Searching the RRID Resource Information Network

Our searching services are busy right now. Please try again later

  • Register
X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X

Leaving Community

Are you sure you want to leave this community? Leaving the community will revoke any permissions you have been granted in this community.

No
Yes

SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

Search

Type in a keyword to search

On page 83 showing 1641 ~ 1660 out of 2,818 results
Snippet view Table view Download Top 1000 Results
Click the to add this resource to a Collection
  • RRID:SCR_005238

    This resource has 1+ mentions.

http://archive.gersteinlab.org/proj/rnaseq/IQSeq/

Software for integrated Isoform Quanti?cation Analysis based on A Partial Sampling Framework.

Proper citation: IQSeq (RRID:SCR_005238) Copy   


  • RRID:SCR_005199

    This resource has 500+ mentions.

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

Software that characterizes coexisting subpopulations (SPs) in a tumor using copy number and allele frequencies derived from exome- or whole genome sequencing input data. The model amplifies the statistical power to detect coexisting genotypes, by fully exploiting run-specific tradeoffs between depth of coverage and breadth of coverage. ExPANdS predicts the number of clonal expansions, the size of the resulting SPs in the tumor bulk, the mutations specific to each SP and tumor purity. The main function runExPANdS provides the complete functionality needed to predict coexisting SPs from single nucleotide variations (SNVs) and associated copy numbers. The robustness of the subpopulation predictions by ExPANdS increases with the number of mutations provided. It is recommended that at least 200 mutations are used as an input to obtain stable results.

Proper citation: ExPANdS (RRID:SCR_005199) Copy   


  • RRID:SCR_005232

    This resource has 1+ mentions.

http://compbio.cs.toronto.edu/ireckon/

An algorithm for the simultaneous isoform reconstruction and abundance estimation. In addition to modelling novel isoforms, multi-mapped reads and read duplicates, this method takes into account the possible presence of unspliced pre-mRNA and intron retention. iReckon only requires a set of transcription start and end sites, but can use known full isoforms to improve sensitivity. Starting from the set of nearly all possible isoforms, iReckon uses a regularized EM algorithm to determine those actually present in the sequenced sample, together with their abundances. iReckon is multi-threaded to increase efficiency in all its time consuming steps.

Proper citation: iReckon (RRID:SCR_005232) Copy   


  • RRID:SCR_005191

    This resource has 5000+ mentions.

http://snpeff.sourceforge.net/

Genetic variant annotation and effect prediction software toolbox that annotates and predicts effects of variants on genes (such as amino acid changes). By using standards, such as VCF, SnpEff makes it easy to integrate with other programs.

Proper citation: SnpEff (RRID:SCR_005191) Copy   


  • RRID:SCR_005108

    This resource has 100+ mentions.

http://gmt.genome.wustl.edu/somatic-sniper/current/

Software program to identify single nucleotide positions that are different between tumor and normal (or, in theory, any two bam files). It takes a tumor bam and a normal bam and compares the two to determine the differences. It outputs a file in a format very similar to Samtools consensus format. It uses the genotype likelihood model of MAQ (as implemented in Samtools) and then calculates the probability that the tumor and normal genotypes are different. This probability is reported as a somatic score. The somatic score is the Phred-scaled probability (between 0 to 255) that the Tumor and Normal genotypes are not different where 0 means there is no probability that the genotypes are different and 255 means there is a probability of 1 ? 10(255/-10) that the genotypes are different between tumor and normal. This is consistent with how the SAM format reports such probabilities. It is currently available as source code via github or as a Debian APT package.

Proper citation: SomaticSniper (RRID:SCR_005108) Copy   


  • RRID:SCR_005226

    This resource has 1+ mentions.

https://code.google.com/p/simrare/

A stand-alone executable software with user-friendly graphical interface implemented in Python/C++ for rare variant association studies. It is designed as a unified simulation framework to provide an unbiased and easy manner to evaluate association methods, including novel methods, under a broad range of choice of biological contexts. It consists of three modules, variant data simulator, genotype/phenotype generator and association method evaluator. SimRare generates variant data for gene regions using forward-time simulation which incorporates realistic population demographic and evolutionary scenarios. For phenotype data it is capable of generating both case-control and quantitative traits. The phenotypic effects of variants can be detrimental, protective or non-causal. SimRare has a graphical user interface which allows for easy entry of genetic and phenotypic parameters. Simulated data can be written into external files in a standard format. For novel association method implemented in R it can be imported into SimRare, which has been equipped built in functions to evaluate performance of new method and visually compare it with currently available ones in an unbiased manner.

Proper citation: SimRare (RRID:SCR_005226) Copy   


  • RRID:SCR_005107

    This resource has 50+ mentions.

http://www.broadinstitute.org/gatk/gatkdocs/org_broadinstitute_sting_gatk_walkers_indels_SomaticIndelDetector.html

Tool for calling indels in Tumor-Normal paired sample mode.

