Tools   Select Another Resource Report Type

https://github.com/AlexeyG/GRASS

A generic algorithm for scaffolding next-generation sequencing assemblies.

Proper citation: GRASS (RRID:SCR_005071) Copy   

•   Source: SciCrunch Registry

http://www.protocol-online.org/

Database of research protocols in a variety of life science fields, it contains protocols contributed by worldwide researchers as well as links to web protocols hosted by worldwide research labs, biotech companies, personal web sites. The data is stored in a MySql relational database. Protocol Online also hosts discipline specific discussion forums (BioForum), and provides a free PubMed search and alerting service (PubAlert).

Proper citation: Protocol Online - Your labs reference book (RRID:SCR_004937) Copy   

•   Source: SciCrunch Registry

http://www.bioinf.boku.ac.at/pub/MapAl/

A software tool for RNA-Seq expression profiling that builds on the established programs Bowtie and Cufflinks. Allowing an incorporation of ''gene models'' already at the alignment stage almost doubles the number of transcripts that can be measured reliably.

Proper citation: MapAl (RRID:SCR_004938) Copy   

•   Source: SciCrunch Registry

http://www.open.ac.uk/

Public research university and the largest university in the UK for undergraduate education. The majority of the OU's undergraduate students are based in the United Kingdom and principally study off-campus; many of its courses can also be studied anywhere in the world.

Proper citation: Open University; Milton Keynes; United Kingdom (RRID:SCR_004931) Copy   

•   Source: SciCrunch Registry

http://www.medicine.uiowa.edu/

Medical school of the University of Iowa, located in Iowa City, in the U.S. state of Iowa.

Proper citation: University of Iowa Carver College of Medicine; Iowa; USA (RRID:SCR_005064) Copy   

•   Source: SciCrunch Registry

http://sri.com/

Independent, nonprofit research institute conducting client sponsored research and development for government agencies, commercial businesses, foundations, and other organizations. SRI also brings its innovations to the marketplace by licensing its intellectual property and creating new ventures. SRI was founded as Stanford Research Institute in 1946 by a group of West Coast industrialists and Stanford University. SRI formally separated from the University in 1970, and we changed our name to SRI International in 1977.

Proper citation: Stanford Research Institute International (RRID:SCR_004926) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/jingyijli/SLIDE.zip

Software package that takes exon boundaries and RNA-Seq data as input to discern the set of mRNA isoforms that are most likely to present in an RNA-Seq sample. It is based on a linear model with a design matrix that models the sampling probability of RNA-Seq reads from different mRNA isoforms. To tackle the model unidentifiability issue, SLIDE uses a modified Lasso procedure for parameter estimation. Compared with deterministic isoform assembly algorithms (e.g., Cufflinks), SLIDE considers the stochastic aspects of RNA-Seq reads in exons from different isoforms and thus has increased power in detecting more novel isoforms. Another advantage of SLIDE is its flexibility of incorporating other transcriptomic data such as RACE, CAGE, and EST into its model to further increase isoform discovery accuracy. SLIDE can also work downstream of other RNA-Seq assembly algorithms to integrate newly discovered genes and exons. Besides isoform discovery, SLIDE sequentially uses the same linear model to estimate the abundance of discovered isoforms.

Proper citation: SLIDE (RRID:SCR_005137) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/viralfusionseq/

A versatile high-throughput sequencing (HTS) tool for discovering viral integration events and reconstruct fusion transcripts at single-base resolution. It combines soft-clipping information, read-pair analysis, and targeted de novo assembly to discover and annotate viral-human fusion events. A simple yet effective empirical statistical model is used to evaluate the quality of fusion breakpoints. Minimal user defined parameters are required.

Proper citation: VFS (RRID:SCR_005138) Copy   

•   Source: SciCrunch Registry

https://github.com/tk2/RetroSeq

A tool for discovery and genotyping of transposable element variants (TEVs) (also known as mobile element insertions) from next-gen sequencing reads aligned to a reference genome in BAM format. The goal is to call TEVs that are not present in the reference genome but present in the sample that has been sequenced. It should be noted that RetroSeq can be used to locate any class of viral insertion in any species where whole-genome sequencing data with a suitable reference genome is available. RetroSeq is a two phase process, the first being the read pair discovery phase where discorandant mate pairs are detected and assigned to a TE class (Alu, SINE, LINE, etc.) by using either the annotated TE elements in the reference and/or aligned with Exonerate to the supplied library of viral sequences.

Proper citation: RetroSeq (RRID:SCR_005133) Copy   

•   Source: SciCrunch Registry

http://yost.genetics.utah.edu/software.php

A software analysis pipeline for mapping mutations using RNA-seq that works without parental strain information, without the requirement of a pre-existing snp map of the organism, and without erroneous assumptions that recombination occurs at the same frequency across the genome. In addition, it compensates for the considerable amount of noise in RNA-seq datasets and simultaneously identifies the region where the mutation lies and generates a list of putative coding region mutations in the linked genomic segment. MMAPPR can utilize RNA-seq datasets from isolated tissues or whole organisms that are often generated for phenotypic analysis and gene network analysis in novel mutants.

