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https://github.com/PGB-LIV/VAPPER

Software tool for analysis of variant antigens in African trypanosomes. Used for quantitative analysis of antigenic diversity in systems data of genomes, transcriptomes, and proteomes, called Variant Antigen Profiling to understand how antigenic diversity relates to clinical outcome, how antigen genes may be used as epidemiological markers of virulence, and in measuring gene expression during experimental infections.

Proper citation: VAPPER (RRID:SCR_016993) Copy   

•   Source: SciCrunch Registry

https://www.sciencescott.com/pyminer

Software tool to automate cell type identification, cell type-specific pathway analyses, graph theory-based analysis of gene regulation, and detection of autocrine-paracrine signaling networks. Finds Gene and Autocrine-Paracrine Networks from Human Islet scRNA-Seq.

Proper citation: PyMINEr (RRID:SCR_016990) Copy   

•   Source: SciCrunch Registry

https://sourceforge.net/projects/jtreeview/

Software as a cross platform gene expression visualization tool. Extensible viewer for microarray data in the PCL or CDT format. Interactive display of clustered gene expression data. Java application for visualizing large data matrices. It can load a dataset, cluster it, browse it, customize its appearance and export it into a figure.

Proper citation: Java Treeview (RRID:SCR_016916) Copy   

•   Source: SciCrunch Registry

https://pachterlab.github.io/sleuth/about

Software tool for analysis of RNA-Seq experiments for which transcript abundances have been quantified with kallisto. Used for the differential analysis of gene expression data that utilizes bootstrapping in conjunction with response error linear modeling to decouple biological variance from inferential variance.

Proper citation: sleuth (RRID:SCR_016883) Copy   

•   Source: SciCrunch Registry

http://www.bx.psu.edu/~giardine/vision/

International project to analyze mouse and human hematopoiesis, and provide a tractable system with clear clinical significance and importance to NIDDK. Collection of information from the flood of epigenomic data on hematopoietic cells as catalogs of validated regulatory modules, quantitative models for gene regulation, and a guide for translation of research insights from mouse to human.

Proper citation: ValIdated Systematic IntegratiON of epigenomic data (RRID:SCR_016921) Copy   

•   Source: SciCrunch Registry

https://github.com/flo-compbio/xlmhg

Software Python package as a semiparametric test for enrichment in ranked lists. Used for determining gene set enrichment.

Proper citation: XL-mHG (RRID:SCR_016846) Copy   

•   Source: SciCrunch Registry

http://biotecnun.unav.es:8080/app/TranscriptAchilles

Software genome-wide tool to predict transcript biomarkers of gene essentiality in cancer. This tool can be used to predict new potential target genes with their corresponding biomarkers (either transcript or gene expression).

Proper citation: TranscriptAchilles (RRID:SCR_016849) Copy   

•   Source: SciCrunch Registry

https://github.com/KhiabanianLab/TuBA

Software tool as graph based unsupervised biclustering algorithm to identify alterations in tumors based on hypothesis that gene pairs relevant to clinical process share statistically significant number of samples with extreme expression.

Proper citation: Tunable Biclustering Algorithm (RRID:SCR_017121) Copy   

•   Source: SciCrunch Registry

http://pklab.med.harvard.edu/scde/pagoda.links.html

Software tool for analyzing transcriptional heterogeneity to detect statistically significant ways in which measured cells can be classified. Used to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability among measured cells.

Proper citation: PAGODA (RRID:SCR_017099) Copy   

•   Source: SciCrunch Registry

https://github.com/dgrun/RaceID

Algorithm for identification of rare and abundant cell types from single cell transcriptome data. Based on transcript counts obtained with unique molecular identifies. Used for discovering rare cell types and corresponding marker genes in healthy and diseased organs. Operating system Unix/Linux, Mac OS, Windows.

Proper citation: RaceID (RRID:SCR_017045) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/goseq.html

Software application for performing Gene Ontology analysis on RNAseq data and other length biased data. Used to reduce complexity and highlight biological processes in genome wide expression studies.

Proper citation: Goseq (RRID:SCR_017052) Copy   

•   Source: SciCrunch Registry

https://pcago.bioinf.uni-jena.de/

Interactive web service for analysis of RNA-Seq read count data with principal component analysis (PCA) and agglomerative clustering. Includes features like read count normalization, filtering read counts by gene annotation and visualization options.

Proper citation: PCAGO (RRID:SCR_017033) Copy   

•   Source: SciCrunch Registry

https://github.com/powellgenomicslab/ascend

Software R package for analysis of single cell RNA-seq expression, normalization and differential expression data. Provides framework to perform cell and gene filtering, quality control, normalization, dimension reduction, clustering, differential expression, and visualization functions.

Proper citation: ascend (RRID:SCR_017257) Copy   

•   Source: SciCrunch Registry

https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/what-is-cell-ranger

Software tool as set of analysis pipelines that process chromium single cell RNA-seq output to align reads, generate feature-barcode matrices and perform clustering and gene expression analysis by 10xGenomics.

Proper citation: Cell Ranger (RRID:SCR_017344) Copy   

•   Source: SciCrunch Registry

http://pathwaynet.princeton.edu/

Web user interface for interaction predictions of human gene networks and integrative analysis of user data types that takes advantage of data from diverse tissue and cell-lineage origins. Predicts presence of functional association and interaction type among human genes or its protein products on whole genome scale. Used to analyze experimetnal gene in context of interaction networks.

Proper citation: PathwayNet (RRID:SCR_017353) Copy   

•   Source: SciCrunch Registry

https://www.hmtphenome.uniba.it

Collection of data about variants, genes, phenotypes and diseases involved in mitochondrial functionality. Users can search for variant position, gene, phenotype or disease and retrieve all related information through integrated network of biological entities.

Proper citation: HmtPhenome (RRID:SCR_017289) Copy   

•   Source: SciCrunch Registry

https://scfind.sanger.ac.uk/

Software R package as search tool for single cell RNA-seq data by gene lists. Builds index from scRNA-seq datasets which organizes information in suitable and compact manner so that datasets can be very efficiently searched for either cells or cell types in which given list of genes is expressed.

Proper citation: Scfind (RRID:SCR_017339) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/Glimma.html

Software package for interactive graphics for gene expression analysis. Generates interactive visualisations for analysis of RNA-sequencing data.

Proper citation: Glimma (RRID:SCR_017389) Copy   

•   Source: SciCrunch Registry

https://github.com/SionBayliss/PIRATE

Software pangenomics toolbox for clustering diverged orthologues in bacteria. Used to identify and classify orthologous gene families in bacterial pangenomes over wide range of sequence similarity thresholds.

Proper citation: PIRATE (RRID:SCR_017265) Copy   

•   Source: SciCrunch Registry

http://sift.bii.a-star.edu.sg/

Data analysis service to predict whether an amino acid substitution affects protein function based on sequence homology and the physical properties of amino acids. SIFT can be applied to naturally occurring nonsynonymous polymorphisms and laboratory-induced missense mutations. (entry from Genetic Analysis Software) Web service is also available.

Proper citation: SIFT (RRID:SCR_012813) Copy   

•   Source: SciCrunch Registry