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http://www.sanger.ac.uk/science/tools/ssaha2-0

A program designed for the efficient mapping of sequence reads onto genomic references. The software is capable of reading most sequencing platforms and giving a range of outputs are supported.

Proper citation: Sequence Search and Alignment by Hashing Algorithm (RRID:SCR_000544) Copy   

•   Source: SciCrunch Registry

http://decgpu.sourceforge.net/homepage.htm

Software tool as parallel and distributed error correction algorithm for high-throughput short reads using CUDA and MPI parallel programming models.

Proper citation: DecGPU (RRID:SCR_000585) Copy   

•   Source: SciCrunch Registry

http://www.bioinf.uni-leipzig.de/Software/RNAplex/

Software tool to rapidly search for short interactions between two long RNAs.

Proper citation: RNAplex (RRID:SCR_002763) Copy   

•   Source: SciCrunch Registry

http://bamview.sourceforge.net/

A free interactive display of read alignments in BAM data files that can be launched with Java Web Start or downloaded. This interactive Java application for visualizing the large amounts of data stored for sequence reads which are aligned against a reference genome sequence can be used in a number of contexts including SNP calling and structural annotation. It has been integrated into Artemis so that the reads can be viewed in the context of the nucleotide sequence and genomic features. The source code is available as part of the Artemis code which can be downloaded from GitHub.

Proper citation: BamView (RRID:SCR_004207) Copy   

•   Source: SciCrunch Registry

http://noble.gs.washington.edu/proj/genomedata/

A format for efficient storage of multiple tracks of numeric data anchored to a genome. The format allows fast random access to hundreds of gigabytes of data, while retaining a small disk space footprint. They have also developed utilities to load data into this format. Retrieving data from this format is more than 2900 times faster than a naive approach using wiggle files. A reference implementation in Python and C components is available here under the GNU General Public License. The software has only been tested on Linux and Mac systems.

Proper citation: Genomedata (RRID:SCR_004544) Copy   

•   Source: SciCrunch Registry

https://github.com/Illumina/strelka/

Software for somatic single nucleotide variant (SNV) and small indel detection from sequencing data of matched tumor-normal samples. Strelka2 germline and somatic small variant caller.

Proper citation: Strelka2 (RRID:SCR_005109) Copy   

•   Source: SciCrunch Registry

http://alchemy.sourceforge.net/

ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes. ALCHEMY is a method for automated calling of diploid genotypes from raw intensity data produced by various high-throughput multiplexed SNP genotyping methods. It has been developed for and tested on Affymetrix GeneChip Arrays, Illumina GoldenGate, and Illumina Infinium based assays. Primary motivations for ALCHEMY''s development was the lack of available genotype calling methods which can perform well in the absence of heterozygous samples (due to panels of inbred lines being genotyped) or provide accurate calls with small sample batches. ALCHEMY differs from other genotype calling methods in that genotype inference is based on a parametric Bayesian model of the raw intensity data rather than a generalized clustering approach and the model incorporates population genetic principles such as Hardy-Weinberg equilibrium adjusted for inbreeding levels. ALCHEMY can simultaneously estimate individual sample inbreeding coefficients from the data and use them to improve statistical inference of diploid genotypes at individual SNPs. The main documentation for ALCHEMY is maintained on the sourceforge-hosted MediaWiki system. Features * Population genetic model based SNP genotype calling * Simultaneous estimation of per-sample inbreeding coefficients, allele frequencies, and genotypes * Bayesian model provides posterior probabilities of genotype correctness as quality measures * Growing number of scripts and supporting programs for validation of genotypes against control data and output reformating needs * Multithreaded program for parallel execution on multi-CPU/core systems * Non-clustering based methods can handle small sample sets for empirical optimization of sample preparation techniques and accurate calling of SNPs missing genotype classes ALCHEMY is written in C and developed on the GNU/Linux platform. It should compile on any current GNU/Linux distribution with the development packages for the GNU Scientific Library (gsl) and other development packages for standard system libraries. It may also compile and run on Mac OS X if gsl is installed.

Proper citation: ALCHEMY (RRID:SCR_005761) Copy   

•   Source: SciCrunch Registry

http://metap.helmholtz-muenchen.de/metap2/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 5,2023. Software tool for processing in metabolomics experiments., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: MetaP (RRID:SCR_014686) Copy   

•   Source: SciCrunch Registry

http://web.cmb.usc.edu/people/alber/Software/tomominer/

Software platform for large-scale cryo electron subtomogram classification, alignment, and averaging.

Proper citation: TomoMiner (RRID:SCR_015045) Copy   

•   Source: SciCrunch Registry

http://www.microbesonline.org/fasttree/

Source code that infers approximately-maximum-likelihood phylogenetic trees from alignments of nucleotide or protein sequences. It uses the Jukes-Cantor or generalized time-reversible (GTR) models of nucleotide evolution and the JTT, WAG, or LG models of amino acid evolution.

Proper citation: FastTree (RRID:SCR_015501) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/lme4/index.html

Software R package. Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue."

Proper citation: lme4 (RRID:SCR_015654) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/EGSEA/

Method developed for RNA-sequencing data. EGSEA combines results from twelve algorithms and calculates collective gene set scores to improve the biological relevance of the highest ranked gene sets.

