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https://github.com/philres/ngmlr

Software tool as long read mapper designed to align PacBio or Oxford Nanopore reads to reference genome and optimized for structural variation detection.

Proper citation: Ngmlr (RRID:SCR_017620) Copy   

•   Source: SciCrunch Registry
  

http://compbio.mit.edu/ChromHMM/

Software tool for chromatin state discovery and characterization. Used for chromatin state discovery and genome annotation of non coding genome using epigenomic information across one or multiple cell types. Combines multiple genome wide epigenomic maps, and uses combinatorial and spatial mark patterns to infer complete annotation for each cell type. Provides automated enrichment analysis of resulting annotations.

Proper citation: ChromHMM (RRID:SCR_018141) Copy   

•   Source: SciCrunch Registry
  

https://github.com/bcgsc/NanoSim

Software tool as Nanopore sequence read simulator based on statistical characterization. Oxford Nanopore Technology sequence simulator written in Python and R. Benefits development of scalable next generation sequencing technologies for long nanopore reads, including genome assembly, mutation detection, and metagenomic analysis software.

Proper citation: NanoSim (RRID:SCR_018243) Copy   

•   Source: SciCrunch Registry
  

https://github.com/lh3/minimap2

Software tool as pairwise alignment for nucleotide sequences. Alignment program to map DNA or long mRNA sequences against large reference database. Versatile pairwise aligner for genomic and spliced nucleotide sequences.

Proper citation: Minimap2 (RRID:SCR_018550) Copy   

•   Source: SciCrunch Registry
  

https://cole-trapnell-lab.github.io/monocle3/

Software analysis toolkit for single cell RNA-seq. Used for single cell RNA-Seq experiments. Unsupervised algorithm that increases temporal resolution of transcriptome dynamics using single-cell RNA-Seq data collected at multiple time points.

Proper citation: Monocle3 (RRID:SCR_018685) Copy   

•   Source: SciCrunch Registry
  

https://hartleys.github.io/QoRTs/

Software package for quality control and data processing of RNA-Seq experiments. Software portable multifunction toolkit for assisting in analysis, quality control, and data management of RNA-Seq and DNA-Seq datasets. Used for detection and identification of errors, biases, and artifacts produced by high throughput sequencing technology. Can be used in operating system that supports Java and R.

Proper citation: QoRTs (RRID:SCR_018665) Copy   

•   Source: SciCrunch Registry
  

https://mygene.info/

Web service for querying or retrieving gene annotation data.

Proper citation: MyGene.info (RRID:SCR_018660) Copy   

•   Source: SciCrunch Registry
  

https://github.com/chhylp123/hifiasm

Software tool as haplotype resolved de novo assembler for PacBio Hifi reads. Can assemble human genome in several hours.Introduces new graph binning algorithm and achieves haplotype resolved assembly given trio data. Takes advantage of long high fidelity sequence reads to represent haplotype information in phased assembly graph. Preserves contiguity of all haplotypes.

Proper citation: Hifiasm (RRID:SCR_021069) Copy   

•   Source: SciCrunch Registry
  

https://biofactoid.org

Web tool for creating digital profile of scientific discoveries in article and connecting them to related research. Authors describe molecular interactions supported by their results, letting researchers explore first hand account of article findings and connect to related articles and knowledge. Web based system for scientists to compose structured representation of networks of interactions between genes, their products, and chemical compounds, represented using power of formal ontology.

Proper citation: Biofactoid (RRID:SCR_021011) Copy   

•   Source: SciCrunch Registry
  

http://phenex.phenoscape.org/

Software application for annotating character matrix files with ontology terms. Character states can be annotated using Entity-Quality syntax, where entity, quality, and possibly related entities are drawn from requisite ontologies. In addition, taxa (the rows of a character matrix) can be annotated with identifiers from taxonomy ontology. Phenex saves ontology annotations alongside original free text character matrix data using new NeXML format standard for evolutionary data.

Proper citation: Phenex (RRID:SCR_021748) Copy   

•   Source: SciCrunch Registry
  

https://www.bcgsc.ca/resources/software/ntcard

Software tool for estimating k-mer coverage histogram of genomics data. Streaming algorithm for estimating frequencies of k-mers in genomics datasets.

Proper citation: ntCard (RRID:SCR_022010) Copy   

•   Source: SciCrunch Registry
  

http://tools.dice-database.org/GOnet/)

Web tool for interactive Gene Ontology analysis of any biological data sources resulting in gene or protein lists.

Proper citation: GOnet (RRID:SCR_018977) Copy   

•   Source: SciCrunch Registry
  

http://gbrowse.org/

A database and interactive web site for manipulating and displaying annotations on genomes. Features include: detailed views of the genome; use of a variety of premade or personally made glyphs ; customizable order and appearance of tracks by administrators and end-users; search by annotation ID, name, or comment; support of third party annotation using GFF formats; DNA and GFF dumps; connectivity to different databases, including BioSQL and Chado; and a customizable plug-in architecture (e.g. run BLAST, find oligonucleotides, design primers, etc.). GBrowse is distributed as source code for Macintosh OS X, UNIX and Linux platforms, and as pre-packaged binaries for Windows machines. It can be installed using the standard Perl module build procedure, or automated using a network-based install script. In order to use the net installer, you will need to have Perl 5.8.6 or higher and the Apache web server installed. The wiki portion accepts data submissions.

