scholarly journals TransRate: reference free quality assessment of de-novo transcriptome assemblies

2015 ◽  
Author(s):  
Richard D Smith-Unna ◽  
Chris Boursnell ◽  
Rob Patro ◽  
Julian M Hibberd ◽  
Steven Kelly
Keyword(s):  
Quality Assessment ◽  
De Novo ◽  
De Novo Transcriptome ◽  
Rna Molecules

TransRateis a tool for reference-free quality assessment of de novo transcriptome assemblies. Using only sequenced reads as the input,TransRatemeasures the quality of individual contigs and whole assemblies, enabling assembly optimization and comparison.TransRatecan accurately evaluate assemblies of conserved and novel RNA molecules of any kind in any species. We show that it is more accurate than comparable methods and demonstrate its use on a variety of data.

Microarray-Based Quality Assessment as a Supporting Criterion for de novo Transcriptome Assembly Selection

2020 ◽  
Vol 17 (1) ◽  
pp. 198-206
Author(s):  
Patricia Carvajal-Lopez ◽  
Fernando D. Von Borstel ◽  
Amada Torres ◽  
Gabriella Rustici ◽  
Joaquin Gutierrez ◽  
...  
Keyword(s):  
Quality Assessment ◽  
De Novo ◽  
Transcriptome Assembly ◽  
De Novo Transcriptome Assembly ◽  
De Novo Transcriptome

scholarly journals dnAQET: a framework to compute a consolidated metric for benchmarking quality of de novo assemblies

BMC Genomics ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Gokhan Yavas ◽  
Huixiao Hong ◽  
Wenming Xiao
Keyword(s):  
Quality Assessment ◽  
Genome Assembly ◽  
Reference Genome ◽  
De Novo ◽  
Quality Score ◽  
De Novo Genome Assembly ◽  
Genome Assemblies ◽  
Reference Genomes ◽  
Better Than

Abstract Background Accurate de novo genome assembly has become reality with the advancements in sequencing technology. With the ever-increasing number of de novo genome assembly tools, assessing the quality of assemblies has become of great importance in genome research. Although many quality metrics have been proposed and software tools for calculating those metrics have been developed, the existing tools do not produce a unified measure to reflect the overall quality of an assembly. Results To address this issue, we developed the de novo Assembly Quality Evaluation Tool (dnAQET) that generates a unified metric for benchmarking the quality assessment of assemblies. Our framework first calculates individual quality scores for the scaffolds/contigs of an assembly by aligning them to a reference genome. Next, it computes a quality score for the assembly using its overall reference genome coverage, the quality score distribution of its scaffolds and the redundancy identified in it. Using synthetic assemblies randomly generated from the latest human genome build, various builds of the reference genomes for five organisms and six de novo assemblies for sample NA24385, we tested dnAQET to assess its capability for benchmarking quality evaluation of genome assemblies. For synthetic data, our quality score increased with decreasing number of misassemblies and redundancy and increasing average contig length and coverage, as expected. For genome builds, dnAQET quality score calculated for a more recent reference genome was better than the score for an older version. To compare with some of the most frequently used measures, 13 other quality measures were calculated. The quality score from dnAQET was found to be better than all other measures in terms of consistency with the known quality of the reference genomes, indicating that dnAQET is reliable for benchmarking quality assessment of de novo genome assemblies. Conclusions The dnAQET is a scalable framework designed to evaluate a de novo genome assembly based on the aggregated quality of its scaffolds (or contigs). Our results demonstrated that dnAQET quality score is reliable for benchmarking quality assessment of genome assemblies. The dnQAET can help researchers to identify the most suitable assembly tools and to select high quality assemblies generated.

scholarly journals De novo transcriptome sequencing and comparative analysis of midgut tissues of four non-model insects pertaining to Hemiptera, Coleoptera, Diptera and Lepidoptera

2017 ◽  
Author(s):  
Rajesh K. Gazara ◽  
Christiane Cardoso ◽  
Daniel Bellieny-Rabelo ◽  
Clélia Ferreira ◽  
Walter R. Terra ◽  
...  
Keyword(s):  
Spodoptera Frugiperda ◽  
De Novo ◽  
Morphological Diversity ◽  
Evolutionary Information ◽  
De Novo Transcriptome ◽  
Cytochrome P450 Genes ◽  
Computational Strategy ◽  
Shed Light ◽  
Dysdercus Peruvianus

