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https://github.com/raphael-group/THetA

An algorithm that estimates the tumor purity and clonal / subclonal copy number aberrations directly from high-throughput DNA sequencing data.

Proper citation: THetA (RRID:SCR_001860) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/SamSPECTRAL.html

Software that identifies cell population in flow cytometry data. It demonstrates significant advantages in proper identification of populations with non-elliptical shapes, low density populations close to dense ones, minor subpopulations of a major population and rare populations. It samples large data such that spectral clustering is possible while preserving density information in edge weights. More specifically, given a matrix of coordinates as input, SamSPECTRAL first builds the communities to sample the data points. Then, it builds a graph and after weighting the edges by conductance computation, the graph is passed to a classic spectral clustering algorithm to find the spectral clusters. The last stage of SamSPECTRAL is to combine the spectral clusters. The resulting connected components estimate biological cell populations in the data sample.

Proper citation: SamSPECTRAL (RRID:SCR_001858) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/RchyOptimyx.html

Software that constructs a hierarchy of cells using flow cytometry for maximization of an external variable (e.g., a clinical outcome or a cytokine response).

Proper citation: RchyOptimyx (RRID:SCR_001889) Copy   

•   Source: SciCrunch Registry

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

Software providing a HTML5/javascript based browser for visualizing RNA-seq results in the familiar track layout of common genome browser. But given the quantitative nature of RNA-seq data, in addition to visualizing sequence coverage, the browser quantitates transcript abundance across regions of interest. The HTML5 functionality is made of use to render all the tracks using the canvas drawing element. This greatly reduces the load on servers and allows for rich interactive graphics without the need for third-party plugins. Furthermore, this framework completely segregates data from visualization, making development much easier. The browser is designed to run on all modern browsers: Firefox, Safari, Chrome, Opera and Internet Explorer (though not recommended).

Proper citation: tbrowse (RRID:SCR_001918) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages//2.10/bioc/html/spade.html

An analysis and visualization software tool for high dimensional flow cytometry data that organizes cells into hierarchies of related phenotypes.

Proper citation: SPADE (RRID:SCR_001810) Copy   

•   Source: SciCrunch Registry

http://sammeth.net/confluence/display/ASTA/2+-+Download

Tool that extracts and displays alternative splicing (AS) events from a given genomic annotation of exon-intron gene coordinates. By comparing all given transcripts, it detects the variations in their splicing structure and identifies all AS events (like exon skipping, alternate donor, etc) by assigning to each of them an AS code. It provides a visual summary of the AS landscape in the analyzed dataset, the possibility to browse the results on the UCSC website or to download them in GTF or ASTA format. You can use AStalavista for any genome by providing your own annotation set, the identifier of your gene(s) of interest, or analyze the AS landscape of reference annotation datasets like Gencode, RefSeq, Ensembl, FlyBase, etc.

Proper citation: AStalavista (RRID:SCR_001815) Copy   

•   Source: SciCrunch Registry

http://sharcgs.molgen.mpg.de/

Software package for a DNA assembly program designed for de novo assembly of 25-40mer input fragments and deep sequence coverage.

Proper citation: SHARCGS (RRID:SCR_002026) Copy   

•   Source: SciCrunch Registry

http://snpper.chip.org/

Retrieve known single-nucleotide polymorphisms (SNPs) by position or by association with a gene; save, filter, analyze, display or export SNP sets; explore known genes using names or chromosome positions.

Proper citation: SNPper (RRID:SCR_001963) Copy   

•   Source: SciCrunch Registry

http://brainarray.mbni.med.umich.edu/Brainarray/Database/SearchSNP/snpfunc.aspx

Database for exploring the function implication of single nucleotide polymorphism (SNP) alleles. It is designed to be a clearing house for all public domain SNP functional annotation data, as well as in-house functional annotations derived from different data sources. It currently contains SNP functional annotations in six major categories including genomic elements, transcription regulation, protein function, pathway, disease and population genetics. Besides extensive SNP functional annotations, it includes a search engine that accepts different types of genetic markers as input and identifies all genetically related SNPs based on the HapMap Phase II data as well as the relationship of different markers to known genes. As a result, the system allows users to identify the potential biological impact of genetic markers and complex relationships among genetic markers and genes, and it greatly facilitates knowledge discovery in genome-wide SNP scanning experiments.

Proper citation: SNP Function Portal (RRID:SCR_001954) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/flowType.html

Software for phenotyping Flow Cytometry assays using multidimentional expansion of single dimentional partitions.

Proper citation: flowType (RRID:SCR_001957) Copy   

•   Source: SciCrunch Registry

http://www.cs.sunysb.edu/~skiena/shorty/

Software for targeted de novo assembly of microreads with mate pair information and sequencing errors.

Proper citation: SHORTY (RRID:SCR_002048) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/ADaCGH2.html

Software for analysis and plotting of array comparative genomic hybridization (CGH) data. It allows usage of Circular Binary Segementation, wavelet-based smoothing (both as in Liu et al., and HaarSeg as in Ben-Yaacov and Eldar), HMM, BioHMM, GLAD, CGHseg. Most computations are parallelized (either via forking or with clusters, including MPI and sockets clusters) and use ff for storing data.

