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http://sourceforge.net/projects/atlas-link/

Software that implements a greedy algorithm and uses graph theory to link and orient assembled existing contigs quickly and accurately using mate pair information.

Proper citation: Next-gen Sequencing Scaffolding Tool (RRID:SCR_006762) Copy   

•   Source: SciCrunch Registry

http://159.149.160.51/cscan/

Data resource that includes a large collection of genome-wide ChIP-Seq experiments performed on transcription factors (TFs), histone modifications, RNA polymerases and others. Enriched peak regions from the ChIP-Seq experiments are crossed with the genomic coordinates of a set of input genes, to identify which of the experiments present a statistically significant number of peaks within the input genes' loci. The input can be a cluster of co-expressed genes, or any other set of genes sharing a common regulatory profile. Users can thus single out which TFs are likely to be common regulators of the genes, and their respective correlations. Also, by examining results on promoter activation, transcription, histone modifications, polymerase binding and so on, users can investigate the effect of the TFs (activation or repression of transcription) as well as of the cell or tissue specificity of the genes' regulation and expression.

Proper citation: Cscan (RRID:SCR_006756) Copy   

•   Source: SciCrunch Registry

http://bio.math.berkeley.edu/eXpress/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented January 29, 2018.
From website: "Note that the eXpress software is also no longer being developed. We recommend you use kallisto instead." Kallisto can be found at http://pachterlab.github.io/kallisto/.

Software for streaming quantification for high-throughput DNA/RNA sequencing.
Can be used in any application where abundances of target sequences need to be estimated from short reads sequenced from them.

Proper citation: eXpress (RRID:SCR_006873) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/quasr/

A lightweight software pipeline written to process and analyse next-generation sequencing (NGS) data from Illumina, 454, and Ion Torrent platforms. Although originally written for viral data, it is generic enough to work on any NGS dataset. Functions include: duplicate removal, demultiplexing, primer-removal, quality-assurance (QA) graphing, quality control (QC), consensus-generation, minority-variant determination, minority-variant graphing.

Proper citation: QUASR (RRID:SCR_006820) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/simhtsd/

Software that given a reference sequence, will create a large set of short nucleotide reads, simulating the output from today''s high-throughput DNA sequencers, such as the Illumina Genome Analyzer II.

Proper citation: simhtsd (RRID:SCR_006822) Copy   

•   Source: SciCrunch Registry

http://www.webgestalt.org/

Web based gene set analysis toolkit designed for functional genomic, proteomic, and large-scale genetic studies from which large number of gene lists (e.g. differentially expressed gene sets, co-expressed gene sets etc) are continuously generated. WebGestalt incorporates information from different public resources and provides a way for biologists to make sense out of gene lists. This version of WebGestalt supports eight organisms, including human, mouse, rat, worm, fly, yeast, dog, and zebrafish.

Proper citation: WebGestalt: WEB-based GEne SeT AnaLysis Toolkit (RRID:SCR_006786) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/virmid/

A Java based variant caller designed for disease-control matched samples. Virmid is also specialized for identifying potential within individual contamination where the disease sample cannot be purified enough. While the SNP calling rate is severely compromised with this heterogeneity, Virmid can uncover SNPs with low allele frequency by considering the level of contamination (alpha). The important features of Virmid are: * Estimation of accurate proporation of control sample in a (mixed) disease sample * Improved SNP and somatic mutation calling with regard to the estimated proportion

Proper citation: Virmid (RRID:SCR_006780) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/bigpre/

A quality assessment software package for next-genomics sequencing data.

Proper citation: BIGpre (RRID:SCR_006781) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/taxoassignement/

Software tool for the taxonomic assignment of Next Generation Sequencing reads using multiple reference taxonomy.

Proper citation: TaxoAssignement (RRID:SCR_006814) Copy   

•   Source: SciCrunch Registry

http://www.cdc.gov/osels/lspppo/Genetic_Testing_Quality_Practices/Nex-StoCT.html

National workgroup to define platform-independent approaches for establishing technical process elements of a quality management system (QMS) to assure the analytical validity and compliance of next-generation sequencing (NGS) tests with existing regulatory and professional quality standards. The workgroup identified and addressed gaps in quality practices that could compromise the quality of both clinical laboratory services and translational efforts needed to advance the implementation and utility of NGS in clinical settings. The workgroup was composed of experts with knowledge of and experience with NGS and included clinical laboratory directors, clinicians, platform and software developers and informaticians, as well as individuals actively engaged in NGS guideline development from accreditation bodies and professional organizations. Representatives from US government agencies also participated. These guidelines address four topics that are components of quality management in a clinical environment: (i) test validation, (ii) quality control (QC) procedures to assure and maintain accurate test results, (iii) the independent assessment of test performance through proficiency testing (PT) or alternative approaches and (iv) reference materials (RMs). Discussions were limited to the analytic and informatics processes required for accurate variant calling. The workgroup did not address how variants are prioritized, interpreted or reported.

Proper citation: Nex-StoCT (RRID:SCR_006777) Copy   

•   Source: SciCrunch Registry

http://biit.cs.ut.ee/gprofiler/

Web server for functional enrichment analysis and conversions of gene lists. Web based tool for functional profiling of gene lists from large scale experiments. Has web interface with powerful visualization. Used for analyzing data from any organism.

Proper citation: g:Profiler (RRID:SCR_006809) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/2.12/bioc/html/seqbias.html

Software package that implements a model of per-position sequencing bias in high-throughput sequencing data using a simple Bayesian network, the structure and parameters of which are trained on a set of aligned reads and a reference genome sequence.

