GAEMR’s analysis philosophy is centered on contiguity, correctness, and completeness -- how many pieces in an assembly composed of, how well those pieces accurately represent the genome sequenced, and how much of that genome is represented by those pieces. By performing over twenty different analyses based on these principles, GAEMR gives a clear picture of the condition of a genome assembly. 

Address of the bookmark: https://www.broadinstitute.org/software/gaemr/

http://genome.cshlp.org/content/early/2012/01/12/gr.131383.111

Address of the bookmark: http://gage.cbcb.umd.edu/index.html

Download

Git repository of SWALO is at https://github.com/atifrahman/SWALO.

Address of the bookmark: https://atifrahman.github.io/SWALO/

http://evomics.org/learning/assembly-and-alignment/velvet/

Address of the bookmark: http://evomics.org/learning/assembly-and-alignment/velvet/

MeGAMerge (A tool to merge assembled contigs, long reads from metagenomic sequencing runs)

Description

MeGAMerge is a perl based wrapper/tool that can accept any number of sequence (FASTA) files containing assembled contigs of any length in Multi-FASTA format to produce an improved contig set based on OLC based assembly. All overlap parameters (Minimum Overlap Length, Identity, etc) are user-declarable at runtime. It is written to run on Linux.

Requirements:

You will need to have the following tools installed and in $PATH, or added to $binpath in the tool:

Newbler (specifically runAssembly)
Minimus2 (part of AMOS, also requires MUMmer)

Address of the bookmark: https://github.com/LANL-Bioinformatics/MeGAMerge

We therefore list many genomle assembly tools here. We mainly reported for the assembly of genomes while the others are designed aiming at handling complex genomes.

• RMAP 2.1 – Short-read Mapping
  RMAP is aimed to map accurately reads from the next-generation sequencing technology. RMAP can map reads with or without error probability information (quality scores) and supports paired-end reads or bisulfite-treated reads mapping. There is no limitaions on read widths or number of mismatches. RMAP can now map more than 8 million reads in an hour at full sensitivity to 2 mismatches
  
  
• MIRA 4.0.2 – Whole Genome Shotgun and EST Sequence Assembler
  MIRA (Mimicking Intelligent Read Assembly)is a whole genome shotgun and EST sequence assembler for Sanger, 454, Solexa (Illumina), IonTorrent data and PacBio (the later at the moment only CCS and error-corrected CLR reads). It can be seen as a Swiss army knife of sequence assembly developed and used in the past 12 years to get assembly jobs done efficiently – and especially accurately. That is, without actually putting too much manual work into finishing the assembly.
  
  
• HapCompass 0.7.7 – A Cycle-Basis Algorithm for Accurate Haplotype Assembly
  HapCompass for polyploid genomes can currently be used to create accurate pairwise SNP phasings.Given a set of aligned sequence reads in a SAM file and a set of variant calls in VCF format, HAPCOMPASS will assemble reads into haplotypes.
  
  
• GAM-NGS 1.1b – Genome Assemblies Merger for Next Generation Sequencing
  GAM-NGS is able to merge two or more assemblies and it rteturns an improved assembly (more contiguous and more correct). GAM-NGS shows its full potential with multi-library Illumina-based projects.
  
  
• GeneStitch 1.2.1 – Network Matching Algorithm to Gene Assembly
  GeneStitch is a tool to assemble genes using network matching algorithm. Given an already-assembled dataset, it is capable of assembling contigs together to form more complete genes with the help of a reference gene set. Currently the assembly software that GeneStitch support is SOAPdenovo.
  
  
• RACA 0.9.1.1 – Reference-Assisted Chromosome Assembly
  RACA is an algorithm to reliably order and orient sequence scaffolds generated by NGS and assemblers into longer chromosomal fragments using comparative genome information and paired-end reads.
  
  
• DISCOVAR 51750 – Genome Shotgun Assembler and Variant Caller
  DISCOVAR is a whole genome shotgun assembler and variant caller that can generate high quality assemblies and variant calls from the latest 250 base Illumina PCR-free fragment reads.
  
  
• SeqCons 1.0 – de novo and reference-guided Sequence Assembly
   SeqCons (Sequence consensus) is an open source consensus computation program for Linux and Windows. The algorithm can be used for de novo and reference-guided sequence assembly.
  
  
• SimAssemblyStage1/2 0.2 – Assembly Alignment of Contigs
  SimAssemblyStage1: Perfectly aligns TranscriptSimulator reads to their nucleotide templates using read title inforamation, creating ideal simulated assembly of super contigs.
  
  
• GapFiller – Closing the Gap within Paired Reads
  GapFiller is not a standard de novo assembler. It aims “only” at closing the gap between pairs of reads as a first step of a large number of downstream analysis
  
  
• PAGIT 1.01 – Post Assembly Genome Improvement Toolkit
  PAGIT (Post Assembly Genome Improvement Toolkit) is a tools to generate automatically high quality sequence by ordering contigs, closing gaps, correcting sequence errors and transferring annotation.
  
  
• ShoRAH 0.8.2 – Short Reads Assembly into Haplotypes
  ShoRAH is a software package that allows for inference about the structure of a population from a set of short sequence reads as obtained from ultra-deep sequencing of a mixed sample. The package contains programs that support mapping of reads to a reference genome, correcting sequencing errors by locally clustering reads in small windows of the alignment, reconstructing a minimal set of global haplotypes that explain the reads, and estimating the frequencies of the inferred haplotypes.
  