Proper citation: SomaticIndelDetector (RRID:SCR_005107) Copy   


  • RRID:SCR_005101

    This resource has 1+ mentions.

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

A novel algorithmic framework for the integrated analysis of RNA-Seq and Whole Genome Shotgun Sequencing (WGSS) data for the purposes of discovering genomic rearrangements and aberrant transcripts. The Comrad framework leverages the advantages of both RNA-Seq and WGSS data, providing accurate classification of rearrangements as expressed or not expressed and accurate classification of the genomic or non-genomic origin of aberrant transcripts. A major benefit of Comrad is its ability to accurately identify aberrant transcripts and associated rearrangements using low coverage genome data. As a result, a Comrad analysis can be performed at a cost comparable to that of two RNA-Seq experiments, significantly lower than an analysis requiring high coverage genome data.

Proper citation: comrad (RRID:SCR_005101) Copy   


  • RRID:SCR_005224

    This resource has 1+ mentions.

http://biohaskell.org/Applications/FlowSim

A suite of tools for simulating the 454 pyrosequencing process. It is based on the characteristics of real 454 data, and attempts to model the known aspects of the process.

Proper citation: FlowSim (RRID:SCR_005224) Copy   


  • RRID:SCR_005184

    This resource has 100+ mentions.

http://phast.wishartlab.com/

A web server designed to rapidly and accurately identify, annotate and graphically display prophage sequences within bacterial genomes or plasmids. It accepts either raw DNA sequence data or partially annotated GenBank formatted data and rapidly performs a number of database comparisons as well as phage cornerstone feature identification steps to locate, annotate and display prophage sequences and prophage features. Relative to other prophage identification tools, PHAST is up to 40 times faster and up to 15% more sensitive. It is also able to process and annotate both raw DNA sequence data and Genbank files, provide richly annotated tables on prophage features and prophage quality and distinguish between intact and incomplete prophage. PHAST also generates downloadable, high quality, interactive graphics that display all identified prophage components in both circular and linear genomic views. Databases available for download include Virus DB, Prophage and virus DB, Bacteria DB, and PHAST result DB. Pre-calculated genomes for viewing are also available.

Proper citation: PHAge Search Tool (RRID:SCR_005184) Copy   


  • RRID:SCR_005187

    This resource has 1+ mentions.

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

A simple and easy to use high through-put analysis tool which can provide comprehensive annotation of both novel and known single nucleotide polymorphisms (SNPs) for any organism with a draft sequence and annotation. SNPdat makes possible analyses involving non-model organisms that are not supported by the vast majority of SNP annotation tools currently available. It is especially intended for use by researchers with limited bioinformatic experience.

Proper citation: SNPdat (RRID:SCR_005187) Copy   


  • RRID:SCR_005254

    This resource has 10+ mentions.

https://github.com/ruping/Breakpointer

A fast tool for locating sequence breakpoints from the alignment of single end reads (SE) produced by next generation sequencing (NGS). It adopts a heuristic method in searching for local mapping signatures created by insertion/deletions (indels) or more complex structural variants(SVs). With current NGS single-end sequencing data, the output regions by Breakpoint mainly contain the approximate breakpoints of indels and a limited number of large SVs. Notably, Breakpointer can uncover breakpoints of insertions which are longer than the read length. Breakpointer also can find breakpoints of many variants located in repetitive regions. The regions can be used not only as a extra support for SV predictions by other tools (such as by split-read method), but also can serve as a database for searching variants which might be missed by other tools. Breakpointer is a command line tool that runs under linux system. Breakpointer takes advanage of two local mapping features of single-end reads as a consequence of indel/SVs: 1) non-uniform read distribution (depth skewness) and 2) misalignments at the boundaries of indel/SVs. These features are summarized as breakpoint signature. Breakpointer proceeds in three stages in capturing this signature. It is implemented in C++ and perl. Input is the file or files containing alignments of single-end reads against a reference genome (in .BAM format). Output is the predicted regions containing potential breakpoints of SVs (in .GFF format). To be able to read in .BAM files, Breakpointer requires bamtools API, which users should install beforehand.

Proper citation: Breakpointer (RRID:SCR_005254) Copy   


  • RRID:SCR_005255

    This resource has 10+ mentions.

https://code.google.com/p/clever-sv/

A collection of tools to discover and genotype structural variations in genomes from paired-end sequencing reads. The main software is written in C++ with some auxiliary scripts in Python.

