bioturing
by BioTuring
Unlock The Power Of Biological Data Through AI Innovation
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| Name | Latest Version | Summary | Updated | License |
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| r-seuratwrappers | 0.3.1 | SeuratWrappers is a collection of community-provided methods and extensions for Seurat, curated by the Satija Lab at NYGC. These methods comprise functionality not presently found in Seurat, and are able to be updated much more frequently. | Mar 25, 2025 | GPL-3 |
| r-nmf | 0.30.4.900 | This package provides a framework to perform Non-negative Matrix Factorization (NMF). It implements a set of already published algorithms and seeding methods, and provides a framework to test, develop and plug new/custom algorithms. Most of the built-in algorithms have been optimized in C++, and the main interface function provides an easy way of performing parallel computations on multicore machines. | Mar 25, 2025 | GPL (>=2) |
| r-nichenetr | 2.0.0 | This package allows you the investigate intercellular communication from a computational perspective. More specifically, it allows to investigate how interacting cells influence each other's gene expression. Functionalities of this package (e.g. including predicting extracellular upstream regulators and their affected target genes) build upon a probabilistic model of ligand-target links that was inferred by data-integration. | Mar 25, 2025 | GPL-3 |
| r-vctrs | 0.6.3 | Defines new notions of prototype and size that are used to provide tools for consistent and well-founded type-coercion and size-recycling, and are in turn connected to ideas of type- and size-stability useful for analysing function interfaces. | Mar 25, 2025 | MIT |
| r-cellchat | 1.5.0 | an open source R tool that infers, visualizes and analyzes the cell-cell communication networks from scRNA-seq data. | Mar 25, 2025 | GPL-3 |
| python-circos | 0.3.0 | Circos is one of the most popular software for visualizing genomic similarities and features. However, its execution process is complicated and requires multiple original config files for the visualizations. Additionally, Circos is written in Perl, which limits its integration with other software for biological analysis. On the other hand, Python has been applied for various biological software packages. Therefore, by combining these packages, researchers can complete most of the required analysis. Nevertheless, Python lacks a library for drawing Circos plots, even though Circos software has been developed for more than a decade. Here, we provide a python Matplotlib based circular genome visualization package pyCiros. Users easily and quickly visualize genomic features and comparative genome analysis results by specifying annotated sequence files such as GenBank files. | Mar 25, 2025 | GPL |
| cellphonedb | 4.0.0 | CellPhoneDB can be used to search for a particular ligand/receptor, or interrogate your own HUMAN single-cell transcriptomics data. | Mar 25, 2025 | MIT |
| r-dplyr | 1.0.5 | A fast, consistent tool for working with data frame like objects, both in memory and out of memory. | Mar 25, 2025 | MIT |
| ktplotspy | 0.1.10 | Python library for plotting Cellphonedb results. Ported from ktplots R package. | Mar 25, 2025 | MIT |
| r-celltrek | 0.0.94 | CellTrek is a computational toolkit that can directly map single cells back to their spatial coordinates in tissue sections based on scRNA-seq and ST data. The CellTrek toolkit also provides two downstream analysis modules, including SColoc for spatial colocalization analysis and SCoexp for spatial co-expression analysis. | Mar 25, 2025 | MIT |
| r-doubletfinder | 2.0.3 | DoubletFinder identifies doublets by generating artificial doublets from existing scRNA-seq data and defining which real cells preferentially co-localize with artificial doublets in gene expression space. Other DoubletFinder package functions are used for fitting DoubletFinder to different scRNA-seq datasets. For example, ideal DoubletFinder performance in real-world contexts requires (I) Optimal pK selection and (2) Homotypic doublet proportion estimation. pK selection is achieved using pN-pK parameter sweeps and maxima identification in mean-variance-normalized bimodality coefficient distributions. Homotypic doublet proportion estimation is achieved by finding the sum of squared cell annotation frequencies. For more information, see our Cell Sysmtes paper https://www.cell.com/cell-systems/fulltext/S2405-4712(19)30073-0 and our github https://github.com/chris-mcginnis-ucsf/DoubletFinder | Mar 25, 2025 | CC-0 |
| r-scenic | 1.3.1 | SCENIC workflow | Mar 25, 2025 | file LICENSE |
| r-emoa | 0.5_0.2 | Collection of building blocks for the design and analysis of evolutionary multiobjective optimization algorithms. | Mar 25, 2025 | GPL-2 |
| r-presto | 1.0.0 | Scalable implementation of the Wilcoxon rank sum test and auROC statistic. Interfaces to dense and sparse matrices, as well as genomics analysis frameworks Seurat and SingleCellExperiment. | Mar 25, 2025 | GPL-3 |