Proper citation: seqbias (RRID:SCR_006832) Copy   

•   Source: SciCrunch Registry

http://genome.ucsc.edu/ENCODE

Encyclopedia of DNA elements consisting of list of functional elements in human genome, including elements that act at protein and RNA levels, and regulatory elements that control cells and circumstances in which gene is active. Enables scientific and medical communities to interpret role of human genome in biology and disease. Provides identification of common cell types to facilitate integrative analysis and new experimental technologies based on high-throughput sequencing. Genome Browser containing ENCODE and Epigenomics Roadmap data. Data are available for entire human genome.

Proper citation: ENCODE (RRID:SCR_006793) Copy   

•   Source: SciCrunch Registry

http://www.1000genomes.org/

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

Proper citation: 1000 Genomes: A Deep Catalog of Human Genetic Variation (RRID:SCR_006828) Copy   

•   Source: SciCrunch Registry

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

Data analysis service and software program that perform Operantional Taxonomic Units (OTUs) finding. It uses a three-step clustering for identifying OTUs. The first-step clustering is raw read filtering and trimming. The second step is error-free reads picking.. At the last step, OTU clustering is done at different distanct cutoffs (0.01, 0.02, 0.03... 0.12).

Proper citation: CD-HIT-OTU (RRID:SCR_006983) Copy   

•   Source: SciCrunch Registry

http://www.microrna.org

Database of microRNA target predictions and expression profiles. Target predictions are based on a development of the miRanda algorithm which incorporates current biological knowledge on target rules and on the use of an up-to-date compendium of mammalian microRNAs. MicroRNA expression profiles are derived from a comprehensive sequencing project of a large set of mammalian tissues and cell lines of normal and disease origin. This website enables users to explore: * The set of genes that are potentially regulated by a particular microRNA. * The implied cooperativity of multiple microRNAs on a particular mRNA. * MicroRNA expression profiles in various mammalian tissues. The web resource provides users with functional information about the growing number of microRNAs and their interaction with target genes in many species and facilitates novel discoveries in microRNA gene regulation. The microRNA Target Detection Software, miRanda, is an algorithm for finding genomic targets for microRNAs. This algorithm has been written in C and is available as an open-source method under the GPL., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: microRNA.org (RRID:SCR_006997) Copy   

•   Source: SciCrunch Registry

http://goblet.molgen.mpg.de/cgi-bin/goblet2008/goblet.cgi

Tool that performs annotation based on GO and pathway terms for anonymous cDNA or protein sequences. It uses the species independent GO structure and vocabulary together with a series of protein databases collected from various sites, to perform a detailed GO annotation by sequence similarity searches. The sensitivity and the reference protein sets can be selected by the user. GOblet runs automatically and is available as a public service on our web server. GOblet expects query sequences to be in FASTA-Format (with header-lines). Protein and nucleotide sequences are accepted. Total size of all sequences submitted per request should not be larger than 50kb currently. For security reasons: Larger post's will be rejected. Due to limited capacities the queries may be processed in batches depending on the server load. The output of the BLAST job is filtered automatically and the relevant hits are displayed. In addition, the respective GO-terms are shown together with the complete GO-hierarchy of parent terms., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GOblet (RRID:SCR_006998) Copy   

•   Source: SciCrunch Registry

http://bioinfo.cau.edu.cn/agriGO/

A web-based tool and database for the gene ontology analysis. Its focus is on agricultural species and is user-friendly. The agriGO is designed to provide deep support to agricultural community in the realm of ontology analysis. Compared to other available GO analysis tools, unique advantages and features of agriGO are: # The agriGO especially focuses on agricultural species. It supports 45 species and 292 datatypes currently. And agriGO is designed as an user-friendly web server. # New tools including PAGE (Parametric Analysis of Gene set Enrichment), BLAST4ID (Transfer IDs by BLAST) and SEACOMPARE (Cross comparison of SEA) were developed. The arrival of these tools provides users with possibilities for data mining and systematic result exploration and will allow better data analysis and interpretation. # The exploratory capability and result visualization are enhanced. Results are provided in different formats: HTML tables, tabulated text files, hierarchical tree graphs, and flash bar graphs. # In agriGO, PAGE and SEACOMPARE can be used to carry out cross-comparisons of results derived from different data sets, which is very important when studying multiple groups of experiments, such as in time-course research. Platform: Online tool, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: agriGO (RRID:SCR_006989) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/intact

Open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions. Direct user submissions of molecular interaction data are encouraged, which may be deposited prior to publication in a peer-reviewed journal. The IntAct Database contains (Jun. 2014): * 447368 Interactions * 33021 experiments * 12698 publications * 82745 Interactors IntAct provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows "zooming in" on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available.

Proper citation: IntAct (RRID:SCR_006944) Copy   

•   Source: SciCrunch Registry

http://pga.mgh.harvard.edu/primerbank/

Database of human and mouse primer pairs for gene expression analysis by polymerase chain reaction (PCR) and quantitative PCR (qPCR). A total of 306,800 primers covering most known human and mouse genes can be accessed from the PrimerBank database, together with information on these primers such as T(m), location on the transcript and amplicon size. For each gene, at least one primer pair has been designed and in many cases alternative primer pairs exist. Primers have been designed to work under the same PCR conditions, thus facilitating high-throughput QPCR. All primers in PrimerBank were carefully designed to ensure gene specificity. All experimental validation data for mouse primers are available from PrimerBank. You can submit your primers. They will be added to the database once they are properly QCd.

Proper citation: PrimerBank (RRID:SCR_006898) Copy   

•   Source: SciCrunch Registry