ArticlePLoS computational biology2014
A scalable and accurate targeted gene assembly tool (SAT-Assembler) for next-generation sequencing data.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
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- MCRL: using a reference library to compress a metagenome into a non-redundant list of sequences, considering viruses as a case study.Bioinformatics (Oxford, England) · 2022Article
- PlantTribes2: Tools for comparative gene family analysis in plant genomics.Frontiers in plant science · 2022Article
- Unleashing the power within short-read RNA-seq for plant research: Beyond differential expression analysis and toward regulomics.Frontiers in plant science · 2022Review
- Lactation Associated Genes Revealed in Holstein Dairy Cows by Weighted Gene Co-Expression Network Analysis (WGCNA).Animals : an open access journal from MDPI · 2021Article
- Quantitative comparison between the rhizosphere effect of Arabidopsis thaliana and co-occurring plant species with a longer life history.The ISME journal · 2020Article
- Targeted domain assembly for fast functional profiling of metagenomic datasets with S3A.Bioinformatics (Oxford, England) · 2020Article
- Review, Evaluation, and Directions for Gene-Targeted Assembly for Ecological Analyses of Metagenomes.Frontiers in genetics · 2019Article
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- MegaGTA: a sensitive and accurate metagenomic gene-targeted assembler using iterative de Bruijn graphs.BMC bioinformatics · 2017Article
- A sensitive short read homology search tool for paired-end read sequencing data.BMC bioinformatics · 2017Article
- GenSeed-HMM: A Tool for Progressive Assembly Using Profile HMMs as Seeds and its Application in Alpavirinae Viral Discovery from Metagenomic Data.Frontiers in microbiology · 2016Article
- Reconstructing 16S rRNA genes in metagenomic data.Bioinformatics (Oxford, England) · 2015Article
- Article
Corrections and comments
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Gene assembly, which recovers gene segments from short reads, is an important step in functional analysis of next-generation sequencing data. Lacking quality reference genomes, de novo assembly is commonly used for RNA-Seq data of non-model organisms and metagenomic data. However, heterogeneous sequence coverage caused by heterogeneous expression or species abundance, similarity between isoforms or homologous genes, and large data size all pose challenges to de novo assembly. As a result, existing assembly tools tend to output fragmented contigs or chimeric contigs, or have high memory footprint. In this work, we introduce a targeted gene assembly program SAT-Assembler, which aims to recover gene families of particular interest to biologists. It addresses the above challenges by conducting family-specific homology search, homology-guided overlap graph construction, and careful graph traversal. It can be applied to both RNA-Seq and metagenomic data. Our experimental results on an Arabidopsis RNA-Seq data set and two metagenomic data sets show that SAT-Assembler has smaller memory usage, comparable or better gene coverage, and lower chimera rate for assembling a set of genes from one or multiple pathways compared with other assembly tools. Moreover, the family-specific design and rapid homology search allow SAT-Assembler to be naturally compatible with parallel computing platforms. The source code of SAT-Assembler is available at https://sourceforge.net/projects/sat-assembler/. The data sets and experimental settings can be found in supplementary material.
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