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
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
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
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
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
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
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]
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]
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.]
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
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
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:
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.
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. OConnor 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
Tutorials for AWK, a powerful tool for handling data tables
Tutorials for bash shell scripting
Tutorials for sed, the command-line stream editor
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