ABSTRACTDespite the great morphological diversity of insects, there is a regularity in their digestive functions, which is apparently related to their physiology. In the present work we report the de novo midgut transcriptomes of four non-model insects from four distinct orders: Spodoptera frugiperda (Lepidoptera), Musca domestica (Diptera), Tenebrio molitor (Coleoptera) and Dysdercus peruvianus (Hemiptera). We employed a computational strategy to merge assemblies obtained with two different algorithms, which substantially increased the quality of the final transcriptomes. Unigenes were annotated and analyzed using the eggNOG database, which allowed us to assign some level of functional and evolutionary information to 79.7% to 93.1% of the transcriptomes. We found interesting transcriptional patterns, such as: i) the intense use of lysozymes in digestive functions of M. domestica larvae, which are streamlined and adapted to feed on bacteria; ii) the up-regulation of orthologous UDP-glycosyl transferase and cytochrome P450 genes in the whole midguts different species, supporting the presence of an ancient defense frontline to counter xenobiotics; iii) evidence supporting roles for juvenile hormone binding proteins in the midgut physiology, probably as a way to activate genes that help fight anti-nutritional substances (e.g. protease inhibitors). The results presented here shed light on the digestive and structural properties of the digestive systems of these distantly related species. Furthermore, the produced datasets will also be useful for scientists studying these insects.

scholarly journals Compacting and correcting Trinity and Oases RNA-Seq de novo assemblies

2016 ◽  
Author(s):  
Cédric Cabau ◽  
Frédéric Escudié ◽  
Anis Djari ◽  
Yann Guiguen ◽  
Julien Bobe ◽  
...  
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Error Rates ◽  
Rna Seq ◽  
De Novo Transcriptome ◽  
Software Packages ◽  
Redundancy Reduction ◽  
Assembly Pipeline ◽  
Free Open Source

Background De novo transcriptome assembly of short reads is now a common step in expression analysis of organisms lacking a reference genome sequence. Several software packages are available to perform this task. Even if their results are of good quality it is still possible to improve them in several ways including redundancy reduction or error correction. Trinity and Oases are two commonly used de novo transcriptome assemblers. The contig sets they produce are of good quality. Still, their compaction (number of contigs needed to represent the transcriptome) and their quality (chimera and nucleotide error rates) can be improved. Results We built a de novo RNA-Seq Assembly Pipeline (DRAP) which wraps these two assemblers (Trinity and Oases) in order to improve their results regarding the above-mentioned criteria. DRAP reduces from 1,3 to 15 fold the number of resulting contigs of the assemblies depending on the read set and the assembler used. This article presents seven assembly comparisons showing in some cases drastic improvements when using DRAP. DRAP does not significantly impair assembly quality metrics such are read realignment rate or protein reconstruction counts. Conclusion Transcriptome assembly is a challenging computational task even if good solutions are already available to end-users, these solutions can still be improved while conserving the overall representation and quality of the assembly. The de novo RNA-Seq Assembly Pipeline (DRAP) is an ease to use software package to produce compact and corrected transcript set. DRAP is free, open-source and available at http://www.sigenae.org/drap .

scholarly journals TransRate: reference-free quality assessment of de novo transcriptome assemblies

2016 ◽  
Vol 26 (8) ◽  
pp. 1134-1144 ◽  
Author(s):  
Richard Smith-Unna ◽  
Chris Boursnell ◽  
Rob Patro ◽  
Julian M. Hibberd ◽  
Steven Kelly
Keyword(s):  
Quality Assessment ◽  
De Novo ◽  
De Novo Transcriptome

scholarly journals Compacting and correcting Trinity and Oases RNA-Seq de novo assemblies

2016 ◽  
Author(s):  
Cédric Cabau ◽  
Frédéric Escudié ◽  
Anis Djari ◽  
Yann Guiguen ◽  
Julien Bobe ◽  
...  
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Error Rates ◽  
Rna Seq ◽  
De Novo Transcriptome ◽  
Software Packages ◽  
Redundancy Reduction ◽  
Assembly Pipeline ◽  
Free Open Source

Background De novo transcriptome assembly of short reads is now a common step in expression analysis of organisms lacking a reference genome sequence. Several software packages are available to perform this task. Even if their results are of good quality it is still possible to improve them in several ways including redundancy reduction or error correction. Trinity and Oases are two commonly used de novo transcriptome assemblers. The contig sets they produce are of good quality. Still, their compaction (number of contigs needed to represent the transcriptome) and their quality (chimera and nucleotide error rates) can be improved. Results We built a de novo RNA-Seq Assembly Pipeline (DRAP) which wraps these two assemblers (Trinity and Oases) in order to improve their results regarding the above-mentioned criteria. DRAP reduces from 1,3 to 15 fold the number of resulting contigs of the assemblies depending on the read set and the assembler used. This article presents seven assembly comparisons showing in some cases drastic improvements when using DRAP. DRAP does not significantly impair assembly quality metrics such are read realignment rate or protein reconstruction counts. Conclusion Transcriptome assembly is a challenging computational task even if good solutions are already available to end-users, these solutions can still be improved while conserving the overall representation and quality of the assembly. The de novo RNA-Seq Assembly Pipeline (DRAP) is an ease to use software package to produce compact and corrected transcript set. DRAP is free, open-source and available at http://www.sigenae.org/drap .

