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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 3rd,2023. A software program designed to accurately map sequence data obtained from next-generation sequencing machines (specifically that of Solexa/Illumina) back to a genome of any size. By using the posterior probability of mapping a given read to a specific genomic loation, we are able to account for repetitive reads by distributing them across several regions in the genome. In addition, the output of the program is created in such a way that it can be easily viewed through other free and readily- available programs. Several benchmark data sets were created with spiked-in duplicate regions, and GNUMAP was able to more accurately account for these duplicate regions.
Proper citation: GNUMAP (RRID:SCR_005482) Copy
http://samstat.sourceforge.net/
C software program for displaying sequence statistics for next generation sequencing. Works with large fasta, fastq and SAM/BAM files.
Proper citation: SAMStat (RRID:SCR_005432) Copy
http://dna.leeds.ac.uk/methylviewer/
A simple integrated software tool for handling MAP (methyltransferase accessibility protocol) and MAP-IT (MAP individual templates) footprinting projects. It can process sequence data (*.txt, *.ab1 and *.scf) derived from the use of up to four different DNA methyltransferases.
Proper citation: MethylViewer (RRID:SCR_005448) Copy
http://epigenome.usc.edu/publicationdata/bissnp2011/
A software package based on the Genome Analysis Toolkit (GATK) map-reduce framework for genotyping and accurate DNA methylation calling in bisulfite treated massively parallel sequencing (Bisulfite-seq, NOMe-seq, RRBS and any other bisulfite treated sequencing) with Illumina directional library protocol. It contains the following key features: * Call and summarize methylation of any cytosine context provided (CpG, CHH, CHG, GCH et.al.); * Work for single end and paired-end data; * Accurtae variant detection. Enable base quality recalibration and indel calling in bisulfite sequencing; * Based on Java map-reduce framework, allow multi-thread computing. Cross-platform; * Allow multiple output format, detailed VCF files, CpG haplotype reads file for mono-allelic methylation analysis, simplified bedGraph, wig and bed format for visualization in UCSC genome broswer and IGV browser. BisSNP uses bayesian inference with locus specific methylation probabilities and bisulfite conversion rate of different cytosine context(not only CpG, CHH, CHG in Bisulfite-seq, but also GCH et.al. in other bisulfite treated sequencing) to determine genotypes and methylation levels simultaneously., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Bis-SNP (RRID:SCR_005439) Copy
http://code.google.com/p/distmap/
A user-friendly software pipeline designed to map short reads in a MapReduce framework on a local Hadoop cluster. It is designed to be easily implemented by researchers who do not have expert knowledge of bioinformatics. As it does not have any dependencies, it provides full flexibility and control to the user. The user can use any version of a compatible mapper and any reference genome assembly. There is no need to maintain the mapper, reference or DistMap source code on each of the slaves (nodes) in the Hadoop cluster, making maintenance extremely easy.
Proper citation: DistMap (RRID:SCR_005473) Copy
http://www.well.ox.ac.uk/project-stampy
A software package for the mapping of short reads from illumina sequencing machines onto a reference genome. It''s recommended for most workflows, including those for genomic resequencing, RNA-Seq and Chip-seq. Stampy excels in the mapping of reads containing that contain sequence variation relative to the reference, in particular for those containing insertions or deletions. It can map reads from a highly divergent species to a reference genome for instance. Stampy achieves high sensitivity and speed by using a fast hashing algorithm and a detailed statistical model. Stampy has the following features: * Maps single, paired-end and mate pair Illumina reads to a reference genome * Fast: about 20 Gbase per hour in hybrid mode (using BWA) * Low memory footprint: 2.7 Gb shared memory for a 3Gbase genome * High sensitivity for indels and divergent reads, up to 10-15% * Low mapping bias for reads with SNPs * Well calibrated mapping quality scores * Input: Fastq and Fasta; gzipped or plain * Output: SAM, Maq''s map file * Optionally calculates per-base alignment posteriors * Optionally processes part of the input * Handles reads of up to 4500 bases
Proper citation: Stampy (RRID:SCR_005504) Copy
http://ngsview.sourceforge.net/
A generally applicable, flexible and extensible next-generation sequence alignment editor. The software allows for visualization and manipulation of millions of sequences simultaneously on a desktop computer, through a graphical interface.
Proper citation: NGSView (RRID:SCR_005637) Copy
http://www.bioinformatics.babraham.ac.uk/projects/hicup/
A tool for mapping and performing quality control on Hi-C data.