  
• RePS 2.0 – WGS Sequence Assembler
  RePS (Repeat-masked Phrap with scaffolding), a WGS sequence assembler, that explicitly identifies exact kmer repeats from the shotgun data and removes them prior to the assembly. The established software Phrap is used to compute meaningful error probabilities for each base. Clone-end-pairing information is used to construct scaffolds that order and orient the contigs. The updated version of RePS incorporates some of the ideas introduced by Phusion on clustering
  
  
• treecat – Phylogenetic Comparative Assembly
  treecat (phylogenetic tree based contig arrangement tool) takes several genomes and their relationships in a phylogenetic tree into account to estimate a possible ordering of the contigs.
  
  
• IsoLasso 2.6.1 – A LASSO Regression Approach to RNA-Seq Based Transcriptome Assembly
  IsoLasso is an algorithm to assemble transcripts and estimate their expression levels from RNA-Seq reads.
  
  
• CEM 0.9.1 – Transcriptome Assembly and Isoform Expression Level Estimation from Biased RNA-Seq Reads
  CEM is an algorithm to assemble transcripts and estimate their expression levels from RNA-Seq reads.
  
  
• MaLTA – Transcriptome Assembly and Quantification from Ion Torrent RNA-Seq data
  MaLTA is a method for simultaneous transcriptome assembly and quantification from Ion Torrent RNA-Seq data.
  
  
• AMOS 3.1.0 – Whole Genome Shotgun Assembler
  AMOS (AModular, Open-Source) consortium is committed to the development of open-source whole genome assembly software. The project acronym (AMOS) represents our primary goal — to produce A Modular, Open-Source whole genome assembler.Open-source so that everyone is welcome to contribute and help build outstanding assembly tools, and modular in nature so that new contributions can be easily inserted into an existing assembly pipeline. This modular design will foster the development of new assembly algorithms and allow the AMOS project to continually grow and improve in hopes of eventually becoming a widely accepted and deployed assembly infrastructure. In this sense, AMOS is both a design philosophy and a software system.
  
  
• AutoEditor 1.20 – Automated Correction of Genome Sequence Errors
  AutoEditor is a tool for correcting sequencing and basecaller errors using sequence assembly and chromatogram data. On average AutoEditor corrects 80% of erroneous base calls, with an accuracy of 99.99%.This in turn improves the overall accuracy of genome sequences and facilitates the use of these sequences for polymorphism discovery.
  
  
• SAGE – String Graph Assembly of GEnomes
  SAGE is a new string-overlap graph-based de novo genome assembler.
  
  
• Omega 1.0.2 – Overlap-graph de novo Assembler for Metagenomics
  Omega is a software for assembling and scaffolding Illumina sequencing data of microbial communities.
  
  
• TCGA-Assembler 1.0.3 – Open-Source Software for Retrieving and Processing TCGA Data
  TCGA-Assembler is an open-source, freely available tool that automatically downloads, assembles, and processes public The Cancer Genome Atlas (TCGA) data, to facilitate downstream data analysis by relieving investigators from the burdens of data preparation.
  
  
• SAMMate 2.7.4 / assemblySAM 1.1 – Processing Short Read Alignments in SAM/BAM format / RNA-Seq Assembly and Analysis
  

  SAMMate is an open source GUI software suite to process RNA-Seq data. It is composed of two modules: assemblySAM and SAMMate.

  assemblySAM employs a novel method to localize and assemble RNA-seq reads into RNA transcript sequences.
  
  

• StringGraph beta – String Graph Construction Using Incremental Hashing
  StringGraph is a novel, hash based method for constructing the string graph.
  
  
• MindTheGap 1.0.0 – Detection and Assembly of Insertion Variants
  MindTheGap is a software that performs detection and assembly of DNA insertion variants in NGS read datasets with respect to a reference genome.
  
  
• MetAMOS 1.5rc3 – Metagenomic Assembly pipeline for AMOS
  MetAMOS is an open source and modular metagenomic assembly and analysis pipeline. MetAMOS represents an important step towards fully automated metagenomic analysis, starting with next-generation sequencing reads and producing genomic scaffolds, open-reading frames and taxonomic or functional annotations.
  
  
• TIGER – DNA Sequence Assembly
  Tiger is a novel de novo assembly framework  which adapts to available computing resources by iteratively decomposing the assembly problem into sub-problems.
  
  
• AlignGraph – Secondary de novo Genome Assembly guided by closely related References
  AlignGraph is a software that extends and joins contigs or scaffolds by reassembling them with help provided by a reference genome of a closely related organism.
  
  
• scarpa 0.241 – Scaffolding Reads with Practical Algorithms
  Scarpa is a stand-alone scaffolding tool for NGS data. It can be used together with virtually any genome assembler and any NGS read mapper that supports SAM format. Other features include support for multiple libraries and an option to estimate insert size distributions from data.
  
  
• VGA v1 – Viral Genome Assembler
  VGA is a method for accurate assembly of a heterogeneous viral population consisting of individuals viral genomes (also known as quasi-species).
  
  
• Genomix 0.2.11 – Parallel Genome Assembly using Hyracks
  Genomix is a parallel genome assembly system built from the ground up with scalability in mind. It can assemble large and high-coverage genomes from fastq files in a short time and produces assemblies similar to Velvet or Ray in quality.
  
  
• LACHESIS – Genome Assembly with Contact Probability Maps
  LACHESIS is method that exploits contact probability map data (e.g. from Hi-C) for chromosome-scale de novo genome assembly.
  
  
• KGBassembler 1.2 – Karyotype-based Genome Assembler for Brassicaceae Species
  KGBassembler (Brassicaceae genome assembler) is a C++ based tool for assembling contigs and/or scaffolds to full chromosomes based on the karyotype maps of Brassicaceae species and without the need of genetic and physical maps.
  
  
• AutoAssemblyD 0.1 – Graphical User Interface system for several Genome Assembler
  The AssemblyD is a software which performed the local and remote genome assembly by several assemblers based on an XML Template which can replace the large command lines required by most assemblers.
  
