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http://gigadb.org/dataset/100360

Method for uncovering mutations from RNA sequencing datasets that could be useful in further functional analysis. It also allows orthogonal validation of DNA-based mutation discovery by providing complementary sequence variation analysis from paired RNA/DNA sequencing data sets.

Proper citation: VaDiR (RRID:SCR_015797) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/L1000CDS2

LINCS L1000 characteristic direction signatures search engine. Software tool to find consensus signatures that match user’s input gene lists or input signatures. Underlying dataset is LINCS L1000 small molecule expression profiles generated at Broad Institute by Connectivity Map team. Differentially expressed genes of these profiles were calculated using multivariate method called Characteristic Direction.

Proper citation: L1000 Characteristic Direction Signature Search Engine (RRID:SCR_016177) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/Harmonizome/

Web application that allows for searching, visualization, and prediction about genes and proteins. It contains a collection of processed datasets gathered to serve and mine knowledge about genes and proteins from major online resources.

Proper citation: Harmonizome (RRID:SCR_016176) Copy   

•   Source: SciCrunch Registry

http://statistika.mfub.bg.ac.rs/interactive-linegraph/

Interactive web based tool for creating line graphs for scientific publications. Users can view different summary statistics, examine lines for any individual in data, focus on time points or groups of interest, and view changes between any two time points and conditions.

Proper citation: Interactive Line Graph (RRID:SCR_018334) Copy   

•   Source: SciCrunch Registry

https://cadd.gs.washington.edu/

Web tool for predicting deleteriousness of variants throughout human genome. Software tool for scoring deleteriousness of single nucleotide variants as well as insertion and deletions variants in human genome.

Proper citation: Combined Annotation Dependent Depletion (RRID:SCR_018393) Copy   

•   Source: SciCrunch Registry

https://geodacenter.github.io/

Software program for spatial analysis for non geographic information systems specialists. Includes functionality ranging from simple mapping to exploratory data analysis, visualization of global and local spatial autocorrelation, and spatial regression.

Proper citation: GeoDa (RRID:SCR_018559) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://github.com/qiicr/dcmqi

Software library to help with the conversion between imaging research formats and the standard DICOM representation for image analysis results. Used to implement conversion of the data stored in commonly used research formats into the standard DICOM representation. Available as a precompiled binary package for every major operating system, as a Docker image, and as an extension to 3D Slicer.

Proper citation: dcmqi (RRID:SCR_016933) Copy   

•   Source: SciCrunch Registry

http://marrvel.org/

Web tool to search multiple public variant databases simultaneously and provide a unified interface to facilitate the search process. Used for integration of human and model organism genetic resources to facilitate functional annotation of the human genome. Used for analysis of human genes and variants by cross-disciplinary integration of records available in public databases to facilitate clinical diagnosis and basic research.

Proper citation: MARRVEL (RRID:SCR_016871) Copy   

•   Source: SciCrunch Registry

https://github.com/hakyimlab/PrediXcan

Software tool to detect known and novel genes associated with disease traits and provide insights into the mechanism of these associations. Used to test the molecular mechanisms through which genetic variation affects phenotype.

Proper citation: PrediXcan (RRID:SCR_016739) Copy   

•   Source: SciCrunch Registry

https://github.com/yarden/MISO/blob/fastmiso/docs/source/sashimi.rst

Software tool for quantitative visualization of aligned RNA-Seq reads that enables quantitative comparison of exon usage across samples or experimental conditions.

Proper citation: Sashimiplot (RRID:SCR_016861) Copy   

•   Source: SciCrunch Registry

https://github.com/BlaisProteomics/mzStudio

Software tool for proteomics data analysis, visualization, and notebook application. Dynamic digital canvas for user driven interrogation of mass spectrometry data. Operating system Unix/Linux, Windows.

Proper citation: mzStudio (RRID:SCR_017088) Copy   

•   Source: SciCrunch Registry

https://combine-lab.github.io/salmon/

Software tool for quantifying expression of transcripts using RNA-seq data. Provides fast and bias-aware quantification of transcript expression. Transcriptome-wide quantifier to correct for fragment GC-content bias.

Proper citation: Salmon (RRID:SCR_017036) Copy   

•   Source: SciCrunch Registry

https://www.nature.com/articles/s41467-018-03367-w

Nanodroplet processing platform for deep and quantitative proteome profiling of 10 to 100 mammalian cells. It enhances efficiency and recovery of sample processing by downscaling processing volumes.

Proper citation: nanoPOTS (RRID:SCR_017129) Copy   

•   Source: SciCrunch Registry

http://caintegrator-info.nci.nih.gov/rembrandt

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. REMBRANDT is a data repository containing diverse types of molecular research and clinical trials data related to brain cancers, including gliomas, along with a wide variety of web-based analysis tools that readily facilitate the understanding of critical correlations among the different data types. REMBRANDT aims to be the access portal for a national molecular, genetic, and clinical database of several thousand primary brain tumors that is fully open and accessible to all investigators (including intramural and extramural researchers), as well as the public at-large. The main focus is to molecularly characterize a large number of adult and pediatric primary brain tumors and to correlate those data with extensive retrospective and prospective clinical data. Specific data types hosted here are gene expression profiles, real time PCR assays, CGH and SNP array information, sequencing data, tissue array results and images, proteomic profiles, and patients'''' response to various treatments. Clinical trials'''' information and protocols are also accessible. The data can be downloaded as raw files containing all the information gathered through the primary experiments or can be mined using the informatics support provided. This comprehensive brain tumor data portal will allow for easy ad hoc querying across multiple domains, thus allowing physician-scientists to make the right decisions during patient treatments., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Repository of molecular brain neoplasia data (RRID:SCR_004704) Copy   

•   Source: SciCrunch Registry

http://smd.princeton.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 17, 2021. Database to store, annotate, view, analyze and share microarray data. It provides registered users access to their own data, provides users access to public data, and tools with which to analyze those data, to any public user anywhere in the world. The GenePattern software package has been incorporated directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability. SMD search options allow the user to Search By Experiments, Search By Datasets, or Search By Gene Names. Web services are provided using common standards, such as Simple Object Access Protocol (SOAP). This enables both local and remote researchers to connect to an installation of the database and retrieve data using pre-defined methods, without needing to resort to use of a web browser.

Proper citation: SMD (RRID:SCR_004987) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/gsea/

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

Proper citation: Gene Set Enrichment Analysis (RRID:SCR_003199) Copy   

•   Source: SciCrunch Registry

http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/

Software R package for weighted correlation network analysis. WGCNA is also available as point-and-click application. Unfortunately this application is not maintained anymore. It is known to have compatibility problems with R-2.8.x and newer, and the methods it implements are not all state of the art., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Weighted Gene Co-expression Network Analysis (RRID:SCR_003302) Copy   

•   Source: SciCrunch Registry

http://caintegrator-info.nci.nih.gov/rembrandt

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 28,2023. An initiative to develop a molecular classification schema that is both clinically and biologically meaningful, based on gene expression and genomic data from tumors (Gliomas) of patients who will be prospectively followed through natural history and treatment phase of their illness. The study will also explore gene expression profiles to determine the responsiveness of the patients and correlate with discrete chromosomal abnormalities. The initiative was designed to obtain a large amount of molecular data on DNA and RNA of freshly collected tumor samples that were collected, processed and analyzed in a standardized fashion to allow for large-scale cross sample analysis. The sample collection is accompanied by careful and prospective clinical data acquisition, allowing a variety of matched molecular and clinical data permitting a wide variety of analyses. GMDI has accrued fresh frozen tumors in the retrospective phase (all from the Henry Ford Hospital, without germline DNA) and fresh frozen tumors in the prospective phase (from a variety of institutions). In addition to characterizing the samples from patients enrolled in GMDI, the microarray group has generated genomic-scale analyses of the many human and canine glioma initiating cells/glioma stem cells (GIC/GSC) lines, as well as many canine and murine normal neural stem cell (NSC) lines produced in laboratory.

Proper citation: Glioma Molecular Dignostic Initiatives (RRID:SCR_003329) Copy   

•   Source: SciCrunch Registry

http://cabig.cancer.gov

THIS RESOURCE IS NO LONGER IN SERVICE, documented July 19, 2016. It has been integrated into the National Cancer Informatics Program (NCIP). The National Cancer Institute launched the cancer Biomedical Informatics Grid (caBIG) to create a virtual network of interconnected data, individuals, and organizations that worked together to redefine how cancer research is conducted. caBIG capabilities allowed researchers and clinicians to collaborate more effectively so that complex research questions might be asked and answered faster and more effectively. The mission of caBIG was to develop a truly collaborative information network that accelerated the discovery of new approaches for the detection, diagnosis, treatment, and prevention of cancer, ultimately improving patient outcomes.

Proper citation: Cancer Biomedical Informatics Grid (RRID:SCR_003328) Copy   

•   Source: SciCrunch Registry