| r-harmony | 1.0 | Implementation of the Harmony algorithm for single cell integration, described in Korsunsky et al <doi.org/10.1101/461954>. Package includes a standalone Harmony function and interfaces to external frameworks. | Mar 25, 2025 | GPL-3 |
| r-wrmisc | 1.12.0 | The efficient treatment and convenient analysis of experimental high-throughput (omics) data gets facilitated through this collection of diverse functions. Several functions address advanced object-conversions, like manipulating lists of lists or lists of arrays, reorganizing lists to arrays or into separate vectors, merging of multiple entries, etc. Another set of functions provides speed-optimized calculation of standard deviation (sd), coefficient of variance (CV) or standard error of the mean (SEM) for data in matrixes or means per line with respect to additional grouping (eg n groups of replicates). Other functions facilitate dealing with non-redundant information, by indexing unique, adding counters to redundant or eliminating lines with respect redundancy in a given reference-column, etc. Help is provided to identify very closely matching numeric values to generate (partial) distance matrixes for very big data in a memory efficient manner or to reduce the complexity of large data-sets by combining very close values. Many times large experimental datasets need some additional filtering, adequate functions are provided. Batch reading (or writing) of sets of files and combining data to arrays is supported, too. Convenient data normalization is supported in various different modes, parameter estimation via permutations or boot-strap as well as flexible testing of multiple pair-wise combinations using the framework of 'limma' is provided, too. | Mar 25, 2025 | GPL-3 |
| r-meringue | 1.0 | MERINGUE is a computational framework based on spatial auto-correlation and cross-correlation analysis to identify genes with spatially heterogeneous expression patterns, derive putative cell-cell communication, and perform spatially informed cell clustering in 2D and 3D in a density-agnostic manner using spatially resolved transcriptomics data. | Mar 25, 2025 | GPL-3 |
| r-packcircles | 0.3.5 | Algorithms to find arrangements of non-overlapping circles. | Mar 25, 2025 | MIT |
| r-card | 1.1 | CARD is a reference-based deconvolution method that estimates cell type composition in spatial transcriptomics based on cell type specific expression information obtained from a reference scRNA-seq data. A key feature of CARD is its ability to accommodate spatial correlation in the cell type composition across tissue locations, enabling accurate and spatially informed cell type deconvolution as well as refined spatial map construction. CARD relies on an efficient optimization algorithm for constrained maximum likelihood estimation and is scalable to spatial transcriptomics with tens of thousands of spatial locations and tens of thousands of genes. CARD is implemented as an open-source R package, freely available at www.xzlab.org/software.html | Mar 25, 2025 | GPL-3 |
| r-cssam | 1.4 | Cell-type specific differential expression of a microarray experiment of heterogeneous tissue samples, using SAM. | Mar 25, 2025 | LGPL-3 |
| r-monocle3 | 1.3.1 | Monocle 3 performs clustering, differential expression and trajectory analysis for single-cell expression experiments. It orders individual cells according to progress through a biological process, without knowing ahead of time which genes define progress through that process. Monocle 3 also performs differential expression analysis, clustering, visualization, and other useful tasks on single-cell expression data. It is designed to work with RNA-Seq data, but could be used with other types as well. | Mar 25, 2025 | MIT |
| r-archr | 1.0.2 | This package is designed to streamline scATAC analyses in R. | Mar 25, 2025 | GPL-2 |
| r-scevan | 1.0.1 | R package that starting from the raw count matrix of scRNA data automatically classifies the cells present in the biopsy by segregating non-malignant cells of tumor microenviroment from the malignant cells and also characterizes the clonal structure of these malignant cells. | Mar 25, 2025 | GPL-2 |
| r-tfbstools | 1.31.2 | TFBSTools is a package for the analysis and manipulation of transcription factor binding sites. It includes matrices conversion between Position Frequency Matirx (PFM), Position Weight Matirx (PWM) and Information Content Matrix (ICM). It can also scan putative TFBS from sequence/alignment, query JASPAR database and provides a wrapper of de novo motif discovery software. | Mar 25, 2025 | GPL-2 |
| r-spark | 1.1.1 | SPARK is an efficient tool for identifying spatial expression patterns. SPARK directly models raw count data generated from various spatial resolved transcriptomic techniques. With a new efficient penalized quasi-likelihood based algorithm, SPARK is scalable to data sets with tens of thousands of genes measured on thousands of samples. Build upon a non-parametric framework, SPARK-X is scalable to large-scale data sets with tens of thousands of genes measured on hundred thousands of samples. | Mar 25, 2025 | GPL-3 |