  
• SR-ASM – DNA Assembly of the Short Sequences coming from 454 sequencer
  SR-ASM (Short Reads ASseMbly) algorithm is designed for DNA assembly of the short sequences coming from 454 sequencers.
  
  
• YASRA 2.33 – Yet Another Short Read Assembler
  YASRA performs comparative assembly of short reads using a reference genome, which can differ substantially from the genome being sequenced.
  
  
• PRICE 1.2 – de novo Genome Assembler
  PRICE (Paired-Read Iterative Contig Extension) is a de novo genome assembler implemented in C++. Its name describes the strategy that it implements for genome assembly: PRICE uses paired-read information to iteratively increase the size of existing contigs. Initially, those contigs can be individual reads from a subset of the paired-read dataset, non-paired reads from sequencing technologies that provide non-paired data, or contigs that were output from a prior run of PRICE or any other 
  
  
• ALE 20130717 – Assembly Likelihood Estimator
  ALE is a probabalistic framework for determining the likelihood of an assembly given the data (raw reads) used to assemble it. It allows for the rapid discovery of errors and comparisons between similar assemblies.
  
  
• SSPACE 3.0 – Scaffolding pre-assembled Contigs using Paired-read data
  SSPACE (SSAKE-based Scaffolding of Pre-Assembled Contigs after Extension) is a stand-alone program for scaffolding pre-assembled contigs using paired-read data. It is unique in offering the possibility to manually control the scaffolding process. By using the distance information of paired-end and/or matepair data, SSPACE is able to assess the order, distance and orientation of your contigs and combine them into scaffolds. Currently we offer this as a command-line tool in Perl. The input data is given by pre-assembled contig sequences (FASTA) and NGS paired-read data (FASTA or FASTQ). The final scaffolds are provided in FASTA format.
  
  
• IMAGE 2.4.1 – Iterative Mapping and Assembly for Gap Elimination
  IMAGE ( Iterative Mapping and Assembly for Gap Elimination) is a software designed to close gaps in any draft assembly using Illumina paired end reads. IMAGE is best described in several stages: aligning of Illumina reads at contig ends; local assembly of reads into new contigs; reference contigs are extended or merged; iterating the whole process to extend and merge more contigs.
  
  
• ATLAS GapFill 2.2 – Deals with the Repetitive Gap Assembly problem
  ATLAS GapFill deals with the repetitive gap assembly problem by using the unique gap-flanking sequences to group reads and convert the problem to a local assembly task. Localizing the assembly reduces the numbers of repeats in the assembly, allows more data to be incorporated, and allows for gaps to be filled.
  
  
• Atlas 2005 – Whole Genome Assembly Suite
  Atlas is a collection of software tools to facilitate the assembly of large genomes from whole genome shotgun reads, or a combination of whole genome shotgun reads and BAC or other localized reads.
  
  
• CGAL 0.9.6b – Computing Genome Assembly Likelihoods
  CGAL is a tool for computing genome assembly likelihoods. It computes the likelihood of reads with respect to the assembly and a statistical model which can be used as a metric for evaluating assemblies.
  
  
• Fermi 1.1 – WGS de novo Assembler based on the FMD-index for large Genomes
  Fermi is a de novo assembler for Illumina reads from whole-genome short-gun sequencing. It also provides tools for error correction, sequence-to-read alignment and comparison between read sets. It uses the FMD-index, a novel compressed data structure, as the key data 
  
  
• PASHA 1.0.10 – Parallelized Short Read Assembly
  PASHA is a parallel short read assembler for large genomes using de Bruijn graphs. Taking advantage of both shared-memory multi-core CPUs and distributed-memory compute clusters, PASHA has demonstrated its potential to perform high-quality de-novo assembly of large genomes in reasonable time with modest computing resources. Our evaluation using three small real paired-end datasets shows that PASHA is able to produce better assemblies with comparable genome coverage and mis-assembly rates compared to three leading assemblers: Velvet, ABySS and SOAPdenovo. Moreover, PASHA achieves the fastest speed for all three datasets on a single CPU.
  
  
• XGenovo – Extended Genovo Metagenomic Assembler by Incorporating Paired-End Information
  XGenovo (Extended Genovo) is an extended genovo metagenomic assembler by incorporating paired-end information
  
  
• MetaVelvet 1.2.01 / MetaVelvet-SL – An Extension of Velvet Assembler to de novo Metagenomic Assembly / utilizing Supervised Learning
  MetaVelvet is an extension of Velvet assembler to de novo metagenome assembly from short sequence reads
  
  
• Edena v3.131028 – De Novo Short Reads Assembler
  Edena is an assembler dedicated to process the millions of very short reads produced by the Illumina Genome Analyzer
  
  
• ConPADE 1.00 – Contig Ploidy and Allele Dosage Estimation
  ConPADE is a tool used to estimate contig ploidy and allele dosage in polyploid genome assemblies.
  
  
• ELOPER 1.2 – Elongation of Paired-end Reads for de novo Assembly
  ELOPER is a pre-processing tool for pair-end sequences that produces a better read library for assembly programs.
  
  
• Oases 0.2.08 – De novo Transcriptome Assembler for very short reads
  Oases designed to heuristically assemble RNA-seq reads in the absence of a reference genome, across a broad spectrum of expression values and in presence of alternative isoforms. It achieves this by using an array of hash lengths, a dynamic filtering of noise, a robust resolution of alternative splicing events, and the efficient merging of multiple assemblies. It was tested on human and mouse RNA-seq data and is shown to improve significantly on the transABySS and Trinity de novo 
  
  
• SOPRA 1.4.6 – Statistical Optimization of Paired Read Assembly
  SOPRA is an assembler for mate pair/paired-end reads from high throughput sequencing platforms, e.g. Illumina and SOLiD.
  
