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https://github.com/mfumagalli/ngsTools

A collection of software programs for population genetics analyses from NGS (Next-Generation Sequencing) data, taking into account its statistical uncertainty. The methods implemented in these programs do not rely on SNP (Single Nucleotide Polymorphism) or genotype calling, and are particularly suitable for low sequencing depth data.

Proper citation: ngsTools (RRID:SCR_005489) Copy   

•   Source: SciCrunch Registry

http://mlab.cb.k.u-tokyo.ac.jp/~quwei/DeNovoShortReadClustering/

An algorithm for efficient frequency-based de novo short read clustering for error trimming in next-generation sequencing. It organizes erroneous short sequences originating in a single abundant sequence into a tree structure such that each child sequence is considered to be derived stochastically from its more abundant parent sequence because of sequencing errors.

Proper citation: FreClu (RRID:SCR_005524) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://dna.cs.byu.edu/gnumap/

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   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/research/enright/software/kraken

A set of software tools ( Reaper, Tally and Sequence Imp) designed to streamline the analysis of next-generation sequencing data. Although designed with small RNA sequence analysis in mind the tools can be used to address issues facing next-generation sequencing in general.

Proper citation: Kraken (RRID:SCR_005484) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/cushaw2/files/CUSHAW2-GPU/

Software program (based on CUSHAW2) designed and optimized for Kepler-based GPUs, but still workable on earlier-generation Fermi-based ones.

Proper citation: CUSHAW2-GPU (RRID:SCR_005480) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://mbgd.genome.ad.jp/CGAT/

A comparative genome analysis tool for detailed comparison of closely related bacterial-sized genomes. It visualizes precomputed pairwise genome alignments on both dotplot and alignment viewers. Users can add information on this alignment, such as existence of tandem repeats or interspersed repetitive sequences and changes in codon usage bias, to facilitate interpretation of the observed genomic changes. Besides visualization functionalities, it also provides a general framework to process genome-scale alignments using various existing alignment programs. CGAT employs a client-server architecture, which consists of AlignmentViewer (client; a Java application) and DataServer (a set of Perl scripts). The DataServer package contains data construction scripts and CGI scripts and the AlignmentViewer program visualizes the alignment data obtained from the server thorough the HTTP protocol.

Proper citation: CGAT (RRID:SCR_005550) Copy   

•   Source: SciCrunch Registry

http://evolution.sysu.edu.cn/english/software/mapnext.htm

A software tool for spliced and unspliced alignments and SNP detection of short sequence reads.

Proper citation: MapNext (RRID:SCR_005425) Copy   

•   Source: SciCrunch Registry

http://weizhong-lab.ucsd.edu/public/?q=softwares/cd-hit-454

A software program to identify artificial duplicates from raw 454 sequencing reads, including exact duplicates and near identical duplicates.

Proper citation: cd-hit-454 (RRID:SCR_005541) Copy   

•   Source: SciCrunch Registry

http://solexaqa.sourceforge.net/

Software package to calculate sequence quality statistics and create visual representations of data quality for Illumina's second-generation sequencing technology.

Proper citation: SolexaQA (RRID:SCR_005421) Copy   

•   Source: SciCrunch Registry

http://www.ridom.de/traceedit/

A cross-platform graphical DNA trace viewer and editor that displays the chromatogram files from Applied Biosystems automated sequencers and files in the Staden SCF format. Incorrect base calls can be edited and saved. TraceEdit is freely available and designed to operate on Windows and UNIX platforms.

Proper citation: Ridom TraceEdit (RRID:SCR_005568) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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

A software package for detecting methylated cytosines (mCs) and differentially methylated regions (DMRs) from bisulfite sequencing data.

Proper citation: Bisulfighter (RRID:SCR_005440) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://cushaw2.sourceforge.net/homepage.htm#latest

Software package for next-generation sequencing read alignment that is fast and parallel gapped read alignment to large genomes, such as the human genome.

Proper citation: CUSHAW (RRID:SCR_005479) Copy   

•   Source: SciCrunch Registry

http://eqtl.rc.fas.harvard.edu/idcheck/

Software that allows assessment of concordance between genotype (from SNP arrays or DNA sequencing) and gene expression (RNA-seq) samples. IDCheck compares the identity of RNA-seq reads and SNP genotypes using a likelihood based method. Based on maximum likelihood estimates of relevant parameters, we can detect sample contamination and identify correct sample pairs when swapping occurs.

Proper citation: IdCheck (RRID:SCR_005510) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry