Tools   Select Another Resource Report Type

https://array.nci.nih.gov/caarray/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on Sep 18, 2018. Open-source, web and programmatically accessible microarray data management system. caArray guides the annotation and exchange of array data using a federated model of local installations whose results are shareable across the cancer Biomedical Informatics Grid (caBIG). caArray furthers translational cancer research through acquisition, dissemination and aggregation of semantically interoperable array data to support subsequent analysis by tools and services on and off the Grid. As array technology advances and matures, caArray will extend its logical library of assay management.

Proper citation: caArray (RRID:SCR_006053) Copy   

•   Source: SciCrunch Registry
  

http://cran.r-project.org/web/packages/MetaQC/

Software for quality control and diagnosis for microarray meta-analysis. Quantitative quality control measures include: (1) internal homogeneity of co-expression structure among studies (internal quality control; IQC); (2) external consistency of co-expression structure correlating with pathway database (external quality control; EQC); (3) accuracy of differentially expressed gene detection (accuracy quality control; AQCg) or pathway identification (AQCp); (4) consistency of differential expression ranking in genes (consistency quality control; CQCg) or pathways (CQCp). For each quality control index, the p-values from statistical hypothesis testing are minus log transformed and PCA biplots were applied to assist visualization and decision. Results generate systematic suggestions to exclude problematic studies in microarray meta-analysis and potentially can be extended to GWAS or other types of genomic meta-analysis. The identified problematic studies can be scrutinized to identify technical and biological causes (e.g. sample size, platform, tissue collection, preprocessing etc) of their bad quality or irreproducibility for final inclusion / exclusion decision.

Proper citation: MetaQC (RRID:SCR_006000) Copy   

•   Source: SciCrunch Registry
  

http://bio-bigdata.hrbmu.edu.cn/diseasemeth/

Human disease methylation database. DiseaseMeth version 2.0 is focused on aberrant methylomes of human diseases. Used for understanding of DNA methylation driven human diseases.

Proper citation: DiseaseMeth (RRID:SCR_005942) Copy   

•   Source: SciCrunch Registry
  

http://sourceforge.net/projects/bless-ec/

Software tool for Bloom-filter-based error correction for next-generation sequencing (NGS) reads. The algorithm produces accurate correction results with much less memory.

Proper citation: BLESS (RRID:SCR_005963) Copy   

•   Source: SciCrunch Registry
  

http://aias.biol.uoa.gr/OMPdb/

A database of Beta-barrel outer membrane proteins from Gram-negative bacteria. The web interface of OMPdb offers the user the ability not only to view the available data, but also to submit advanced queries for text search within the database''s protein entries or run BLAST searches against the database. The most up-to-date version of the database (as well as all past versions) can be downloaded in various formats (flat text, XML format or raw FASTA sequences). For constructing OMPdb, multiple freely accessible resources were combined and a detailed literature search was performed. The classification of OMPdb''s protein entries into families is based mainly on structural and functional criteria. Information included in the database consists of sequence data, as well as annotation for structural characteristics (such as the transmembrane segments), literature references and links to other public databases, features that are unique worldwide. Along with the database, a collection of profile Hidden Markov Models that were shown to be characteristic for Beta-barrel outer membrane proteins was also compiled. This set, when used in combination with our previously developed algorithms (PRED-TMBB, MCMBB and ConBBPRED) will serve as a powerful tool in matters of discrimination and classification of novel Beta-barrel proteins and whole-genome analyses., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: OMPdb (RRID:SCR_006221) Copy   

•   Source: SciCrunch Registry
  

http://www.bioconductor.org/packages/devel/bioc/html/deepSNV.html

Software package that provides quantitative variant callers for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. The algorithm is used for a comparative setup with a control experiment of the same loci and uses a beta-binomial model and a likelihood ratio test to discriminate sequencing errors and subclonal SNVs (single nucleotide variants).

Proper citation: deepSNV (RRID:SCR_006214) Copy   

•   Source: SciCrunch Registry
  

http://evolution.genetics.washington.edu/phylip.html

A free package of software programs for inferring phylogenies (evolutionary trees). The source code is distributed (in C), and executables are also distributed. In particular, already-compiled executables are available for Windows (95/98/NT/2000/me/xp/Vista), Mac OS X, and Linux systems. Older executables are also available for Mac OS 8 or 9 systems.

Proper citation: PHYLIP (RRID:SCR_006244) Copy   

•   Source: SciCrunch Registry
  

https://github.com/RGLab/pepStat

Software for statistical analysis of peptide microarrays. It uses an integrated analytical method for analyzing peptide microarray antibody binding data, from normalization through subject-specific positivity calls and data integration and visualization.

Proper citation: pepStat (RRID:SCR_006240) Copy   

•   Source: SciCrunch Registry
  

http://stormo.wustl.edu/ScerTF

Catalog of over 1,200 position weight matrices (PWMs) for 196 different yeast transcription factors (TFs). They've curated 11 literature sources, benchmarked the published position-specific scoring matrices against in-vivo TF occupancy data and TF deletion experiments, and combined the most accurate models to produce a single collection of the best performing weight matrices for Saccharomyces cerevisiae. ScerTF is useful for a wide range of problems, such as linking regulatory sites with transcription factors, identifying a transcription factor based on a user-input matrix, finding the genes bound/regulated by a particular TF, and finding regulatory interactions between transcription factors. Enter a TF name to find the recommended matrix for a particular TF, or enter a nucleotide sequence to identify all TFs that could bind a particular region.