  
• hapAssembly – Haplotype Assembly from Whole-Genome Sequence Data
  hapAssembly  beats the previous best for the important Haplotype Assembly Problem. It is an approach to finding optimal solutions for the haplotype assembly problem under the minimum-error-correction (MEC) model.
  
  
• PBSIM 1.0.3 – PacBio Reads Simulator
  PacBio sequencers produced two types of characteristic reads: CCS (short and low error rate) and CLR (long and high error rate), both of which could be useful for de novo assembly of genomes. PBSIM simulates those PacBio reads by using either a model-based or sampling-based simulation.
  
  
• SIS – Generate Draft Genome Sequence Scaffolds for Prokaryotes
  SIS (Scaffolds from Inversion Signatures)is a new easy-to-use tool to generate contig scaffolds
  
  
• NN50-calculator 0.5 – Evaluate the Correctness of Genome Assemblies
  NN50-calculator (Normalized N50 calculator) is a tool for evaluating the correctness of genome assemblies.
  
  
• Baa.pl 0.20 – use BLAT to ASSESS an ASSEMBLY
  Baa.pl is a simple script that parses the output of a BLAT run of a transcriptome vs. a genome assembly.
  
  
• hapsembler 2.21 – Haplotype-specific Genome Assembly Toolkit
  Hapsembler is a haplotype-specific genome assembly toolkit that is designed for genomes that are rich in SNPs and other types of polymorphism. Hapsembler can be used to assemble reads from a variety of platforms including Illumina and Roche/454.
  
  
• ViSpA 02 – Viral Spectrum Assembler
  ViSpA (Viral Spectrum Assembling) implements a novel viral assembling and frequency estimation methods. This software uses a simple error correction, viral variants assembling based on maximum-bandwidth paths in weighted read graphs and frequency estimation via Expectation Maximization on all reads.
  
  
• VelvetOptimiser 2.2.5 – Automatically Optimise Velvet Assembler Parameters
  VelvetOptimiser is a multi-threaded Perl script for automatically optimising the three primary parameter options (K, -exp_cov, -cov_cutoff) for the Velvet de novo sequence assembler.
  
  
• Assemblet 0.1 – Antigenic Variation Assembler
  Assemblet is a short read assembler for assembling antigenic variant sequences in bacteria.
  
  
• VelvetK 20120606 – Find a reasonable K-mer size to Assemble Genome Reads with Velvet
  VelvetK can estimate the best k-mer size to use for your Velvet de novo assembly. It needs two inputs: the estimated genome size, and all your sequence read files. The genome size can be supplied as as a number (eg. 3.5M) or as a FASTA file of a closely related genome.
  
  
• VAGUE 1.0.5 – Velvet Assembler Graphical User Environment
  VAGUE (Velvet Assembler Graphical Front End) is a GUI for the Velvet de novo assembler.
  
  
• Transcriptome Assembler – Transcriptome Assembly used in RNA-seq of 16 Mammalian Species
  Transcriptome Assembler is a software for transcriptome assembly used in RNA-seq of 16 mammalian species.
  
  
• BioSequenceAssembler 2.0 – Microsoft Research Sequence Assembler
  BioSequenceAssembler is intended for use by biologist and laboratory technicians who are responsible for managing next-generation genomic sequencing data for alignment, assembly, and/or BLAST identification.
  
  
• BugBuilder – Microbial Genome Assembly
  BugBuilder is a pipeline for the automated assembly and annotation of microbial genomes from high-throughput sequence data. It is configurable so as not to be tied to any assembler or scaffolder, and is designed to run in a cluster environment facilitating high-throughput processing of genomes.
  
• MAXIMUS 0.2 – Hybrid Reference and de novo Assembly pipeline
  MAXIMUS is a genome assembly pipeline which takes the best out of multiple reference assemblies and de novo assembly. The benefits of this approach include better assembled repetitive regions, less gaps and higher accuracy for the resultant assembly.
  
  
• ISSAKE – Short Read Sequence Assembly
  iSSAKE (immuno-SSAKE) is a sequencing approach and assembly software for profiling T-cell metagenomes using short reads from the massively parallel sequencing platforms.
  
  
• IDBA / IDBA-UD 1.1.1 – De Bruijn Graph De Novo Assembler with Highly Uneven Sequencing Depth
   IDBA is a practical iterative De Bruijn Graph De Novo Assembler for sequence assembly in bioinfomatics. Most assemblers based on de Bruijn graph build a de Bruijn graph with a specific k to perform the assembling task. For all of them, it is very crucial to find a specific value of k. If k is too large, there will be a lot of gap problems in the graph. If k is too small, there will a lot of branch problems. IDBA uses not only one specific k but a range of k values to build the iterative de Bruijn graph. It can keep all the information in graphs with different k values. So, it will perform better than other assemblers.
  
  
• est2assembly 1.13 – Assembly and Annotation of Transcriptomes for any Species
  The est2assembly platform is the only platform for standardising transcriptome projects: go from raw trace files to an annotated GBrowse interface driven by the Seqfeature database. It accepts both Sanger and 454 sequencing technology for a denovo assembly, annotation and data mining of EST data.
  
  
• Curtain 0.2.3 beta – Assembling large Genomes from Short Read Sequences
  Curtain is an assembler of next generation sequence. Curtain is a Java wrapper around next-generation assemblers such as Velvet, which allows the incremental introduction of read-pair information into the assembly process.
  
  
• PEAssember 1.2 – A de novo Genome Assembler
  PEAssember is a parallel de novo genome assembler for small – mid sized genomes.
  
