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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
Software package to detect and quantify local splicing variations (LSV) from RNA-Seq data. Used to automatically detect and downweight outliers in RNA-Seq datasets with replicates for differential splicing (SD) analysis.
Proper citation: MAJIQ (RRID:SCR_016706) Copy
Python library for materials analysis codes. Defines core object representations for structures and molecules.
Proper citation: Pymatgen (RRID:SCR_016565) Copy
Software tool for assay data analysis.
Proper citation: MyAssays (RRID:SCR_016562) Copy
Web application for integrated analysis and interactive visualization of RNA interference (RNAi) screening data.
Proper citation: CARD (RRID:SCR_016602) Copy
https://github.com/xia-lab/MetaboAnalystR
Software R package for comprehensive analysis of metabolomics data. Contains the R functions and libraries underlying MetaboAnalyst web server, including functions for metabolomic data analysis, visualization, and functional interpretation.
Proper citation: MetaboAnalystR (RRID:SCR_016723) Copy
http://imagej.net/Simple_Neurite_Tracer
Software tool for reconstruction, visualization and analysis of neuronal processes .Fiji's framework for semi-automated tracing of neurons and other tube-like structures (blood vessels) through 3D image stacks.
Proper citation: Simple Neurite Tracer (RRID:SCR_016566) Copy
Software tools for compound-centric data mining and navigation. Used to identify compounds in overlapping and co-eluting peaks with feature extraction and correlation algorithms for chromatographic separation. Used for separating true signals from noise.
Proper citation: Agilent MassHunter WorkStation - Qualitative Analysis for GC/MS (RRID:SCR_016657) Copy
https://visrsoftware.github.io/
Software as an R-based visual framework for analysis of sequencing datasets. Provides a framework for integrative and interactive analyses.
Proper citation: VisR (RRID:SCR_016658) Copy
https://software.broadinstitute.org/gatk/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 18th,2023. Software package for genome analysis. Used for analysis of next generation genomic data in cancer.
Proper citation: IndelGenotyper (RRID:SCR_016663) Copy
https://bitbucket.org/biobakery/biobakery/wiki/Home
Analysis environment and collection of individual software tools to process raw shotgun metagenome or metatranscriptome sequencing data for quantitative microbial community profiling. Used for a metaomics data analysis., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: biobakery (RRID:SCR_016596) Copy
https://github.com/vaklip/rsfmri_fconn
Software program for preprocessing resting state functional magnetic resonance imaging (rsfMRI) measurements and calculating region of interest based whole brain functional connectivity.
Proper citation: rsfMRI_fconn calculation (RRID:SCR_016591) Copy
Cloud based standardised European e-infrastructure for metabolomics and phenomics data processing, analysis and information mining on public or private cloud providers. Used for large scale computing for medical metabolomics.
Proper citation: PhenoMeNal (RRID:SCR_016605) Copy
https://niaid.github.io/spice/
Software application for data mining and visualization. Used for analyzes of large FLOWJO data sets from polychromatic flow cytometry and organizing the normalized data graphically.
Proper citation: SPICE (RRID:SCR_016603) Copy
https://joinsolver.niaid.nih.gov
Software tool to analyze human immunoglobulin V(D)J recombination and performing Ig nucleotide and amino acid alignment, as well as extensive mutation and Complementarity Determining Region 3 (CDR3H) analysis.
Proper citation: JOINSOLVER (RRID:SCR_016619) Copy
https://www.niaid.nih.gov/research/simmune-project
Software package to define the interactions between individual molecules in a large network or the behaviors of cells in response to external signals. It consists of three components: Modeler, Cell Designer and Simulator.
Proper citation: Simmune (RRID:SCR_016618) Copy
https://bioconductor.org/packages/release/bioc/html/riboSeqR.html
Software tool for analysis of sequencing data from ribosome profiling experiments. Used for plotting functions, frameshift detection and parsing of sequencing data from ribosome profiling experiments.
Proper citation: riboSeqR (RRID:SCR_016947) Copy
https://bioconductor.org/packages/release/bioc/html/Rsubread.html
Software R package for sequence alignment and counting for R. Used for analyses of second and third generation sequencing data, for read mapping, read counting, SNP calling, short and long read alignment, quantification and mutation discovery. Includes assessment of sequence reads, read alignment, read summarization, exon-exon junction detection, fusion detection, detection of short and long indels, absolute expression calling and SNP calling. Can be used with reads generated from any of the major sequencing platforms including Illumina GA/HiSeq/MiSeq, Roche GS-FLX, ABI SOLiD and LifeTech Ion PGM/Proton sequencers.
Proper citation: Rsubread (RRID:SCR_016945) Copy
https://bioconductor.org/packages/release/bioc/html/scran.html
Software package for low-level analyses of single-cell RNA-seq data. Used for quality control, data exploration and normalization, cell cycle phase assignment, identification of highly variable and correlated genes, clustering into subpopulations and marker gene detection.
Proper citation: scran (RRID:SCR_016944) Copy
http://bioconductor.org/packages/release/bioc/html/ConsensusClusterPlus.html
Software written in R for determining cluster count and membership by stability evidence in unsupervised analysis. Provides quantitative and visual stability evidence for estimating the number of unsupervised classes in a dataset with item tracking, item consensus and cluster consensus plots.
Proper citation: ConsensusClusterPlus (RRID:SCR_016954) Copy
https://github.com/fyz11/MOSES
Computational Python library for the motion analysis of biological single-cell and collective motion for high content screens. Framework to quantify and discover cellular motion phenotypes.
Proper citation: Motion Sensing Superpixels (MOSES) (RRID:SCR_016839) Copy
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