subtyping is performed using intermediary assessments created with autoencoders and similarity calculations.

Last updated 4 years ago

2.70 score 4 scripts 157 downloads

SeqKat - Detection of Kataegis

Kataegis is a localized hypermutation occurring when a region is enriched in somatic SNVs. Kataegis can result from multiple cytosine deaminations catalyzed by the AID/APOBEC family of proteins. This package contains functions to detect kataegis from SNVs in BED format. This package reports two scores per kataegic event, a hypermutation score and an APOBEC mediated kataegic score. Yousif, F. et al.; The Origins and Consequences of Localized and Global Somatic Hypermutation; Biorxiv 2018 <doi:10.1101/287839>.

Last updated 5 years ago

2.11 score 13 scripts 141 downloads

OutSeekR - Statistical Approach to Outlier Detection in RNA-Seq and Related Data

An approach to outlier detection in RNA-seq and related data based on five statistics. 'OutSeekR' implements an outlier test by comparing the distributions of these statistics in observed data with those of simulated null data.

Last updated 3 days ago

2.00 score 2 scripts

OmicsQC - Nominating Quality Control Outliers in Genomic Profiling Studies

A method that analyzes quality control metrics from multi-sample genomic sequencing studies and nominates poor quality samples for exclusion. Per sample quality control data are transformed into z-scores and aggregated. The distribution of aggregated z-scores are modelled using parametric distributions. The parameters of the optimal model, selected either by goodness-of-fit statistics or user-designation, are used for outlier nomination. Two implementations of the Cosine Similarity Outlier Detection algorithm are provided with flexible parameters for dataset customization.

Last updated 9 months ago

2.00 score 2 scripts 119 downloads