  
• Contrail 0.8.2 – Assembly of Large Genomes using Cloud Computing
  Contrail is a Hadoop based genome assembler for assembling large genomes in the clouds
  
  
• BEAP 0.6 beta – Blast Extension and Assembly Program
  The BEAP is a computer program that uses a short starting DNA fragment, often a EST or partial gene segment, as “primer”, to recursively blast nucleotide databases in an attempt to obtain all sequences that overlaps, directly or indirectly, with the “primer” therefore help to “extend” the length of the original sequence for constructing a “full length” sequence for functional analysis, or at least to obtain neighboring regions of the segment for SNP discovery and linkage disequilibrium 
  
  
• BRANCH 1.8.1 – boosting RNA-Seq Assemblies with Partial or related Genomic Sequences
  BRANCH is a software that extends de novo transfrags and identifies novel transfrags with DNA contigs or genes of close related species. BRANCH discovers novel exons first and then extends/joins fragmented de novo transfrags, so that the resulted transfrags are more complete.
  
  
• Quake 0.3.5 – Detect & Correct Substitution Sequencing Errors in WGS Data Sets
  

  Quake is a package to correct substitution sequencing errors in experiments with deep coverage (e.g. >15X), specifically intended for Illumina sequencing reads. Quake adopts the k-mer error correction framework, first introduced by the EULER genome assembly package. Unlike EULER and similar progams, Quake utilizes a robust mixture model of erroneous and genuine k-mer distributions to determine where errors are located. Then Quake uses read quality values and learns the nucleotide to nucleotide error rates to determine what types of errors are most likely. This leads to more corrections and greater accuracy, especially with respect to avoiding mis-corrections,  which create false sequence unsimilar to anything in the original genome sequence from which the read was taken.

• Velvet 1.2.10 – Sequence Assembler for Very Short Reads
  Velvet is a de novo genomic assembler specially designed for short read sequencing technologies, such as Solexa or 454.Velvet currently takes in short read sequences, removes errors then produces high quality unique contigs. It then uses paired-end read and long read information, when available, to retrieve the repeated areas between contigs.
  
  
• Lucy 2.20 – DNA Sequence Quality & Vector Trimming
  Lucy has been used for several years to clean sequence data from automated DNA sequencers prior to sequence assembly and other downstream uses.  The quality trimming portion of lucy makes use of phred quality scores, such as those produced by many automated sequencers based on the Sanger sequencing method.  As such, lucy’s quality trimming may not be appropriate for sequence data produced by some of the new “next-generation” sequencers.
  
  
• iAssembler 1.3.2 – de novo Assembly of Roche-454/Sanger Transcriptome Sequences
  iAssembler is a standalone package to assemble ESTs generated using Sanger and/or Roche-454 pyrosequencing technologies into contigs.
  
  
• GAEMR 1.0.1 – Assembly Analysis Framework
  GAEMR (Genome Assembly Evaluation Metrics and Reportin) is a complete genome analysis package that helps you evaluate and report on a genome assembly’s completeness, correctness, and contiguity.
  
  
• PyroCleaner 1.3 – Clean 454 Pyrosequencing Reads in order to ease the Assembly Process
  The pyrocleaner is intended to clean the reads included in the sff file in order to ease the assembly process. It enables filtering sequences on different criteria such as length, complexity, number of undetermined bases which has been proven to correlate with poor quality and multiple copy reads. It also enables to clean paired-ends sff files and generates on one side a sff with the validated paired-ends and on the other the sequences which can be used as shotgun reads.
  
  
• SLiQ – Simple linear Inequalities based Mate-Pair reads Filtering and Scaffolding
  SLIQ , a set of simple linear inequalities derived from the geometry of contigs on the line, can be used to predict the relative positions and orientations of contigs from individual mate pair reads and thus produce a contig digraph.
  
  
• rectangles 2.0 – Rectangle Graph for Repeat Resolution in Genome Assembly
  rectangles is an ultimate tool for resolving repeats in genome assemblies.
  
  
• Arachne 4.6233 – Whole-genome Shotgun Assembler
  ARACHNE is a program for assembling data from whole genome shotgun sequencing experiments. It was designed for long reads from Sanger sequencing technology, and has been used extensively to assemble many genomes, including many that are large and highly repetitive.
  
  
• Reconciliator 2.0 – The tool for Merging Assemblies
  Reconciliator is the tool for merging assemblies.
  
  
• PhrapUMD 2 – Modified version of Phrap
  Phrap UMD consists of the UMD Trimmer, UMD Overlapper and a modified version of Phrap.It is capable of assembling data downloaded directly from the NCBI Trace Archive. The pipeline runs in 3 stages:  first the vector ends of the reads are examined and the vector is found.  Then the reads are trimmed for vector and quality.  After that the trimmed reads afe fed into the 5-pass UMD Overlapper that finds the overlaps, corrects the base caller errors and performs additional trimming if necessary.  After the overlaps are produced, the trimmed and error-corrected reads and overlaps are input into the modified version of Phrap, whichonly puts the reads together if they overlap according to the list of overlaps produced by the UMD Overlapper.
  
  
• DNA Dragon 1.5.6 build1 – DNA Sequence Contig Assembler Software
  DNA Dragon Contig Assembler assembles sequences, trace data (ABI, SCF, AB1), Illumina and Roche 454 flowgrams into contigs. It is a very fast and accurate DNA sequence assembly software. The DNA sequences are assembled into contigs and a direct comparision of trace date with nucleotide data is possible. It also allows for proofreading and base editing.
  