Proper citation: ADaCGH2 (RRID:SCR_001981) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/splicegrapher/

Software that predicts alternative splicing patterns and produces splice graphs that capture in a single structure the ways a gene''s exons may be assembled. It enhances gene models using evidence from next-generation sequencing and EST alignments.

Proper citation: SpliceGrapher (RRID:SCR_006657) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/devel/bioc/html/ChIPXpress.html

A R package designed to improve ChIP-seq and ChIP-chip target gene ranking using publicly available gene expression data. It takes as input predicted transcription factor (TF) bound genes from ChIPx data and uses a corresponding database of gene expression profiles downloaded from NCBI GEO to rank the TF bound targets in order of which gene is most likely to be functional TF target.

Proper citation: ChIPXpress (RRID:SCR_006653) Copy   

•   Source: SciCrunch Registry

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

A sensitive structural variant (SV) detection software tool for Illumina paired-end next-generation sequencing data. It simultaneously utilizes soft-clipping and read-pair strategies for detecting SVs to increase sensitivity. Soft clips are proxies for split-reads that indicate part of the read maps to the reference genome, but the other part is not localized at the same place (e.g. breakpoint spanning reads). Discordant read-pairs refer to a read and its mate, where the insert size is greater (or less than) the expected distribution of the dataset ? or ? where the mapping orientation of the reads is unexpected (e.g. both on the same strand). SoftSearch looks for areas with soft-clipping in the genome that have discordant read pairs supporting the anomaly. Once areas with both these conditions are identified, the read and mate information is extracted directly from the BAM file containing the discordant reads, obviating the need for time-consuming and error-prone complex alignment strategies. Only a small number of soft-masked bases discordant read-pairs are necessary to identify an SV, which on their own would not be sufficient to make an SV call, thus highlighting SoftSearch?s improved sensitivity. SoftSearch is well suited to be ?plugged in? to most sequence analysis workflows, since it requires standard file inputs, such as a BAM file using almost any aligner and a reference genome FASTA file. Because SoftSearch requires soft-masked bases, the only requirement is that the aligner must have this functionality, which is usually turned on by default by many standard aligners (e.g. BWA, Novoalign, etc).

Proper citation: SoftSearch (RRID:SCR_006683) Copy   

•   Source: SciCrunch Registry

https://genorm.cmgg.be/

Software to determine most stable reference (housekeeping) genes from set of tested candidate reference genes in given sample panel. From this, gene expression normalization factor can be calculated for each sample based geometric mean of user-defined number of reference genes.

Proper citation: geNORM (RRID:SCR_006763) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/artfastqgen/

Software to evaluate and improve the accuracy of sequencing error under different experimental conditions. It can identify which components of a system may be suboptimal and which regions of the genome may be problematic.

Proper citation: ArtificialFastqGenerator (RRID:SCR_006880) Copy   

•   Source: SciCrunch Registry

http://seqbarracuda.sourceforge.net/

A sequence mapping software that utilizes the massive parallelism of graphics processing units to accelerate the inexact alignment of short sequence reads to a particular location on a reference genome. It can align a paired-end library containing 14 million pairs of 76bp reads to the Human genome in about 27 minutes (from fastq files to SAM alignment) using a ��380 NVIDIA Geforce GTX 680*. The alignment throughput can be boosted further by using multiple GPUs (up to 8) at the same time. Being based on BWA (http://bio-bwa.sf.net) from the Sanger Institute, BarraCUDA delivers a high level of alignment fidelity and is comparable to other mainstream alignment programs. It can perform gapped alignment with gap extensions, in order to minimise the number of false variant calls in re-sequencing studies.

Proper citation: BarraCUDA (RRID:SCR_006881) Copy   

•   Source: SciCrunch Registry

http://watson.nci.nih.gov/bioc_mirror/packages/2.11/bioc/html/EDASeq.html

Software for numerical and graphical summaries of RNA-Seq read data. Within-lane normalization procedures to adjust for GC-content effect (or other gene-level effects) on read counts: loess robust local regression, global-scaling, and full-quantile normalization (Risso et al., 2011). Between-lane normalization procedures to adjust for distributional differences between lanes (e.g., sequencing depth): global-scaling and full-quantile normalization (Bullard et al., 2010)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: EDASeq (RRID:SCR_006751) Copy   

•   Source: SciCrunch Registry

http://www.genomesunzipped.org/

A group blog providing expert, independent commentary on the personal genomics industry. The goal of the project is to provide genetic testing consumers with independent and informed analysis of developments in the field of genetics and the genetic testing industry. Members of Genomes Unzipped include active researchers in various fields of genetics, as well as specialists in the legal and public health issues surrounding new genomic technologies. Many of us have also been extensively involved in public communication about genetics. Members of the group have had their DNA tested with a variety of products. We have released all of these genetic data openly to the public, both as raw data and in a custom genome browser. As the project proceeds we plan to obtain more genetic tests ����?? up to and including whole genome sequencing ����?? and to continue to release these data to the world. The group is also performing analyses of our own raw genetic data to illustrate fundamental concepts in genetics, using software written both by group members and other collaborators; and we����??ll be releasing the code for that software in our new code repository. As the project expands, we����??ll be looking to add data from other volunteers to the project, as well as to collaborate with other ����??genome hackers����?? on the development of new tools for exploring genetic data.

Proper citation: Genomes Unzipped (RRID:SCR_006870) Copy   

•   Source: SciCrunch Registry