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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://research.cs.wisc.edu/wham/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. High-throughput sequence alignment tool that aligns short DNA sequences (reads) to the whole human genome at a rate of over 1500 million 60bps reads per hour, which is one to two orders of magnitudes faster than the leading state-of-the-art techniques. Feature list for the current version (v 0.1.5) of WHAM: * Supports paired-end reads * Supports up to 5 errores * Supports alignments with gaps * Supports quality scores for filtering invalid alignments, and sorting valid alignments * finds ALL valid alignments * Supports multi-threading * Supports rich reporting modes * Supports SAM format output
Proper citation: WHAM (RRID:SCR_005497) Copy
http://www-personal.umich.edu/~jianghui/seqmap/
A software tool for mapping large amount of oligonucleotide to the genome. It is designed for finding all the places in a genome where an oligonucleotide could potentially come from. SeqMap can efficiently map as many as dozens of millions of short sequences to a genome of several billions of nucleotides. While doing the mapping, several mutations as well as insertions / deletions of the nucleotide bases in the sequences can be tolerated and furthermore detected. Various input and output formats are supported, as well as many command line options for tuning almost every steps in the mapping process. A typical mapping can be done in a few hours on an ordinary PC.
Proper citation: SeqMap (RRID:SCR_005495) Copy
http://www.genome.umd.edu/jellyfish.html
A software tool for fast, memory-efficient counting of k-mers in DNA. A k-mer is a substring of length k, and counting the occurrences of all such substrings is a central step in many analyses of DNA sequence. JELLYFISH can count k-mers quickly by using an efficient encoding of a hash table and by exploiting the compare-and-swap CPU instruction to increase parallelism. Jellyfish is a command-line program that reads FASTA and multi-FASTA files containing DNA sequences. It outputs its k-mer counts in an binary format, which can be translated into a human-readable text format using the jellyfish dump command., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Jellyfish (RRID:SCR_005491) Copy
http://mrfast.sourceforge.net/
Software designed to map short reads generated with the Illumina platform to reference genome assemblies; in a fast and memory-efficient mannerl. Currently Supported Features: * Output in SAM format * Indels up to 8 bp (4 bp deletions and 4 bp insertions) * Paired-end mapping ** Discordant option to generate mapping file ready for VariationHunter to detect structural variants. * One end anchored (OEA) map locations for novel sequence insertion detection with NovelSeq * Matepair library mapping (long inserts with RF orientation). Planned Features: * Multithreading
Proper citation: mrFAST (RRID:SCR_005487) Copy
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
An application for discovering potential splice junctions in high throughput sequencing (HTS) data.
Proper citation: Supersplat (RRID:SCR_009826) Copy
http://soap.genomics.org.cn/soapsnp.html
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software providng a method based on Bayes? theorem (the reverse probability model) to call consensus genotype by carefully considering the data quality, alignment, and recurring experimental errors., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: SOAPsnp (RRID:SCR_010602) Copy
http://noble.gs.washington.edu/proj/crux/
A software toolkit for tandem mass spectrometry analysis, with a focus on peptide identification. Crux analyzes shotgun proteomics tandem mass spectra, associating peptides with observed spectra. This software toolkit for tandem mass spectrometry analysis, with a focus on peptide identification is provided as a single executable. Crux is implemented in C and is distributed with source code freely to noncommercial users. Mass spectrometry, the core technology in the field of proteomics, promises to enable scientists to identify and quantify the entire complement of proteins in a complex biological sample. Currently, the primary bottleneck in this type of experiment is computational. Existing algorithms for interpreting mass spectra are slow and fail to identify a large proportion of the given spectra. We describe a database search program called Crux that reimplements and extends the widely used database search program Sequest. For speed, Crux uses a peptide indexing scheme to rapidly retrieve candidate peptides for a given spectrum. For each peptide in the target database, Crux generates shuffled decoy peptides on the fly, providing a good null model and, hence, accurate false discovery rate estimates. Crux also implements two recently described postprocessing methods: a p value calculation based upon fitting a Weibull distribution to the observed scores, and a semisupervised method that learns to discriminate between target and decoy matches. Both methods significantly improve the overall rate of peptide identification.
Proper citation: Crux tandem mass spectrometry analysis software (RRID:SCR_010648) Copy
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