Warning! This software is to be considered under development. Functionality and the user interface may still change significantly from one version to another. If you want to use this software, please stay up to date with the list of known issues:https://github.com/BinPro/CONCOCT/issues

Address of the bookmark: https://github.com/BinPro/CONCOCT

Genomics England will play a key role in building on the UK’s long track record as leader in medical science advances to push the boundaries by unlocking the power of DNA data. The UK will become the first ever country to introduce this technology in its mainstream health system – leading the global race for better tests, better drugs and above all better, more personalised care.

http://www.genomicsengland.co.uk/100k-genome-project/

Next generation quantitative genetics in plants. Jiménez-Gómez, Frontiers in Plant Science 2:77, 2011 Full Text [equally relevant to animal and microbial systems]

Sense from sequence reads: methods for alignment and assembly. Flicek & Birney, Nat Methods 6(11 Suppl):S6-S12, 2009. Full Text

Library construction and experimental design

Statistical design and analysis of RNA sequencing data. Auer & Doerge, Genetics 185(2):405-16, 2010. PubMedCentral

Biases in Illumina transcriptome sequencing caused by random hexamer priming. Hansen et al., Nucleic Acids Res. 38(12): e131, 2010. PubMedCentral

Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries. Aird et al, Genome Biology 12:R18, 2011 Full Text

Amplification-free Illumina sequencing-library preparation facilitates improved mapping and assembly of GC-biased genomes. Kozarewa et al, Nature Methods 6(4):291-5, 2009 PubMedCentral

Cost-effective, high-throughput DNA sequencing libraries for multiplexed target capture. Rohland & Reich, Genome Research 22(5): 939–946. PubMedCentral

Data formats, data management, and alignment software tools

The Sequence Alignment/Map format and SAMtools. Li et al, Bioinformatics 25(16):2078-9, 2009 PubMedCentral

SAM format specification file

Efficient storage of high throughput sequencing data using reference-based compression. Fritz et al, Genome Res 21(5):734-40, 2011. Full Text

Compression of DNA sequence reads in FASTQ format. Deorowicz & Grabowski, Bioinformatics 27(6):860-2, 2011. PubMed

Fast and accurate short read alignment with Burrows-Wheeler transform. Li & Durbin, Bioinformatics 25(14):1754-60, 2009. PubMedCentral

Improving SNP discovery by base alignment quality. Li H, Bioinformatics 27(8):1157-8, 2011. PubMed

BEDTools: a flexible suite of utilities for comparing genomic features. Quinlan and Hall, Bioinformatics 26:841-842, 2010. Publisher Website

Data quality assessment, filtering, and correction

SolexaQA: At-a-glance quality assessment of Illumina second-generation sequencing data. Cox et al, BMC Bioinformatics 11:485, 2010. PubMedCentral

TileQC: a system for tile-based quality control of Solexa data. Dolan & Denver, BMC Bioinformatics 9:250, 2008 PubMedCentral [requires a reference sequence]

Quake: quality-aware detection and correction of sequencing errors. Kelley et al, Genome Biol 11(11):R116, 2010. PubMed

FastQC: a quality control tool for high-throughput sequence data. Home Page

FASTX-toolkit: FASTQ/A short-reads pre-processing tools Home Page

Reference-free validation of short read data. Schröder et al, PLoS One 5(9):e12681, 2010. PubMedCentral

Correction of sequencing errors in a mixed set of reads. Salmela, Bioinformatics 26(10):1284, 2010. Full Text [includes error correction of SOLiD reads in colorspace]

Repeat-aware modeling and correction of short read errors. Yang et al, BMC Bioinformatics 12(Supp1):S52, 2011 PubMedCentral [requires a reference sequence]

HiTEC: accurate error correction in high-throughput sequencing data. Ilie et al, Bioinformatics 27(3):295, 2011 Full Text

Error correction of high-throughput sequencing datasets with non-uniform coverage. Medvedev et al., Bioinformatics 27(13):i137-41, 2011. PubMedCentral

De novo assembly

Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Zerbino & Birney, Genome Res 18(5):821-9, 2008. u>PubMedCentral

Assembly of large genomes using second-generation sequencing. Schatz et al, Genome Res 20(9):1165-73, 2010. PubMedCentral

High-quality draft assemblies of mammalian genomes from massively parallel sequence data. Gnerre et al, PNAS 108(4): 1513-18, 2011 PubMedCentral

Genome assembly has a major impact on gene content: a comparison of annotation in two Bos taurus assemblies. Florea  et al., PLoS One 6(6):e21400, 2011. PubMedCentral

Artemis: an integrated platform for visualization and analysis of high-throughput sequence-based experimental data. Carver et al, Bioinformatics 28(4):464 - 469, 2012 PubMedCentral

Efficient de novo assembly of large genomes using compressed data structures. Simpson & Durbin, Genome Research 22:549-556, 2012 Full Text [Describes the String Graph Assembler (SGA), which assembled a human genome in less than 6 days using 54 Gb of RAM and a 123-processor compute cluster for calculation of an FM-index of the 1.2 billion reads]

Readjoiner: a fast and memory efficient string graph-based sequence assembler. Gonnella & Kurtz, BMC Bioinformatics 13: 82, 2012 PubMedCentral

Assemblathon 1: A competitive assessment of de novo short read assembly methods. Earl et al, Genome Research 21:2224-2241, 2011 Full Text

Chromatin immunoprecipation analysis: ChIP-seq

ChIP-seq: advantages and challenges of a maturing technology. Park, Nat Rev Genet. 10:669-80, 2009 PubMed

ChIP-seq and Beyond: new and improved methodologies to detect and characterize protein-DNA interactions. Furey, Nat Rev Genet 13: 840–852, 2012 Publisher Web Site

MuMoD: a Bayesian approach to detect multiple modes of protein–DNA binding from genome-wide ChIP data. Narlikar, Nucleic Acids Res 41:21–32, 2013 PubMed

Transcriptome analysis

Assembly and comparison to genome

Full-length transcriptome assembly from RNA-Seq data without a reference genome. Grabherr et al, Nature Biotechnology 29:644 - 652, 2011. PubMed [The software is called Trinity, and is available on Sourceforge.]

