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Interactive scientific development environment package for Python. Used for editing, analysis, debugging, and profiling functionality of comprehensive development tool with data exploration, interactive execution, deep inspection, and visualization.
Proper citation: Spyder (RRID:SCR_017585) Copy
https://github.com/ruanjue/smartdenovo
Software tool as de novo assembler for PacBio and Oxford Nanopore data. It produces assembly from all-vs-all raw read alignments without error correction stage. Allows to read overlapping, rescue missing overlaps, identify low-quality regions and chimaera and produce better consensus.
Proper citation: SMARTdenovo (RRID:SCR_017622) Copy
https://github.com/brentp/duphold
Software tool to annotate structural variant calls with sequence depth information that can add or remove confidence to SV predicted to affect copy number. Indicates the presence of a rapid change in depth relative to the regions surrounding the breakpoints. Allows the run time to be nearly independent of the number of variants important for large, jointly called projects with many samples. Annotates structural variant predictions made from both short read and long read data.
Proper citation: duphold (RRID:SCR_016938) Copy
http://ikrsrv1.medma.uni-heidelberg.de/redmine/projects/ummperfusion
Analysis software for dynamic contrast enhanced magnetic resonance images with implementation of a pixel-by-pixel deconvolution approach. It quantifies T1-weighted contrast-enhanced dynamic MR imaging (DCE-MRI) perfusion data as an OsiriX plug-in.
Proper citation: UMMPerfusion (RRID:SCR_015970) Copy
https://github.com/madeluis/GENIST
Software tool as an algorithm to infer gene regulatory networks from spatial and temporal datasets. Spatial dataset or any data that can provide information about coexpression is used by the first step of the algorithm to perform clustering and separate the genes in the network in smaller coexpressed groups. Temporal dataset is used by the second step of the algorithm to infer regulations among the genes, based on Bayesian networks.
Proper citation: GENIST (RRID:SCR_016942) Copy
https://github.com/ABCD-STUDY/redcap-hook-framework
Software tool to organize and deploy custom hooks in a single project or across the entire instance. It features multi-language support for data entry and survey pages, a bar-code for text fields, and highlighting of rows on data entry and survey pages that have been filled out.
Proper citation: redcap-hook-framework (RRID:SCR_016028) Copy
http://www.uimcimes.es/contenidos/golink?p=1
Software toolbox for Statistical Parametric Mapping (SPM) to fit reference-region kinetic models (SRTM, SRTM2, Patlak Reference and Logan Reference Plot) are currently available in QModeling to dynamic PET studies. Used for the analysis of brain imaging data sequences.
Proper citation: QModeling (RRID:SCR_016358) Copy
https://github.com/xsun28/CloudMerge/
Software for merging massive VCF files into a single VCF file or TPED file. Source codes can be slightly modified to fit into other types of sorted merging of Omics data.
Proper citation: CloudMerge (RRID:SCR_016051) Copy
https://www.uke.de/english/research/core-facilities/bioinformatics-core-en.html
Core provides bioinformatics services for researchers at University Medical Center Hamburg Eppendorf and related institutions. Focusing on high throughput sequencing data. Services include data analysis, consulting, software development, and bioinformatical training.
Proper citation: University Medical Center Hamburg-Eppendorf Bioinformatics Core Facility (RRID:SCR_017144) Copy
http://deweylab.biostat.wisc.edu/detonate/
Software tool to evaluate de novo transcriptome assemblies from RNA-Seq data. Consists of RSEM-EVAL and REF-EVAL packages. RSEM-EVAL is reference-free evaluation method. REF-EVAL is reference based and can be used to compare sets of any kinds of genomic sequences.
Proper citation: DETONATE (RRID:SCR_017035) Copy
http://brainarchitecture.org/allen-atlas-brain-toolbox
Software Matlab toolbox for quantitative analysis of digitized brain wide gene expression data from Allen Atlas of adult mouse brain.
Proper citation: Brain Gene Expression Analysis toolbox (RRID:SCR_017438) Copy
https://www.addgene.org/collections/covid-19-resources/
Collections of Addgene plasmids, open access articles, protocols, and other resource collections related to COVID-19 that may be of use to scientists. Ordering or depositing plasmids related to COVID-19 research.
