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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| biocolabsdk | 1.0.5 | A set of python modules for accessing BioTuring Ecosystem on BioColab private server | Mar 25, 2025 | MIT |
| bioflex | 1.1.1 | A set of python modules for accessing BioTuring single-cell database | Mar 25, 2025 | MIT |
| bioturing-connector | 1.2.0 | A set of python modules for accessing BBrowserX on private server | Mar 25, 2025 | MIT |
| 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 |
| giotto | 0.10.5 | Web development simplified. An MVC framework supporting Python 3. | Mar 25, 2025 | BSD-2-Clause |
| ktplotspy | 0.1.10 | Python library for plotting Cellphonedb results. Ported from ktplots R package. | Mar 25, 2025 | MIT |
| 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 |
| r-archr | 1.0.2 | This package is designed to streamline scATAC analyses in R. | Mar 25, 2025 | GPL-2 |
| r-bseqsc | 1.0 | Companion package to: A single-cell transcriptomic map of the human and mouse pancreas reveals inter- and intra-cell population structure. Baron et al. Cell Systems (2016) https://www.ncbi.nlm.nih.gov/pubmed/27667365 | Mar 25, 2025 | GPL-2 |
| 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-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 |
| 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-chromvarmotifs | 0.2.0 | Stores several motifs as PWMatrixList objects for use in R with packages like motifmatchr and chromVAR. | Mar 25, 2025 | MIT |
| 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-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-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 |
| 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-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-ibridge | 0.0.0.9000 | The development of immune checkpoint-based therapies has been a major advancement in the treatment of cancer with a subset of patients exhibiting dramatic and durable responses across a variety of tumor types. A predictive biomarker for the immunotherapy response is the pre-existing T cell infiltration in the tumor immune microenvironment (TIME). Bulk transcriptomics-based approaches can crudely and indirectly quantify the level of T-cell infiltration using metagenes/deconvolution methods, and therefore can differentiate inflamed and immunologically cold tumors. However, these bulk techniques are unable to identify biomarkers of individual cell types in the TIME. More recently, single-cell RNA sequencing (scRNAseq) based assays have been used to profile a granular account of the TIME. To our knowledge there is no method of identifying patients with T-cell inflamed TIME using both scRNAseq and bulk transcriptomics data. Here, we demonstrate a method, called Identifying Biological Relationships In Dark matter of Genomics Entities (I-BRIDGE), which integrates TCGA bulk RNA-seq data with the malignant/epithelial portion of scRNAseq data to identify patients with T-cell inflamed TIME. Using this method, we report the markers of inflamed phenotypes in malignant cells, myeloid cells and fibroblasts. Thus, we identify Type I and Type II interferon pathways as dominant signals, especially in malignant and myeloid cells. This contrasts with the immune cell metagenes as the main markers of inflamed cancers identified in bulk datasets. These cell-type specific markers potentially include causative targetable genes that can transform a cold TIME to an inflamed one when modulated. In addition, I-BRIDGE can be applied to in vitro grown cancer cell lines and can identify the cell lines that are likely to be adapted from inflamed/cold patient tumors. | Mar 25, 2025 | MIT |
| 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-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-music | 1.0.0 | Companion package to: A bulk tissue deconvolution method with multi-subject single cell expression reference. This package provide functions to estimate bulk tissue cell type proportions with multi-subject single cell expression as reference. | Mar 25, 2025 | GPL-3 |
| 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-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-packcircles | 0.3.5 | Algorithms to find arrangements of non-overlapping circles. | Mar 25, 2025 | MIT |