SHRiMP: Accurate Mapping of Short Color-space Reads

Rumble, Stephen M.; Lacroute, Phil; Dalca, Adrian V.; Fiume, Marc; Sidow, Arend; Brudno, Michael

doi:10.1371/journal.pcbi.1000386

Cited by 512 publications

(416 citation statements)

References 20 publications

Supporting

Mentioning

410

Contrasting

Unclassified

Order By: Relevance

“…16 Clement et al 17 introduced a program called GNUMAP (Genomic Next generation Universal MAPper), which uses the quality score to get more accurate results from fewer sequencing runs (which are often costly). Other tools such as PASS, 18 SOAP2, 19 Bowtie, 20 CloudBurst, 15 MAQ, 21 ZOOM, 22 SHRIMP, 23 PERM 24 and others are also designed recently for NGS data.…”

Section: Mapping Tools Overviewmentioning

confidence: 99%

“…Quality scores that come with reads from NGS platforms (mainly from Illumina) are, arguably, crucial in preventing the possibility of trivial matches during the mapping. Most of the tools [18][19][20][21][22][23][24][25][26]28 available now use base quality information when they do mapping tasks, although some of them may not fully use it to advance mapping accuracy. However, there are also some programs, such as CloudBurst, SeqMap, MOM, ProbeMatch and Slider, that involve nucleotide information only for short reads alignment.…”

Section: Mapping Tools Overviewmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of next-generation sequencing software in mapping and assembly

et al. 2011

View full text Add to dashboard Cite

Next-generation high-throughput DNA sequencing technologies have advanced progressively in sequence-based genomic research and novel biological applications with the promise of sequencing DNA at unprecedented speed. These new non-Sanger-based technologies feature several advantages when compared with traditional sequencing methods in terms of higher sequencing speed, lower per run cost and higher accuracy. However, reads from next-generation sequencing (NGS) platforms, such as 454/Roche, ABI/SOLiD and Illumina/Solexa, are usually short, thereby restricting the applications of NGS platforms in genome assembly and annotation. We presented an overview of the challenges that these novel technologies meet and particularly illustrated various bioinformatics attempts on mapping and assembly for problem solving. We then compared the performance of several programs in these two fields, and further provided advices on selecting suitable tools for specific biological applications.

show abstract

Section: Mapping Tools Overviewmentioning

confidence: 99%

Section: Mapping Tools Overviewmentioning

confidence: 99%

Evaluation of next-generation sequencing software in mapping and assembly

et al. 2011

View full text Add to dashboard Cite

show abstract

“…The N. gonorrhoeae strain MS11 small transcriptome sequencing data were mapped to the reference genome assembly GCA_00156855.2; the FA1090 whole transcriptome sequencing data were mapped to the reference genome assembly GCA_0000068451; the NCCP11945 whole transcriptome sequencing data were mapped to the reference genome assembly GCA_000020105.1; and, the N. meningitidis FAM18 whole trancriptome sequencing data were mapped to the reference genome assembly GCA_000009465.1. All transcriptome maps were created using the Nesoni data analysis toolset available through the Victorian Bioinformatics Consortium (http://www.vicbioinformatics.com/software.nesoni.shtml) which uses the SHRiMP read aligner and produces files that may be supplied to Artemis for graphic visualization (Rumble et al, 2009;Carver et al, 2012). Visualization of genomic locations of transcripts and histograms of transcript read depth were generated using the Circos software package version 0.66 (Krzywinski et al, 2009).…”

Section: Methodsmentioning

confidence: 99%

pilS loci in Neisseria gonorrhoeae are transcriptionally active

et al. 2015

View full text Add to dashboard Cite

Piliation is an important virulence determinant for Neisseria gonorrhoeae. PilE polypeptide is the major protein subunit in the pilus organelle and engages in extensive antigenic variation due to recombination between pilE and a pilS locus. pilS were so-named as they are believed to be transcriptionally silent, in contrast to the pilE locus. In this study, we demonstrate the presence of a small, pil-specific RNA species. Through using a series of pilE deletion mutants, we show by Northern blotting and quantitative reverse transcriptase PCR analysis (qRT-PCR), that these smaller RNA species are not derived from the primary pilE transcript following some processing events, but rather, arose through transcription of the pilS loci. Small transcriptome analysis, in conjunction with analysis of pilS recombinants, identified both sense and anti-sense RNAs originating from most, but not all, of the pilS gene copies. Focusing on the MS11 pilS6 locus, we identified by site-directed mutagenesis a sense promoter located immediately upstream of pilS6 copy 2, as well as an anti-sense promoter immediately downstream of pilS6 copy 1. Whole transcriptome analysis also revealed the presence of pil-specific sRNA in both gonococci and meningococci. Overall, this study reveals an added layer of complexity to the pilE/pilS recombination scheme by demonstrating pil-specific transcription within genes that were previously thought to be transcriptionally silent.

show abstract

“…They are often used to infer exon-exon splice junctions and will be introduced in the next section. Currently, two classic approaches are widely used in the unspliced short read mappers ( [12][13][14][15][16][17][18][19][20][21][22][23]. Hash-based implementations (such as Maq [12], ZOOM [13], RMAP [14], SeqMap [15], and SOAP [16]) can be further differentiated into two classes based on the memory usage.…”

Section: Short Read Mappingmentioning

confidence: 99%

Overview of available methods for diverse RNA-Seq data analyses

Chen

Wang

Shi

2011

Sci. China Life Sci.

View full text Add to dashboard Cite

RNA-Seq technology is becoming widely used in various transcriptomics studies; however, analyzing and interpreting the RNA-Seq data face serious challenges. With the development of high-throughput sequencing technologies, the sequencing cost is dropping dramatically with the sequencing output increasing sharply. However, the sequencing reads are still short in length and contain various sequencing errors. Moreover, the intricate transcriptome is always more complicated than we expect. These challenges proffer the urgent need of efficient bioinformatics algorithms to effectively handle the large amount of transcriptome sequencing data and carry out diverse related studies. This review summarizes a number of frequently-used applications of transcriptome sequencing and their related analyzing strategies, including short read mapping, exon-exon splice junction detection, gene or isoform expression quantification, differential expression analysis and transcriptome reconstruction. To date, RNA-Seq has been applied to a number of species for various research, such as inferring alternative splicing [4,5], quantifying the expression of genes and transcripts [6,7], detecting gene fusions [8,9], revealing long noncoding RNAs (lncRNAs) [10], and identifying single nucleotide variants (SNVs) in expressed exons [11]. Although RNA-Seq has brought tremendous benefits to these studies, it also faces many challenges from both sequencing technologies themselves and bioinformatics analyses of the data. In detail, RNA-Seq has biases in library construction, and strand-specific libraries are still not easy to be produced but are important for determining the orientation of transcripts [1]. Furthermore, RNA-Seq generates a large amount of data, and the read length is generally short and sequencing errors exist in the reads. These aspects challenge the corresponding methods and algorithms to effectively process the large amount of RNA-Seq data.

show abstract

SHRiMP: Accurate Mapping of Short Color-space Reads

Cited by 512 publications

References 20 publications

Evaluation of next-generation sequencing software in mapping and assembly

Evaluation of next-generation sequencing software in mapping and assembly

pilS loci in Neisseria gonorrhoeae are transcriptionally active

Overview of available methods for diverse RNA-Seq data analyses

Contact Info

Product

Resources

About