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http://www.laskerfoundation.org/index.htm

The Albert and Mary Lasker Foundation and its programs are dedicated to the support of biomedical research toward conquering disease, improving human health and extending life. The Foundation''s mission is to foster the prevention and treatment of disease and disabilities by honoring excellence in basic and clinical science, by educating the public, and by advocating for support of medical research. The Lasker Awards The Lasker Foundation''s Awards Program recognizes the contributions of scientists, physicians, and public servants who have made major advances in the understanding, diagnosis, treatment, cure or prevention of human disease. Other Programs Although the Lasker Foundation is not a grant-giving organization, it does support select initiatives that raise awareness of medical discoveries and their benefits to human health, and that increase support for the medical science enterprise. These initiatives have included study groups, Congressional briefings, innovative web-based programs, educational forums, and scholarly studies.

Proper citation: Lasker Foundation (RRID:SCR_005114) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.wistar.upenn.edu/isoformex

Software that estimates transcript expression levels and gene expression levels from mRNA-Seq data. Technically speaking, IsoformEx parses bowtie alignment files in a project directory (e.g. ~yourid/isoformex/xxx, where xxx is the project name) and generates two files: (1) xxx/xxx_transcript_1.txt: expression levels of all transcripts, (2) xxx/xxx_gene_1.txt: expression levels of all genes.

Proper citation: IsoformEx (RRID:SCR_005235) Copy   

•   Source: SciCrunch Registry

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

RNA-seq tool that uses the Dirichlet distribution and a transformation to identify genes that exhibit small within-condition and large between-condition variance.

Proper citation: aldex (RRID:SCR_005110) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/cga/absolute

Software to estimate purity / ploidy, and from that compute absolute copy-number and mutation multiplicities. When DNA is extracted from an admixed population of cancer and normal cells, the information on absolute copy number per cancer cell is lost in the mixing. The purpose of ABSOLUTE is to re-extract these data from the mixed DNA population. This process begins by generation of segmented copy number data, which is input to the ABSOLUTE algorithm together with pre-computed models of recurrent cancer karyotypes and, optionally, allelic fraction values for somatic point mutations. The output of ABSOLUTE then provides re-extracted information on the absolute cellular copy number of local DNA segments and, for point mutations, the number of mutated alleles.

Proper citation: ABSOLUTE (RRID:SCR_005198) Copy   

•   Source: SciCrunch Registry

http://www.qcmg.org/bioinformatics/tiki-index.php

A single nucleotide variant caller optimised for identifying somatic variants in low cellularity cancer samples.

Proper citation: qSNP (RRID:SCR_005105) Copy   

•   Source: SciCrunch Registry

http://www.damonrunyon.org/

The Damon Runyon Cancer Research Foundation funds early career cancer researchers who have the energy, drive and creativity to become leading innovators in their fields. We identify the best young scientists in the nation and support them through four award programs: our Fellowship, Pediatric Cancer Fellowship, Clinical Investigator and Innovation Awards. Damon Runyon awards give young scientists: * Freedom to follow their own ideas, explore new paths and take risks * A prestigious endorsement that attracts further funding, advances their careers and accelerates their research * Guaranteed financial support, sparing them hours applying for grants Since 1946, Damon Runyon has invested more than $240 million in the best young minds in the nation. Our alumni include 11 Nobel Laureates and leaders of major cancer centers across the United States. Many of our 3,300 scientists have gone on to make breakthroughs in the way we prevent, diagnose and treat many forms of cancer. The Damon Runyon Cancer Research Foundation is a registered nonprofit with 501(c)(3) status.

Proper citation: Damon Runyon Cancer Research Foundation (RRID:SCR_005106) Copy   

•   Source: SciCrunch Registry

http://samtools.sourceforge.net/mpileup.shtml

Provide various utilities for manipulating alignments in the SAM format, including sorting, merging, indexing and generating alignments in a per-position format.

Proper citation: SAMtools/BCFtools (RRID:SCR_005227) Copy   

•   Source: SciCrunch Registry

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

Software framework for simultaneous RNA-Seq-based Transcript Identification and Quantification in Multiple Samples. They define a likelihood function based on the negative binomial distribution, use a regularization approach to select a few transcripts collectively explaining the observed read data, and show how to find the optimal solution using Mixed Integer Programming. MiTie can a) take advantage of known transcripts, b) reconstruct and quantify transcripts simultaneously in multiple samples, as well as c) resolve the location of multi-mapping reads. It is designed for genome- and assembly-based transcriptome reconstruction.

Proper citation: MiTie (RRID:SCR_005228) Copy   

•   Source: SciCrunch Registry

http://orman.sourceforge.net/Home

A software tool for resolving multi-mappings within an RNA-Seq SAM file.

Proper citation: ORMAN (RRID:SCR_005188) Copy   

•   Source: SciCrunch Registry

https://github.com/vezzi/FRC_align

Software package containing tools to process bam files in order to evaluate and analyze de novo assembly / assemblers and identify Structural Variations suspicious genomics regions. The tools have been already successfully applied in several de novo and resequencing projects. This package contains two tools: # FRCbam: tool to compute Feature Response Curves in order to validate and rank assemblies and assemblers # FindTranslocations: tool to identify chromosomal rearrangements using Mate Pairs

Proper citation: FRCbam (RRID:SCR_005189) Copy   

•   Source: SciCrunch Registry

http://www.ukzn.ac.za/

University with five campuses in the province of KwaZulu-Natal in South Africa. It was formed on 1 January 2004 after the merger between the University of Natal and the University of Durban-Westville.