Proper citation: MMAPPR (RRID:SCR_005092) Copy   

•   Source: SciCrunch Registry

http://www.murdock-trust.org/

The M. J. Murdock Charitable Trust seeks to enrich the quality of life in the Pacific Northwest by providing grants and enrichment programs to non-profit organizations that seek to strengthen the region''s educational, spiritual, and cultural base in creative and sustainable ways. In addition to a special interest in education and scientific research, the Trust partners with a wide variety of organizations that serve the arts, public affairs, health and medicine, human services, leadership development, and persons with disabilities. Eligibility for scientific research grants is limited. Select public research universities and medical institutes located within the five-state region (Pacific Northwest: Alaska, Washington, Oregon, Idaho, Montana) are typically considered for funding. The Trust prefers requests for projects in the natural sciences where the main objective is the acquisition of new knowledge. However, requests for research in engineering and medicine are also eligible. Training students in conducting research is an important consideration.

Proper citation: MJ Murdock Charitable Trust (RRID:SCR_005122) Copy   

•   Source: SciCrunch Registry

http://www.dcc.ac.uk/

The Digital Curation Centre (DCC) is a world-leading centre of expertise in digital information curation with a focus on building capacity, capability and skills for research data management across the UK''s higher education research community. The Digital Curation Centre provides expert advice and practical help to anyone in UK higher education and research wanting to store, manage, protect and share digital research data. The DCC provides access to a range of resources including our popular How-to Guides, case studies and online services. Our training programmes aim to equip researchers and data custodians with the skills they need to manage and share date effectively. We also provide consultancy and support with issues such as policy development and data management planning.

Proper citation: Digital Curation Centre (RRID:SCR_005087) Copy   

•   Source: SciCrunch Registry

http://www.omicsoft.com/fusionmap/

An efficient fusion aligner which aligns reads spanning fusion junctions directly to the genome without prior knowledge of potential fusion regions. It detects and characterizes fusion junctions at base-pair resolution. FusionMap can be applied to detect fusion junctions in both single- and paired-end dataset from either gDNA-Seq or RNA-Seq studies. FusionMap runs under both Windows and Linux (requiring MONO) environments. Although it can run on 32 bit machine, it is recommended to run on 64-bit machine with 8GB RAM or more. If you have an ArrayStudio License, you can run the fusion detection easily through its GUI.

Proper citation: FusionMap (RRID:SCR_005242) Copy   

•   Source: SciCrunch Registry

http://www.cs.helsinki.fi/en/gsa/traph/

A software tool for transcript identification and quantification with RNA-Seq. The method has a two-fold advantage: on the one hand, it translates the problem as an established one in the field of network flows, which can be solved in polynomial time, with different existing solvers; on the other hand, it is general enough to encompass many of the previous proposals under the least sum of squares model.

Proper citation: Traph (RRID:SCR_005119) Copy   

•   Source: SciCrunch Registry

http://www.raetschlab.org/suppl/rquant

Software for quantitative detection of alternative transcripts with RNA-Seq data. The method, based on quadratic programming, estimates biases introduced by experimental settings and is thus a powerful tool to reveal and quantify novel (alternative) transcripts.

Proper citation: rQuant (RRID:SCR_005150) Copy   

•   Source: SciCrunch Registry

http://www.bsse.ethz.ch/cbg/software/shorah

A software package that allows for inference about the structure of a population from a set of short sequence reads as obtained from ultra-deep sequencing of a mixed sample. The package contains programs that support mapping of reads to a reference genome, correcting sequencing errors by locally clustering reads in small windows of the alignment, reconstructing a minimal set of global haplotypes that explain the reads, and estimating the frequencies of the inferred haplotypes.

Proper citation: ShoRAH (RRID:SCR_005211) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/scientific-community/science/projects/viral-genomics/v-phaser-2

A software tool to call variants in genetically heterogeneous populations from ultra-deep sequence data. It combines information regarding the covariation (i.e. phasing) between observed variants to increase sensitivity and an expectation maximization algorithm that iteratively recalibrates base quality scores to increase specificity. V-Phaser can reliably detect rare variants in diverse populations that occur at frequencies of <1%. V-Phaser 2 is a complete rewrite of the original V-Phaser. It contains a new model for length polymorphisms (indels) and incorporates paired end read information in its phasing model. The data access and probability computation sections of the code have also been highly optimized, resulting in substantial improvements in running time and memory usage.

Proper citation: V-Phaser 2 (RRID:SCR_005212) Copy   

•   Source: SciCrunch Registry

https://sites.google.com/site/nsmapforrnaseq/

Software designed to identify and quantify isoforms from RNA-seq by incorporating a sparsity term into expression level estimation to enable isoform structure prediction and expression estimation simultaneously.

Proper citation: NSMAP (RRID:SCR_005213) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/cova/

A variant annotation and comparison tool for next-generation sequencing. It annotates the effects of variants on genes and compares those among multiple samples, which helps to pinpoint causal variation(s) relating to phenotype.

Proper citation: COVA (RRID:SCR_005175) Copy   

•   Source: SciCrunch Registry

http://bmda.cs.unibas.ch/HivHaploTyper/

Software for reconstructing haplotypes from next-generation sequencing data., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PredictHaplo (RRID:SCR_005207) Copy   

•   Source: SciCrunch Registry