Proper citation: EGSEA (RRID:SCR_015036) Copy   

•   Source: SciCrunch Registry

http://weizhong-lab.ucsd.edu/cd-hit/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software program for clustering biological sequences with many applications in various fields such as making non-redundant databases, finding duplicates, identifying protein families, filtering sequence errors and improving sequence assembly etc. It is very fast and can handle extremely large databases. CD-HIT helps to significantly reduce the computational and manual efforts in many sequence analysis tasks and aids in understanding the data structure and correct the bias within a dataset. The CD-HIT package has CD-HIT, CD-HIT-2D, CD-HIT-EST, CD-HIT-EST-2D, CD-HIT-454, CD-HIT-PARA, PSI-CD-HIT, CD-HIT-OTU and over a dozen scripts. * CD-HIT (CD-HIT-EST) clusters similar proteins (DNAs) into clusters that meet a user-defined similarity threshold. * CD-HIT-2D (CD-HIT-EST-2D) compares 2 datasets and identifies the sequences in db2 that are similar to db1 above a threshold. * CD-HIT-454 identifies natural and artificial duplicates from pyrosequencing reads. * CD-HIT-OTU cluster rRNA tags into OTUs The usage of other programs and scripts can be found in CD-HIT user''s guide. CD-HIT was originally developed by Dr. Weizhong Li at Dr. Adam Godzik''s Lab at the Burnham Institute (now Sanford-Burnham Medical Research Institute)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: CD-HIT (RRID:SCR_007105) Copy   

•   Source: SciCrunch Registry

http://www.chr7.org

Database containing the DNA sequence and annotation of the entire human chromosome 7, encompassing nearly 158 million nucleotides of DNA and 1917 gene structures, are presented; the most up to date collation of sequence, gene, and other annotations from all databases (eg. Celera published, NCBI, Ensembl, RIKEN, UCSC) as well as unpublished data. To generate a higher order description, additional structural features such as imprinted genes, fragile sites, and segmental duplications were integrated at the level of the DNA sequence with medical genetic data, including 440 chromosome rearrangement breakpoints associated with disease. The objective of this project is to generate a comprehensive description of human chromosome 7 to facilitate biological discovery, disease gene research and medical genetic applications. There are over 360 disease-associated genes or loci on chromosome 7. A major challenge ahead will be to represent chromosome alterations, variants, and polymorphisms and their related phenotypes (or lack thereof), in an accessible way. In addition to being a primary data source, this site serves as a weighing station for testing community ideas and information to produce highly curated data to be submitted to other databases such as NCBI, Ensembl, and UCSC. Therefore, any useful data submitted will be curated and shown in this database. All Chromosome 7 genomic clones (cosmids, BACs, YACs) listed in GBrowser and in other data tables are freely distributed.

Proper citation: Chromosome 7 Annotation Project (RRID:SCR_007134) Copy   

•   Source: SciCrunch Registry

http://www.thebiogrid.org/

Curated protein-protein and genetic interaction repository of raw protein and genetic interactions from major model organism species, with data compiled through comprehensive curation efforts.

Proper citation: Biological General Repository for Interaction Datasets (BioGRID) (RRID:SCR_007393) Copy   

•   Source: SciCrunch Registry

http://enhancer.lbl.gov/

Resource for experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Most of these noncoding elements were selected for testing based on their extreme conservation in other vertebrates or epigenomic evidence (ChIP-Seq) of putative enhancer marks. Central public database of experimentally validated human and mouse noncoding fragments with gene enhancer activity as assessed in transgenic mice. Users can retrieve elements near single genes of interest, search for enhancers that target reporter gene expression to particular tissue, or download entire collections of enhancers with defined tissue specificity or conservation depth.

Proper citation: VISTA Enhancer Browser (RRID:SCR_007973) Copy   

•   Source: SciCrunch Registry

http://t1dbase.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 26,2019. In October 2016, T1DBase has merged with its sister site ImmunoBase (https://immunobase.org). Documented on March 2020, ImmunoBase ownership has been transferred to Open Targets (https://www.opentargets.org). Results for all studies can be explored using Open Targets Genetics (https://genetics.opentargets.org). Database focused on genetics and genomics of type 1 diabetes susceptibility providing a curated and integrated set of datasets and tools, across multiple species, to support and promote research in this area. The current data scope includes annotated genomic sequences for suspected T1D susceptibility regions; genetic data; microarray data; and global datasets, generally from the literature, that are useful for genetics and systems biology studies. The site also includes software tools for analyzing the data.

Proper citation: T1DBase (RRID:SCR_007959) Copy   

•   Source: SciCrunch Registry

http://qiime.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data, but also supporting analysis of other types of data. QIMME analyzes and transforms raw sequencing data generated on Illumina or other platforms to publication quality graphics and statistics.

Proper citation: QIIME (RRID:SCR_008249) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/genbank/dbest/

Database as a division of GenBank that contains sequence data and other information on single-pass cDNA sequences, or Expressed Sequence Tags, from a number of organisms.

Proper citation: dbEST (RRID:SCR_008132) Copy   

•   Source: SciCrunch Registry

http://www.baderlab.org/Software/ActiveDriver

A statistical method for interpreting variations in protein sequence (e.g. coding SNPs in the population, SNVs in cancer genomes) in the context of protein post-translational signaling modifications.

Proper citation: ActiveDriver (RRID:SCR_008104) Copy   

•   Source: SciCrunch Registry