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Kelley Ryan Matthew

Bio: Kelley Ryan Matthew is an academic researcher from Illumina. The author has contributed to research in topics: Reference genome & Nucleic acid. The author has an hindex of 3, co-authored 5 publications receiving 9982 citations.

Papers
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Journal ArticleDOI
TL;DR: TopHat2 is described, which incorporates many significant enhancements to TopHat, and combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes.
Abstract: TopHat is a popular spliced aligner for RNA-sequence (RNA-seq) experiments. In this paper, we describe TopHat2, which incorporates many significant enhancements to TopHat. TopHat2 can align reads of various lengths produced by the latest sequencing technologies, while allowing for variable-length indels with respect to the reference genome. In addition to de novo spliced alignment, TopHat2 can align reads across fusion breaks, which can occur after genomic translocations. TopHat2 combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes. TopHat2 is available at http://ccb.jhu.edu/software/tophat.

11,380 citations

Patent
01 May 2018
TL;DR: In this article, the authors describe a set of index oligonucleotides configured to identify sources of samples of nucleic acids and methods, apparatus, systems and computer program products for identifying and making the indices.
Abstract: The disclosed embodiments concern index oligonucleotides configured to identify sources of samples of nucleic acids and methods, apparatus, systems and computer program products for identifying and making the index oligonucleotides. In some implementations, the index oligonucleotides include a set of index sequences, a Hamming distance between any two index sequences of the set of index sequences meeting one or more criteria. System, apparatus, and computer program products are also provided for determining a sequence of interest using the index oligonucleotides.

5 citations

Patent
07 May 2018
TL;DR: In this paper, the authors describe a set of index oligonucleotides configured to identify sources of samples of nucleic acids and methods, apparatus, systems and computer program products for identifying and making the indices.
Abstract: The disclosed embodiments concern index oligonucleotides configured to identify sources of samples of nucleic acids and methods, apparatus, systems and computer program products for identifying and making the index oligonucleotides. In some implementations, the index oligonucleotides include a set of index sequences, a Hamming distance between any two index sequences of the set of index sequences meeting one or more criteria. System, apparatus, and computer program products are also provided for determining a sequence of interest using the index oligonucleotides.

4 citations

Patent
11 Jul 2019
TL;DR: In this paper, a computer-implemented method of aligning RNA including receiving onto a data storage unit primer sequences and transcript sequences transcribable from a reference genome based on a gene model, generating target sequences to be amplified from a combination of the primer and the transcript sequences, generating a modified reference genome, aligning sequence reads generated from a test sample comprising RNA amplicon molecules to the of target sequences, and generating an alignment profile for the test sample based on the aligning.
Abstract: Provided is a computer-implemented method of aligning RNA including receiving onto a data storage unit primer sequences and transcript sequences transcribable from a reference genome based on a gene model, generating target sequences to be amplified from a combination of the primer sequences and the transcript sequences, generating a modified reference genome based on the plurality of target sequences, aligning sequence reads generated from a test sample comprising RNA amplicon molecules to the of target sequences, and generating an alignment profile for the test sample based on the aligning. Also provided is a computer system for performing the foregoing method.

1 citations

Patent
18 Jul 2019
TL;DR: In this paper, the index sequence incorporated into each index site of the nucleic acid fragment is selected from a plurality of distinguishable index sequences and such that the population of generated index fragments represents each index sequence from the plurality.
Abstract: Presented herein are techniques for indexing of nucleic acid, e.g., for use in conjunction with sequencing. The techniques include generating indexed nucleic acid fragments from an individual sample, whereby the index sequence incorporated into each index site of the nucleic acid fragment is selected from a plurality of distinguishable of index sequences and such that the population of generated nucleic acid fragments represents each index sequence from the plurality. In this manner, the generated indexed nucleic acid fragments from a single sample are indexed with a diverse mix of index sequences that reduce misassignment due to index read errors associated with low sequence diversity.

Cited by
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Journal ArticleDOI
TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
Abstract: In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html .

47,038 citations

Posted ContentDOI
17 Nov 2014-bioRxiv
TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
Abstract: In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-Seq data, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data. DESeq2 uses shrinkage estimation for dispersions and fold changes to improve stability and interpretability of the estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression and facilitates downstream tasks such as gene ranking and visualization. DESeq2 is available as an R/Bioconductor package.

17,014 citations

Journal ArticleDOI
TL;DR: Tests showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method, and requires only 4.3 gigabytes of memory.
Abstract: HISAT (hierarchical indexing for spliced alignment of transcripts) is a highly efficient system for aligning reads from RNA sequencing experiments. HISAT uses an indexing scheme based on the Burrows-Wheeler transform and the Ferragina-Manzini (FM) index, employing two types of indexes for alignment: a whole-genome FM index to anchor each alignment and numerous local FM indexes for very rapid extensions of these alignments. HISAT's hierarchical index for the human genome contains 48,000 local FM indexes, each representing a genomic region of ∼64,000 bp. Tests on real and simulated data sets showed that HISAT is the fastest system currently available, with equal or better accuracy than any other method. Despite its large number of indexes, HISAT requires only 4.3 gigabytes of memory. HISAT supports genomes of any size, including those larger than 4 billion bases.

13,192 citations

Journal ArticleDOI
TL;DR: StringTie, a computational method that applies a network flow algorithm originally developed in optimization theory, together with optional de novo assembly, to assemble these complex data sets into transcripts produces more complete and accurate reconstructions of genes and better estimates of expression levels.
Abstract: Methods used to sequence the transcriptome often produce more than 200 million short sequences. We introduce StringTie, a computational method that applies a network flow algorithm originally developed in optimization theory, together with optional de novo assembly, to assemble these complex data sets into transcripts. When used to analyze both simulated and real data sets, StringTie produces more complete and accurate reconstructions of genes and better estimates of expression levels, compared with other leading transcript assembly programs including Cufflinks, IsoLasso, Scripture and Traph. For example, on 90 million reads from human blood, StringTie correctly assembled 10,990 transcripts, whereas the next best assembly was of 7,187 transcripts by Cufflinks, which is a 53% increase in transcripts assembled. On a simulated data set, StringTie correctly assembled 7,559 transcripts, which is 20% more than the 6,310 assembled by Cufflinks. As well as producing a more complete transcriptome assembly, StringTie runs faster on all data sets tested to date compared with other assembly software, including Cufflinks.

6,594 citations

Journal ArticleDOI
TL;DR: Kallisto pseudoaligns reads to a reference, producing a list of transcripts that are compatible with each read while avoiding alignment of individual bases, which removes a major computational bottleneck in RNA-seq analysis.
Abstract: We present kallisto, an RNA-seq quantification program that is two orders of magnitude faster than previous approaches and achieves similar accuracy. Kallisto pseudoaligns reads to a reference, producing a list of transcripts that are compatible with each read while avoiding alignment of individual bases. We use kallisto to analyze 30 million unaligned paired-end RNA-seq reads in <10 min on a standard laptop computer. This removes a major computational bottleneck in RNA-seq analysis.

6,468 citations