Proper citation: GBrowse (RRID:SCR_006829) Copy   

•   Source: SciCrunch Registry
  

http://www.broad.mit.edu/annotation/fungi/fgi/

Produces and analyzes sequence data from fungal organisms that are important to medicine, agriculture and industry. The FGI is a partnership between the Broad Institute and the wider fungal research community, with the selection of target genomes governed by a steering committee of fungal scientists. Organisms are selected for sequencing as part of a cohesive strategy that considers the value of data from each organism, given their role in basic research, health, agriculture and industry, as well as their value in comparative genomics.

Proper citation: Fungal Genome Initiative (RRID:SCR_003169) Copy   

•   Source: SciCrunch Registry
  

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

A software tool for annotating biomedical investigations and the resulting data, then producing a MAGE-TAB file. This software is a standalone desktop which features: an editor function, an annotation modifier, incorporation of terms from biomedical ontologies, standard templates for common experiment types, a design aid to help create a new document, and a validator that checks for syntactic and semantic violations.

Proper citation: Annotare (RRID:SCR_000319) Copy   

•   Source: SciCrunch Registry
  

http://khmer.readthedocs.org/

Software library and suite of command line tools for working with DNA sequence that takes a k-mer-centric approach to sequence analysis. It is primarily aimed at short-read sequencing data such as that produced by the Illumina platform.

Proper citation: khmer (RRID:SCR_001156) Copy   

•   Source: SciCrunch Registry
  

http://bioconductor.org/packages/release/bioc/html/nondetects.html

Software R package to model and impute non-detects in results of qPCR experiments.Used to directly model non-detects as missing data.

Proper citation: nondetects (RRID:SCR_001702) Copy   

•   Source: SciCrunch Registry
  

http://www.sanger.ac.uk/mouseportal/

Database of mouse research resources at Sanger: BACs, targeting vectors, targeted ES cells, mutant mouse lines, and phenotypic data generated from the Institute''''s primary screen. The Wellcome Trust Sanger Institute generates, characterizes, and uses a variety of reagents for mouse genetics research. It also aims to facilitate the distribution of these resources to the external scientific community. Here, you will find unified access to the different resources available from the Institute or its collaborators. The resources include: 129S7 and C57BL6/J bacterial artificial chromosomes (BACs), MICER gene targeting vectors, knock-out first conditional-ready gene targeting vectors, embryonic stem (ES) cells with gene targeted mutations or with retroviral gene trap insertions, mutant mouse lines, and phenotypic data generated from the Institute''''s primary screen.

Proper citation: Sanger Mouse Resources Portal (RRID:SCR_006239) Copy   

•   Source: SciCrunch Registry
  

http://www.bioconductor.org/

Software repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.

Proper citation: Bioconductor (RRID:SCR_006442) Copy   

•   Source: SciCrunch Registry
  

http://avis.princeton.edu/pixie/index.php

bioPIXIE is a general system for discovery of biological networks through integration of diverse genome-wide functional data. This novel system for biological data integration and visualization, allows you to discover interaction networks and pathways in which your gene(s) (e.g. BNI1, YFL039C) of interest participate. The system is based on a Bayesian algorithm for identification of biological networks based on integrated diverse genomic data. To start using bioPIXIE, enter your genes of interest into the search box. You can use ORF names or aliases. If you enter multiple genes, they can be separated by commas or returns. Press ''submit''. bioPIXIE uses a probabilistic Bayesian algorithm to identify genes that are most likely to be in the same pathway/functional neighborhood as your genes of interest. It then displays biological network for the resulting genes as a graph. The nodes in the graph are genes (clicking on each node will bring up SGD page for that gene) and edges are interactions (clicking on each edge will show evidence used to predict this interaction). Most likely, the first results to load on the results page will be a list of significant Gene Ontology terms. This list is calculated for the genes in the biological network created by the bioPIXIE algorithm. If a gene ontology term appears on this list with a low p-value, it is statistically significantly overrepresented in this biological network. As you move the mouse over genes in the network, interactions involving these genes are highlighted. If you click on any of the highlighted interactions graph, evidence pop-up window will appear. The Evidence pop-up lists all evidence for this interaction, with links to the papers that produced this evidence - clicking these links will bring up the relevant source citation(s) in PubMed. You may need to download the Adobe Scalable Vector Graphic (SVG) plugin to utilize the visualization tool (you will be prompted if you need it).

Proper citation: bioPIXIE (RRID:SCR_004182) Copy   

•   Source: SciCrunch Registry