Proper citation: University of KwaZulu-Natal; Durban; South Africa (RRID:SCR_005222) Copy   

•   Source: SciCrunch Registry

http://stothard.afns.ualberta.ca/downloads/NGS-SNP/

A collection of command-line scripts for providing rich annotations for SNPs identified by the sequencing of transcripts or whole genomes from organisms with reference sequences in Ensembl. Included among the annotations, several of which are not available from any existing SNP annotation tools, are the results of detailed comparisons with orthologous sequences. These comparisons allow, for example, SNPs to be sorted or filtered based on how drastically the SNP changes the score of a protein alignment. Other fields indicate the names of overlapping protein domains or features, and the conservation of both the SNP site and flanking regions. NCBI, Ensembl, and Uniprot IDs are provided for genes, transcripts, and proteins when applicable, along with Gene Ontology terms, a gene description, phenotypes linked to the gene, and an indication of whether the SNP is novel or known. A ?Model_Annotations? field provides several annotations obtained by transferring in silico the SNP to an orthologous gene, typically in a well-characterized species.

Proper citation: NGS-SNP (RRID:SCR_005182) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/cga/indelocator

A software tool for calling short indels in next generation sequencing data.

Proper citation: Indelocator (RRID:SCR_005258) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/knime4bio/

A set of custom nodes for the KNIME (The Konstanz Information Miner) graphical workbench, for analysing next-generation sequencing (NGS) data without the requirement of programming skills.

Proper citation: Knime4Bio (RRID:SCR_005376) Copy   

•   Source: SciCrunch Registry

http://ergatis.sourceforge.net/

A web interface and scalable software system for bioinformatics workflows that is used to create, run, and monitor reusable computational analysis pipelines. It contains pre-built components for common bioinformatics analysis tasks. These components can be arranged graphically to form highly-configurable pipelines. Each analysis component supports multiple output formats, including the Bioinformatic Sequence Markup Language (BSML). The current implementation includes support for data loading into project databases following the CHADO schema, a highly normalized, community-supported schema for storage of biological annotation data. Ergatis uses the Workflow engine to process its work on a compute grid. Workflow provides an XML language and processing engine for specifying the steps of a computational pipeline. It provides detailed execution status and logging for process auditing, facilitates error recovery from point of failure, and is highly scalable with support for distributed computing environments. The XML format employed enables commands to be run serially, in parallel, and in any combination or nesting level.

Proper citation: Ergatis (RRID:SCR_005377) Copy   

•   Source: SciCrunch Registry

http://toolshed.g2.bx.psu.edu/repository/display_tool?repository_id=5d0de444b1f9ac52&tool_config=database%2Fcommunity_files%2F000%2Frepo_136%2Fcrest.xml&changeset_revision=4f6952e0af48

An algorithm for detecting genomic structural variations at base-pair resolution using next-generation sequencing data. CREST uses pieces of DNA called soft clips to find structural variations. Soft clips are the DNA segments produced during sequencing that fail to properly align to the reference genome as the sample genome is reassembled. CREST uses the soft clips to precisely identify sites of chromosomal rearrangement or where pieces of DNA are inserted or deleted.

Proper citation: CREST (RRID:SCR_005257) Copy   

•   Source: SciCrunch Registry

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

An interactive software program that integrates phenotypic data exploration, selection, management and quality control using a unified platform for association studies of rare and common variants.

Proper citation: PhenoMan (RRID:SCR_005249) Copy   

•   Source: SciCrunch Registry

http://www.bioextract.org/GuestLogin

An open, web-based system designed to aid researchers in the analysis of genomic data by providing a platform for the creation of bioinformatic workflows. Scientific workflows are created within the system by recording tasks performed by the user. These tasks may include querying multiple, distributed data sources, saving query results as searchable data extracts, and executing local and web-accessible analytic tools. The series of recorded tasks can then be saved as a reproducible, sharable workflow available for subsequent execution with the original or modified inputs and parameter settings. Integrated data resources include interfaces to the National Center for Biotechnology Information (NCBI) nucleotide and protein databases, the European Molecular Biology Laboratory (EMBL-Bank) non-redundant nucleotide database, the Universal Protein Resource (UniProt), and the UniProt Reference Clusters (UniRef) database. The system offers access to numerous preinstalled, curated analytic tools and also provides researchers with the option of selecting computational tools from a large list of web services including the European Molecular Biology Open Software Suite (EMBOSS), BioMoby, and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The system further allows users to integrate local command line tools residing on their own computers through a client-side Java applet.

Proper citation: BioExtract (RRID:SCR_005397) Copy   

•   Source: SciCrunch Registry

http://statgenpro.psychiatry.hku.hk/limx/kggseq/

A biological Knowledge-based mining platform for Genomic and Genetic studies using Sequence data. The software platform, constituted of bioinformatics and statistical genetics functions, makes use of valuable biologic resources and knowledge for sequencing-based genetic mapping of variants / genes responsible for human diseases / traits. It facilitates geneticists to fish for the genetic determinants of human diseases / traits in the big sea of DNA sequences. KGGSeq has paid attention to downstream analysis of genetic mapping. The framework was implemented to filter and prioritize genetic variants from whole exome sequencing data.

Proper citation: KGGSeq (RRID:SCR_005311) Copy   

•   Source: SciCrunch Registry

http://soap.genomics.org.cn/soapindel.html

Software focusing on calling indels from the next-generation paired-end sequencing data.

Proper citation: SOAPindel (RRID:SCR_005272) Copy   

•   Source: SciCrunch Registry