Proper citation: CLEVER Toolkit (RRID:SCR_005255) Copy   


  • RRID:SCR_005256

    This resource has 1+ mentions.

https://code.google.com/p/clippers/

A software program designed to identify long deletions of a genome as well as the RNA splicings using long Illumina reads. Currently, Clippers is implemented for long reads Illumina, ex: 75bp or 100bp, allowing mismatches and a single deletion/splicing. Clippers is a sister tool of PerM, our short reads aligner. Users are strongly suggested to use PerM to initially mapped reads and identify the deletion/splicing with the initially unmapped reads. We plan to extend it to ABI SOLiD reads in the near future. Clippers outputs gap-alignments in SAM format. You can use SAMtools or other program to interpret the deletion/splicing. The input files are a reference in fasta format and the reads is in fasta or fastq format.

Proper citation: Clippers (RRID:SCR_005256) Copy   


  • RRID:SCR_005373

http://mfiers.github.io/Moa/

Software to assist a bioinformatician to organize, document, share, execute and repeat workflows in a command line environment without losing any of the flexibility of the command line, and, at all times giving the user full access to all aspects of the workflow.

Proper citation: Moa (RRID:SCR_005373) Copy   


  • RRID:SCR_005253

    This resource has 1+ mentions.

http://sv.gersteinlab.org/age/

A tool that implements an algorithm for optimal alignment of sequences with Structural Variations (SVs).

Proper citation: AGE (RRID:SCR_005253) Copy   


  • RRID:SCR_005314

    This resource has 1+ mentions.

http://www.ebi.ac.uk/Rebholz-srv/ebimed/

A web application that combines Information Retrieval and Extraction from Medline. EBIMed finds Medline abstracts in the same way PubMed does. Then it goes a step beyond and analyses them to offer a complete overview on associations between UniProt protein/gene names, GO annotations, Drugs and Species. The results are shown in a table that displays all the associations and links to the sentences that support them and to the original abstracts. By selecting relevant sentences and highlighting the biomedical terminology EBIMed enhances your ability to acquire knowledge, relate facts, discover implications and, overall, have a good overview economizing the effort in reading.

Proper citation: EBIMed (RRID:SCR_005314) Copy   


  • RRID:SCR_005399

    This resource has 10+ mentions.

http://nebc.nerc.ac.uk/tools/bio-linux/bio-linux-7-info

A free, fully featured, powerful, configurable and easy to maintain bioinformatics workstation that provides more than 500 bioinformatics programs on an Ubuntu Linux 12.04 LTS base. Install it or run it live. There is a graphical menu for bioinformatics programs, as well as easy access to the Bio-Linux bioinformatics documentation system and sample data useful for testing programs. You can run a Bio-Linux system on Amazon EC2 or other cloud computing architectures by using CloudBioLinux.

Proper citation: Bio-Linux (RRID:SCR_005399) Copy   


  • RRID:SCR_005273

    This resource has 1+ mentions.

http://www.genoscope.cns.fr/externe/gmorse/

Software aimed at using RNA-Seq short reads to build de novo gene models. First, candidate exons are built directly from the positions of the reads mapped on the genome (without any ab initio assembly of the reads), and all the possible splice junctions between those exons are tested against unmapped reads : the testing of junctions is directed by the information available in the RNA-Seq dataset rather than a priori knowledge about the genome. Exons can thus be chained into stranded gene models.

Proper citation: G-Mo.R-Se (RRID:SCR_005273) Copy   


http://cistrome.org/BETA/

A software package that integrates ChIP-seq of transcription factors or chromatin regulators with differential gene expression data to infer direct target genes. BETA has three functions: (1) to predict whether the factor has activating or repressive function; (2) to infer the factor''''s target genes; and (3) to identify the motif of the factor and its collaborators which might modulate the factor''''s activating or repressive function. BETA requires ~2GB RAM and 1h for the whole procedure. BETA may run on the web server at Cistrome or may be downloaded.

Proper citation: Binding and Expression Target Analysis (RRID:SCR_005396) Copy   



Can't find your Tool?

We recommend that you click next to the search bar to check some helpful tips on searches and refine your search firstly. Alternatively, please register your tool with the SciCrunch Registry by adding a little information to a web form, logging in will enable users to create a provisional RRID, but it not required to submit.

Can't find the RRID you're searching for? X
  1. NIDDK Information Network Resources

    Welcome to the dkNET Resources search. From here you can search through a compilation of resources used by dkNET and see how data is organized within our community.

  2. Navigation

    You are currently on the Community Resources tab looking through categories and sources that dkNET has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.

  3. Logging in and Registering

    If you have an account on dkNET then you can log in from here to get additional features in dkNET such as Collections, Saved Searches, and managing Resources.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Save Your Search

    You can save any searches you perform for quick access to later from here.

  6. Query Expansion

    We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.

  7. Collections

    If you are logged into dkNET you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  8. Sources

    Here are the sources that were queried against in your search that you can investigate further.

  9. Categories

    Here are the categories present within dkNET that you can filter your data on

  10. Subcategories

    Here are the subcategories present within this category that you can filter your data on

  11. Further Questions

    If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.

X