Comprehensive analysis of RNA-Seq data reveals extensive RNA editing in a human transcriptome. Peng et al, Nature Biotechnology 30:253 - 260, 2012. PubMed [Several comments on this paper question whether the reported differences are in fact evidence of editing or are simply sequencing errors - the authors stand by their conclusions, but the controversy demonstrates the importance of robust data analysis methods.]

Optimization of de novo transcriptome assembly from next-generation sequencing data. Surget-Groba & Montoya-Burgos, Genome Res 20(10):1432-40, 2010. Full Text

Rnnotator: an automated de novo transcriptome assembly pipeline from stranded RNA-Seq reads. Martin et al, BMC Genomics 11:663, 2010 Full Text

De novo assembly and analysis of RNA-seq data. Robertson et al, Nature Methods 7:909-912, 2010 Full Text [describes Trans-ABySS, a pipeline to use the ABySS parallel assembler for de novo transcriptome analysis]

Differential expression analysis

R-SAP: a multi-threading computational pipeline for the characterization of high-throughput RNA-sequencing data. Mittal & McDonald, Nucleic Acids Res, 2012 Full Text

Targeted RNA sequencing reveals the deep complexity of the human transcriptome. Mercer et al, Nature Biotechnology 30:99 - 104, 2012 Publisher Website

Differential gene and transcript expression analysis of RNA-Seq experiments with TopHat and Cufflinks. Trapnell et al, Nature Protocols 7:562 - 578, 2012 Publisher Website

Characterization and improvement of RNA-Seq precision in quantitative transcript expression profiling. Łabaj et al, Bioinformatics 27:i383 - i391, 2011 Full Text

Improving RNA-Seq expression estimates by correcting for fragment bias. Roberts et al, Genome Biol 12:R22, 2011 PubMed Central

Cloud-scale RNA-sequencing differential expression analysis with Myrna. Langmead et al, Genome Biol 11:R83, 2010 Full Text

From RNA-seq reads to differential expression results. Oshlack et al, Genome Biol 11(12):220, 2010 Full Text

DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Wang et al., Bioinformatics. 26(1):136-8. 2010 PubMed

DEseq: Differential expression analysis for sequence count data. Anders and Huber, Genome Biology 11:R106, 2010 Full Text

edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Robinson et al., Bioinformatics 26(1):139-40 2010 PubMedCentral

Two-stage Poisson model for testing RNA-seq data. Auer and Doerge, SAGMB 10(1), article 26 Full Text

Experimental design, preprocessing, normalization and differential expression analysis of small RNA sequencing experiments. McCormick et al., Silence2(1):2, 2011 PubMedCentral

RNA-Seq gene expression estimation with read mapping uncertainty. Li et al, Bioinformatics 26:493-500, 2010 PubMedCentral [describes the RSEM software package]

Comparing genomes and assemblies; variant detection

Versatile and open software for comparing large genomes. Kurtz et al, Genome Biol (5(2):R12, 2004. PubMedCentral [describes the MUMmer software for full-genome alignment & comparisons]

Searching for SNPs with cloud computing. Langmead et al, Genome Biol 10(11):R134, 2009 Full Text

Calling SNPs without a reference sequence. Ratan et al, BMC Bioinformatics 11:130, 2010 PubMedCentral

Microindel detection in short-read sequence data. Krawitz et al, Bioinformatics 26(6):722-9, 2010. Full Text

vipR: variant identification in pooled DNA using R. Altmann et al., Bioinformatics 27: i77-i84, 2011. PubMedCentral

Geoseq: a tool for dissecting deep-sequencing datasets. Gurtowski et al, BMC Bioinformatics 11:506, 2010. PubMedCentral [Geoseq is a web service that allows searching deep sequencing datasets with a reference sequence of a gene of interest]

Detecting and annotating genetic variations using the HugeSeq pipeline. Lam et al, Nature Biotechnology 30:226 - 229, 2012 Publisher Website, Home Page

Genome-wide LORE1 retrotransposon mutagenesis and high-throughput insertion detection in Lotus japonicus. Urbański et al, Plant J 64:731-741, 2012. Publisher Website [This paper describes a 2-dimensional pooling strategy with barcoding to allow use of Illumina sequencing to screen for retrotransposon insertion mutations, and includes a software package called FSTpoolit for analysis of the resulting sequence reads.]

Genotyping by sequencing

Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Davey et al., Nat Rev Genet 12(7):499-510, 2011 PubMed [A review of methods available at the time]

A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. Elshire et al., PLoS One 6(5):e19379, 2011. Full Text

Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach. Poland et al., PLoS One 7(2): e32253, 2012. Full Text

Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. Peterson et al, PLoS One 7(5):e37135, . 2012. Full Text

Imputation of unordered markers and the impact on genomic selection accuracy. Rutkowski et al, G3 3(3):427-39, 2013. Full Text

Diversity Arrays Technology (DArT) and next-generation sequencing combined: genome-wide, high-throughput, highly informative genotyping for molecular breeding of Eucalyptus. Sansaloni et al., BMC Proceedings 5(Suppl 7):P54, 2011 Full Text

High-throughput genotyping by whole-genome resequencing. Huang et al., Genome Res 19(6):1068-76, 2009. Full Text

Multiplexed shotgun genotyping for rapid and efficient genetic mapping. Andolfatto et al. Genome Res 21(4):610-7, 2011. Full Text

Restriction-site Associated DNA (RAD) markers

Rapid SNP discovery and genetic mapping using sequenced RAD markers. Baird et al, PLoS One 3(10):e3376, 2008 Full Text

Linkage mapping and comparative genomics using next-generation RAD sequencing of a non-model organism. Baxter et al., PLoS One 6(4):e19315, 2011. Full Text

Genome evolution and meiotic maps by massively parallel DNA sequencing: spotted gar, an outgroup for the teleost genome duplication. Amores et al, Genetics 188(4):799-808, 2011. PubMed