Proper citation: HiCUP (RRID:SCR_005569) Copy
http://zhanglab.c2b2.columbia.edu/index.php/OLego
A program specifically designed for de novo spliced mapping of mRNA-seq reads. It adopts a multiple-seed-and-extend scheme, and does not rely on a separate external mapper.
Proper citation: OLego (RRID:SCR_005811) Copy
https://code.google.com/p/pepr-chip-seq/
A ChIP-Seq peak calling or differential binding analysis tool that is primarily designed for data with biological replicates. It uses a negative binomial distribution to model the read counts among the samples in the same group, and look for consistent differences between ChIP and control group or two ChIP groups run under different conditions.
Proper citation: PePr (RRID:SCR_005759) Copy
http://www.bioinf.uni-freiburg.de/Software/GraphProt/
Software for modeling binding preferences of RNA-binding proteins from high-throughput experiments such as CLIP-seq and RNAcompete.
Proper citation: GraphProt (RRID:SCR_005842) Copy
http://www-math.u-strasbg.fr/genpred/spip.php?article3
R software package to study, predict and simulate the diffusion of a signal through a temporal gene network. It predicts changes in gene expressions after a biological perturbation in the network and provides graphical outputs that allow monitoring the spread of a signal through the network., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Cascade (RRID:SCR_005861) Copy
http://www.psb.ugent.be/cbd/papers/BiNGO/Home.html
The Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape''''s versatile visualization environment to produce an intuitive and customizable visual representation of the results. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: BiNGO: A Biological Networks Gene Ontology tool (RRID:SCR_005736) Copy
http://www.nematodes.org/nematodegenomes/index.php/Main_Page
A collaborative wiki that collates information on completed, ongoing and planned genome and transcriptome sequencing projects on species from phylum Nematoda. The intention is to encourage genome sequencing across the diversity of the phylum Nematoda. Wiki includes: * Published complete nematode genomes: A dynamically generated table of all species for which the genome is published. * Nematode species with genomes in progress: A dynamically generated table of all species for which a genome project is underway. Users may add species to the list * Proposed nematode genome projects: To propose a species for genome sequencing, edit its species page, and set the genome project status to proposed. * BLAST server: Search a number of the nematode-genomes-in-progress with genes of your choice. Currently there are 12 draft genomes available... * Genomes with Data available: Genomes with data available for download. Users may add more data URLs to strain pages or update the URLs.
Proper citation: 959 Nematode Genomes (RRID:SCR_006068) Copy
http://www.bioconductor.org/packages/2.14/bioc/html/h5vc.html
Software package that contains functions to interact with tally data from Next-Generation Sequencing (NGS) experiments that is stored in HDF5 files.
Proper citation: h5vc (RRID:SCR_006039) Copy
http://eddylab.org/software.html
Software library containing tools for statistical manipulations of data. Tools include profile hidden Markov models for biological sequence analysis, RNA structure analysis, and a prototype noncoding RNA genefinder.
Proper citation: Eddy Lab Software (RRID:SCR_001458) Copy
https://github.com/uci-cbcl/PyLOH
Software for deconvolving tumor purity and ploidy by integrating copy number alterations and loss of heterozygosity. The model resolves the identifiability problem by integrating two types of sequencing information - somatic copy number alterations and loss of heterozygosity - within an unified probabilistic framework.
Proper citation: PyLOH (RRID:SCR_001511) Copy
A computer algorithm to predict aggregation nucleating regions in proteins as well the effect of mutations and environmental conditions on the aggregation propensity of these regions.
Proper citation: TANGO (RRID:SCR_001770) Copy
http://cufflinks.cbcb.umd.edu/
Software that estimates expression at transcript-level resolution and controls for variability evident across replicate libraries.
Proper citation: Cuffdiff (RRID:SCR_001647) Copy
http://sourceforge.net/projects/pennseq/
Software for isoform-specific gene expression quantification in RNA-Seq by modeling non-uniform read distribution. Instead of making parametric assumptions, they give adequate weight to the underlying data by the use of a non-parametric approach. The rationale is that regardless what factors lead to non-uniformity, whether it is due to hexamer priming bias, local sequence bias, positional bias, RNA degradation, mapping bias or other unknown reasons, the probability that a fragment is sampled from a particular region will be reflected in the aligned data. This empirical approach thus maximally reflects the true underlying non-uniform read distribution.
Proper citation: PennSeq (RRID:SCR_001763) Copy
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