Streaming fragment assignment for real-time analysis of sequencing experiments

By Adam Roberts, Lior S. Pachter. Nature Methods, 2012

1,015 citations recorded by the source corpus.

We present eXpress, a software package for efficient probabilistic assignment of ambiguously mapping sequenced fragments. eXpress uses a streaming algorithm with linear run time and constant memory use. It can determine abundances of sequenced molecules in real time and can be applied to ChIP-seq, metagenomics and other large-scale sequencing data. We demonstrate its use on RNA-seq data and show that eXpress achieves greater efficiency than other quantification methods.

View Paper: https://www.semanticscholar.org/paper/ba4a3005b6f74c62fcc5585e9945085902d3276c

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Citations in the corpus

Gaining comprehensive biological insight into the transcriptome by performing a broad-spectrum RNA-seq analysis (2017, methodology): “When a transcriptomic reference is available, reads can be directly aligned to it followed by an abundance estimation step using tools like RSEM 37 and eXpress 18 .”
De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with Trinity (2013, methodology): “Several methods 4,14,22 were recently developed to estimate how to correctly allocate such reads to transcripts in a way that best approximates the transcripts’ true expression levels.”
RNA Sequencing Data: Hitchhiker's Guide to Expression Analysis (2018, background): “, onlineEM), rather than the factorization of the underlying likelihood function [82] [83] .”
Next maSigPro: updating maSigPro bioconductor package for RNA-seq time series (2014, methodology): “…et al. , 2010) and DEseq (Anders and Huber, 2010) updated microarray analysis to RNA-seq by incorporating appropriate statistical models, whereas other methodologies were developed specifically for the new technology (Roberts and Pachter, 2013; Tarazona et al. , 2011; Trapnell et al. , 2012).”
A survey of best practices for RNA-seq data analysis (2016, methodology): “These methods allocate multi-mapping reads among transcript and output within-sample normalized values corrected for sequencing biases [35, 41, 43].”
expVIP: a Customizable RNA-seq Data Analysis and Visualization Platform1[OPEN] (2016, methodology): “4) using the parameters recommended by eXpress (Roberts and Pachter, 2013): output in sam format (-S), maximum insert size of 800 bp (-X 800), and unlimited multimappings (-a).”
Statistically based splicing detection reveals neural enrichment and tissue-specific induction of circular RNA during human fetal development (2015, background): “Additionally, as pointed out in [24], counting both reads could result in double counting individual reads if both sides of a read are junctional, as would be expected for long reads and small inserts or small circles.”
A Unified Algorithmic Framework for Block-Structured Optimization Involving Big Data: With applications in machine learning and signal processing (2015, methodology): “For example, emerging problems in image processing, social network analysis, and computational biology can easily exceed millions or billions of variables, and significant research is underway to enable fast accurate solutions to these problems [1]–[4].”
Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms (2013, methodology): “Unlike synthetic test data used in previous work [5, 10], the procedure used by the Flux Simulator is not based specifically on the generative model underlying our estimation procedure.”
Salmon: fast and bias-aware quantification of transcript expression using dual-phase inference (2017, methodology): “Using experimental data from the GEUVADIS [11] and SEQC [12] studies, and synthetic data from the Polyester [13] and RSEM-sim [14] simulators, we benchmark Salmon against kallisto [10] and eXpress [15] + Bowtie2 [16]; both of these methods also implement their own bias models.”