Proper citation: COVID-19 and Coronavirus plasmids and resources (RRID:SCR_018347) Copy
http://fit.genomics.lbl.gov/cgi-bin/myFrontPage.cgi
Web tool for browsing genome wide fitness experiments for diverse bacteria from Deutschbauer lab, the Arkin lab, and collaborators. Collection of mutant phenotypes for bacterial genes of unknown function.
Proper citation: Fitness Browser (RRID:SCR_018981) Copy
List of proteins commonly found in proteomics experiments that are present either by accident or through unavoidable contamination of protein samples. List is based on analysis of current version of GPMDB, as well as suggestions by users. Current version of cRAP in FASTA format can be obtained from the GPM FTP site.
Proper citation: cRAP protein sequences (RRID:SCR_018187) Copy
Desktop application that provides interactive visualization functionality to analyze data from different 10x Genomics solutions. Used to interrogate different views of 10x data to gain insights into underlying biology.
Proper citation: Loupe Browser (RRID:SCR_018555) Copy
Consortium to unite efforts and resources from experts across globe to advance effective, antibody based therapies against novel coronavirus, SARS-CoV-2. Represents multidisciplinary convergence of structural biology, virologists, immunologists, clinicians and bioinformaticians from academic and industry settings. Collects antibodies for testing as part of CoVICS. Contributed antibodies are blinded and will only be known as code name. Antibody contributors will be able to see performance of their own molecules and take part in analysis. Contributors retain ownership of their antibodies and may continue to publish on them using original antibody names. Goal is to determine relative in vitro potency and in vivo efficacy using centralized standardized assays to identify best individual mAbs and rational combinations of mAbs. Consortium will recommend ideal therapeutic molecules for human use to protect vulnerable populations from COVID-19 disease. CoVIC database (CoVIC-DB) will serve as clearinghouse for monoclonal antibodies against SARS-CoV-2. Database will catalog contributed antibodies in searchable resource and provide interactive analysis tools for comparisons among them.
Proper citation: Coronavirus Immunotherapy Consortium (RRID:SCR_018258) Copy
https://metagenote.niaid.nih.gov/
Quick and intuitive way to annotate data from genomics studies including microbiome. Project to aid researchers in applying standardized metadata describing what, where, how, and when of samples collected in genomics study. Collection of METAdata of GEnomics studies on web based NOTEbook. Metadata are stored in centralized repository and validated according to guidelines from Genomics Standard Consortium, which are also supported by repositories and large microbiome initiatives such as NCBI, European Bioinformatics Institute (EBI), and Earth Microbiome Project. Upon request from researchers, data will also be submitted for publication via NCBI Sequence Read Archive (SRA) repository.
Proper citation: METAGENOTE (RRID:SCR_018494) Copy
Core designed for immune monitoring services for clinical and translational studies. Goals include providing standardized, state-of-the art immune monitoring assays at RNA, protein, and cellular level, testing and developing new technologies for immune monitoring, archive, report, and mine data from immune monitoring studies. HIMC uses online database for integration of data from standard HIMC assays, along with de-identified clinical and demographic data.
Proper citation: Stanford University Human Immune Monitoring Center Core Facility (RRID:SCR_018266) Copy
https://broadinstitute.github.io/warp/docs/Pipelines/Optimus_Pipeline/README
Optimus is a pipeline developed by the Data Coordination Platform (DCP) of the Human Cell Atlas (HCA) Project that supports processing of any 3' single-cell and single-nuclei expression data generated with the 10x Genomic v2 or v3 assay. It is an alignment and transcriptome quantification pipeline that corrects cell barcodes, aligns reads to the genome, corrects Unique Molecular Identifiers (UMIs), generates an expression matrix in a UMI-aware manner, calculates summary metrics for genes and cells, detects empty droplets, returns read outputs in BAM format, and returns gene counts in NumPy matrix and Loom matrix formats.
Proper citation: Optimus Pipeline (RRID:SCR_018908) Copy
Web tool for protein-protein docking. Server provides removal of unstructured protein regions, application of attraction or repulsion, accounting for pairwise distance restraints, construction of homo-multimers, consideration of small-angle X-ray scattering data, and location of heparin-binding sites. Six different energy functions can be used, depending on protein type.This protocol describes use of various options, construction of auxiliary restraints files, selection of energy parameters, and analysis of results.
Proper citation: ClusPro (RRID:SCR_018248) Copy
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