scholarly journals The Bellerophon pipeline, improving de novo transcriptomes and removing chimeras

2018 ◽  
Author(s):  
Jesse Kerkvliet ◽  
Arthur de Fouchier ◽  
Michiel van Wijk ◽  
Astrid T. Groot
Keyword(s):  
Quality Control ◽  
Quality Assessment ◽  
Reference Genome ◽  
Assessment Tool ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Rna Seq ◽  
Quality Assessment Tool ◽  
Chimeric Sequences

AbstractTranscriptome quality control is an important step in RNA-seq experiments. However, the quality of de novo assembled transcriptomes is difficult to assess, due to the lack of reference genome to compare the assembly to. We developed a method to assess and improve the quality of de novo assembled transcriptomes by focusing on the removal of chimeric sequences. These chimeric sequences can be the result of faulty assembled contigs, merging two transcripts into one. The developed method is incorporated into a pipeline, that we named Bellerophon, which is broadly applicable and easy to use. Bellerophon first uses the quality-assessment tool TransRate to indicate the quality, after which it uses a Transcripts Per Million (TPM) filter to remove lowly expressed contigs and CD-HIT-EST to remove highly identical contigs. To validate the quality of this method, we performed three benchmark experiments: 1) a computational creation of chimeras, 2) identification of chimeric contigs in a transcriptome assembly, 3) a simulated RNAseq experiment using a known reference transcriptome. Overall, the Bellerophon pipeline was able to remove between 40 to 91.9% of the chimeras in transcriptome assemblies and removed more chimeric than non-chimeric contigs. Thus, the Bellerophon sequence of filtration steps is a broadly applicable solution to improve transcriptome assemblies.

Examining De Novo Transcriptome Assemblies via a Quality Assessment Pipeline

2018 ◽  
Vol 15 (2) ◽  
pp. 494-505 ◽  
Author(s):  
Noushin Ghaffari ◽  
Osama A. Arshad ◽  
Hyundoo Jeong ◽  
John Thiltges ◽  
Michael F. Criscitiello ◽  
...  
Keyword(s):  
Quality Assessment ◽  
De Novo ◽  
De Novo Transcriptome

scholarly journals Comprehensive transcriptome analysis of grafting onto Artemisia scoparia  W. to affect the aphid resistance of chrysanthemum (Chrysanthemum morifolium T. )

2019 ◽  
Author(s):  
Xue-ying Zhang(Former Corresponding Author) ◽  
Xian-zhi Sun(New Corresponding Author) ◽  
Sheng Zhang ◽  
Fang-fang Liu ◽  
Jing-hui Yang ◽  
...  
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Chrysanthemum Morifolium ◽  
De Novo Transcriptome Assembly ◽  
Rna Seq ◽  
De Novo Transcriptome ◽  
Biotic And Abiotic Stresses ◽  
Yield And Quality ◽  
Artemisia Scoparia

Abstract Aphid ( Macrosiphoniella sanbourni ) stress drastically influences the yield and quality of chrysanthemum, and grafting has been widely used to improve tolerance to biotic and abiotic stresses. However, the effect of grafting on the resistance of chrysanthemum to aphids remains unclear. Therefore, we used the RNA-Seq platform to perform a de novo transcriptome assembly to analyze the self - rooted grafted chrysanthemum ( Chrysanthemum morifolium 'Hangbaiju') and the grafted Artermisia-chrysanthemum ( grafted onto Artemisia scoparia ) transcription response to aphid stress.

scholarly journals Impact of sequencing data filtering on the quality of de novo transcriptome assembly

2021 ◽  
Vol 270 ◽  
pp. 01014
Author(s):  
Yakov Meger ◽  
Ekaterina Vodiasova ◽  
Anastasiya Lantushenko
Keyword(s):  
Input Data ◽  
De Novo ◽  
Transcriptome Assembly ◽  
De Novo Transcriptome Assembly ◽  
Data Filtering ◽  
Sequencing Data ◽  
De Novo Transcriptome ◽  
Filtering Algorithm ◽  
Required Quality

There are many assemblers with different algorithms that are used for de novo transcriptome assembly. At the same time, the filtering stage, which is one of the key stages, also has several approaches and algorithms. However, to date, there are only few studies on the effect of the degree of filtration on the de novo transcriptome assembly, specially for single-end reads. In this paper, we analyzed transcriptomes obtained using two of the most common software (rnaSPADES and Trinity), and also applied various approaches to the stage of filtering reads. The key differences between the two assemblies were shown and the parameters that were sensitive to the degree of filtering and the length of the input reads were identified. An efficient two-stage filtering algorithm was also proposed, which allows one to preserve the volume of input data as much as possible with the required quality of all reads after filtering and trimming.

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