Construction and application for QTL analysis of a Restriction-site Associated DNA (RAD) linkage map in barley. Chutimanitsakun et al, BMC Genomics 4; 12:4, 2011. Full Text

RAD tag sequencing as a source of SNP markers in Cynara cardunculus L. Scaglione et al., BMC Genomics 13:3, 2012. Full Text

Paired-end RAD-seq for de novo assembly and marker design without available reference. Willing et al., Bioinformatics 27(16):2187-93, 2011. Publisher Website

Local de novo assembly of RAD paired-end contigs using short sequencing reads. Etter et al., PLOS ONE 6(4): e18561, 2011. Full Text

Stacks: building and genotyping loci de novo from short-read sequences. Catchen et al., G3: Genes, Genomes, Genetics, 1:171-182, 2011. Full Text, Home Page

Rainbow: an integrated tool for efficient clustering and assembling RAD-seq reads. Chong et al, Bioinformatics 28(21):2732-7, 2012. Publisher Website

UK RAD Sequencing Wiki page, with bibliography and RADTools software download Home Page

Workspace environments

Papers

Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Goecks et al, Genome Biol 11(8):R86, 2010 PubMedCentral

Galaxy Cloudman: Delivering compute clusters. BMC Bioinformatics 11(Suppl. 12):S4, 2010 Full Text

The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. McKenna et al, Genome Res 20(9):1297-303, 2010. PubMedCentral

A framework for variation discovery and genotyping using next-generation DNA sequencing data. DePristo et al., Nat Genet 43(5):491-8, 2011. PubMed

Online resources

The R statistical computing environment includes Bioconductor, a specialized set of tools for analysis of microarray and high-throughput sequencing data. Introductory materials from on-line or short workshops are widely available online; examples are Evomics2012 Bioconductor-tutorial.pdf, and Intro to Bioconductor. Materials from an advanced course on high-throughput genetic data analysis are at Seattle 2012 materials. Thomas Girke of UC-Riverside has written a very complete set of manuals describing the use of R and Bioconductor for analysis of genomic datasets, available at R and Bioconductor Manuals.
Manuals and contributed documentation for R are available at the R-project.org website, and video tutorials are also available on Youtube; those posted by Tutorlol are brief, clear, and to the point.
Materials from a series of mini-courses in R taught in 2010 at UCLA are available:

• Intro to programming and graphics
• Data manipulation and functions
• Graphics for exploratory data analysis
• Introductory statistics
• Linear regression

A Little Book of R for Bioinformatics is an on-line resource with information and exercises to provide practice in bioinformatics analysis of DNA sequences and other biological data in R.
Many books on specific topics in R programming are also available through Amazon or other vendors.

Cloud computing resources

The case for cloud computing in genome informatics. Lincoln Stein, Genome Biol. 11(5):207, 2010 Pubmed

Galaxy Cloudman: delivering cloud compute clusters. Afgan et al, BMC Bioinformatics 11(Suppl 12):S4, 2010 Full Text

CloudBioLinux is an open-source project that provides a bioinformatics Linux system for cloud computing, pre-configured with a variety of software tools installed and ready to use.

A tutorial on getting started with CloudBioLinux on the Amazon Web Services Elastic Compute Cloud (EC2)

“Deploying Galaxy on the Cloud” – slides from a presentation by Enis Afgan (Emory University) at the
 Bioinformatics Open Source Conference in Boston, July 2010

A screencast that provides a step-by-step guide to starting a Galaxy cluster in the EC2 environment

A webpage that has the same information in text form, and is the basis for the screencast

The iPlant Collaborative, an NSF-funded project to create computational resources for plant biology research, provides access to cloud computing resources through Atmosphere

SeqWare Query Engine: storing and searching sequence data in the cloud. O’Connor et al, BMC Bioinformatics 11(Suppl 12):S2, 2010 Full Text

An overview of the Hadoop/MapReduce/HBase framework and its current applications in bioinformatics. Taylor, BMC Bioinformatics 11(Suppl 12):S1, 2010 Full Text

Links to Linux command-line tutorials and resources

Tutorials for AWK, a powerful tool for handling data tables

• A set of awk notes from Boston University
• Bruce Barnett's awk tutorial
• Greg Goebel's awk tutorial
• Executing an awk command from R to simplify data exploratory analysis, from Lex Nederbragt

Tutorials for bash shell scripting

• A tutorial at linuxconfig.org
• A Getting Started With Bash tutorial at hypexr.org
• Mendel Cooper's Advanced Bash Shell-Scripting Guide

Tutorials for sed, the command-line stream editor

• A tutorial at Rutgers
• Peteris Krumins claims to have the World's Best Introduction to Sed; take a look and judge for yourself.
• Bruce Barnett's sed tutorial.

Links to other useful sites

The SEQanswers online community has forums on several topics related to sequencing; the bioinformatics forum is the most active.

The SEQanswers Software Wiki is a list of software for analysis of sequencing data

Biostar is another online community for questions and answers on bioinformatics and computational genomics.

Information on file formats used by the University of California - Santa Cruz Genome Browser is on the FAQ list

A manual for the Integrated Genome Browser visualization tool is here

Course materials for a short course entitled Introduction to R and Bioconductor, held in Seattle in Dec 2010

Genomic Regions Enrichment of Annotations Tool - A web service to test for over-representation of specific ontology categories among genes near ChIP-seq peaks

Next-gen-seq software - a list of software packages, both commercial and open-source, related to analysis of deep sequencing datasets

Software from the Center for Bioinformatics and Computational Biology, University of Maryland - many useful programs, all open-source

PLAZA: a comparative genomics resource to study gene and genome evolution in plants; described by Proost et al, Plant Cell 21:3718, 2010 Full Text

The European Bioinformatics Institute provides tools ArrayExpressHTS and R-Cloud for analysis of transcriptome data