Proper citation: ScerTF (RRID:SCR_006121) Copy   

•   Source: SciCrunch Registry
  

http://pathogenseq.lshtm.ac.uk/estmoi

A per-based software to estimate multiplicity of infection (MOI) in parasite genomic sequence data. It is primarily developed to address the limitations of current laboratory (PCR) based estimates of multiplicity using high throughput sequence data. It requires a BAM (alignment output of short reads to the reference genome), VCF (a file with information on variant calls) and FASTA (reference genome) files. # Short reads are aligned to a reference genome using BWA, BOWTIE, SMALT or other short read aligners to generate a BAM file. # Single Nucleotide Polymorphisms (SNPs) are then identified using SAMTools/BCFtools and stored in the VCF format. # The reference FASTA file is expected to be indexed using ''samtools faidx'' to generate a *.fai file. estMOI generates files containing MOI estimates for each SNP combinations (file with name *.log) and a summary for all chromosomes (file with name *.txt).

Proper citation: estMOI (RRID:SCR_006192) Copy   

•   Source: SciCrunch Registry
  

http://megasun.bch.umontreal.ca/People/lartillot/www/

A Bayesian Monte Carlo Markov Chain (MCMC) sampler software for phylogenetic reconstruction. Its main distinguishing feature is the underlying probabilistic model, CAT (Lartillot and Philippe, 2004). CAT is an infinite mixture model accounting for site-specific amino-acid or nucleotide preferences. It is well suited to phylogenomic studies using large multigene alignments., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PhyloBayes (RRID:SCR_006402) Copy   

•   Source: SciCrunch Registry
  

http://kobas.cbi.pku.edu.cn/

Web server to identify statistically enriched pathways, diseases, and GO terms for a set of genes or proteins, using pathway, disease, and GO knowledge from multiple famous databases. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). A standalone command line version is also available, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: KOBAS (RRID:SCR_006350) Copy   

•   Source: SciCrunch Registry
  

http://snps.ccbr.utoronto.ca:8080/SNPdryad/

Service to predict deleterious non-synonymous human Single Nucleotide Polymorphisms (SNPs) using only orthologous protein sequences.

Proper citation: SNPdryad (RRID:SCR_006414) Copy   

•   Source: SciCrunch Registry
  

http://cran.r-project.org/web/packages/QCGWAS/

Software tools for (automated and manual) quality control of the results of Genome Wide Association Studies.

Proper citation: QCGWAS (RRID:SCR_006408) Copy   

•   Source: SciCrunch Registry
  

http://loschmidt.chemi.muni.cz/predictsnp/

Consensus classifier tool that combines six of the top performing tools for the prediction of the effects of mutation on protein function. The obtained results are provided together with annotations extracted from the Protein Mutant Database and the UniProt database. A stand-alone version is also available.

Proper citation: PredictSNP (RRID:SCR_006327) Copy   

•   Source: SciCrunch Registry
  

http://omim.org

Online catalog of human genes and genetic disorders, for clinical features, phenotypes and genes. Collection of human genes and genetic phenotypes, focusing on relationship between phenotype and genotype. Referenced overviews in OMIM contain information on all known mendelian disorders and variety of related genes. It is updated daily, and entries contain copious links to other genetics resources.

Proper citation: OMIM (RRID:SCR_006437) Copy   

•   Source: SciCrunch Registry
  

http://sing.ei.uvigo.es/GC/

Tool for extensively testing the discriminatory power of biologically relevant gene sets in microarray data classification. While the user can work with different gene set collections and several microarray data files to configure specific classification experiments, the tool is able to run several tests in parallel. It is able to render valuable information for diagnostic analyses and clinical management decisions based on systematically evaluating custom hypothesis over different data sets using complementary classifiers, a key aspect in clinical research.

Proper citation: GeneCommittee (RRID:SCR_004168) Copy   

•   Source: SciCrunch Registry
  

http://taylorlab.ucsf.edu/software_data.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documentedt on January 10, 2023. Software that implements babel routines for identifying unusual ribosome protected fragment counts given mRNA counts, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Babel (RRID:SCR_004307) Copy   

•   Source: SciCrunch Registry
  

http://code.google.com/p/perm/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software package to perform highly efficient genome scale alignments for hundreds of millions of short reads produced by the ABI SOLiD and Illumina sequencing platforms. It capable of providing full sensitivity for alignments within 4 mismatches for 50bp SOLID reads and 9 mismatches for 100bp Illumina reads.Efficient mapping of short sequencing reads with periodic full sensitive spaced seeds.

Proper citation: PerM (RRID:SCR_004223) Copy   

•   Source: SciCrunch Registry
  

http://www.egappreviews.org/

Initiative to develop a systematic, evidence-based process for evaluating genetic tests and other applications of genomic technology that are rapidly moving from research to use in clinical practice. A key objective of this process is to provide objective, timely, and credible information that is clearly linked to the scientific evidence on specific applications of genetic and genomic tests. The primary focus of EGAPP activities is an independent, nonfederal expert panel, the EGAPP Working Group. Other components of the EGAPP initiative include a federal interagency, the CDC staff and consultants, and an EGAPP initiative evaluation team.

Proper citation: EGAPP (RRID:SCR_004189) Copy   

•   Source: SciCrunch Registry