Evaluation of de novo transcriptome assemblies from RNA-Seq data

Li, Bo; Fillmore, Nathanael; Bai, Yongsheng; Collins, M. J.; Thomson, James A.; Stewart, Ron; Dewey, Colin N.

doi:10.1186/s13059-014-0553-5

Cited by 249 publications

(258 citation statements)

References 52 publications

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“…The higher N50 obtained after CAP3 confirms that merging different assemblies can produce higher N50 values (Kumar and Blaxter, 2010). Although N50 is not an exact parameter to measure the accuracy of contigs (Salzberg et al, 2012), it is one of the most popular reference-free measures (Li et al, 2014). The N50 value was in the range reported for other transcriptome de novo fish studies (Milano et al, 2011;Fan et al, 2014;Schunter et al, 2014).…”

Section: Resultssupporting

confidence: 57%

De novo Assembly, Characterization and Functional Annotation of Southern Hake (Merluccius australis) Transcriptome

Reyes¹,

Gold

González³

et al. 2016

Front. Mar. Sci.

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Southern hake (Merluccius australis) is an ecological and economically important demersal fish in Chile and Argentina. Notwithstanding, genetic resource for genetic or ecological studies on this species are scarce. Consequently, here we present transcriptome sequencing results (RNA-Seq) for spleen and liver tissues with the 454 FLX titanium platform. The de novo transcriptome assembly generated 10,314 unigenes, with an average length of 510 bp, N50 of 572 bp and 3171 annotated sequences. A specific Gadiform BLAST search, with focus on immune genes, showed 186 (56%) genes homologous to those of Atlantic cod. A total of 2302 microsatellites were detected in 1687 unigenes and 741 presented adequate flanking sequences for primer design. In total, these potential molecular markers and transcriptome characterization represent an important resource for genetic and ecological studies on southern hake.

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Section: Resultssupporting

confidence: 57%

De novo Assembly, Characterization and Functional Annotation of Southern Hake (Merluccius australis) Transcriptome

Reyes¹,

Gold

González³

et al. 2016

Front. Mar. Sci.

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“…Given that the ground truth is unknown for real data, DETONATE [24] or TransRate [25] can be used as a more reliable measure of de novo transcriptome assembly. To provide insight into how well the assembled candidates represent the data in an efficient way, we used DETONATE, which provides two types of assembly quality measure, namely RSEM-EVAL without and REF-EVAL with a reference transcriptome.…”

Section: Resultsmentioning

confidence: 99%

TraRECo: a greedy approach based de novo transcriptome assembler with read error correction using consensus matrix

et al. 2018

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BackgroundThe challenges when developing a good de novo transcriptome assembler include how to deal with read errors and sequence repeats. Almost all de novo assemblers utilize a de Bruijn graph, with which complexity grows linearly with data size while suffering from errors and repeats. Although one can correct the errors by inspecting the topological structure of the graph, this is not an easy task when there are too many branches. Two research directions are to improve either the graph reliability or the path search precision, and in this study, we focused on the former.ResultsWe present TraRECo, a greedy approach to de novo assembly employing error-aware graph construction. In the proposed approach, we built contigs by direct read alignment within a distance margin and performed a junction search to construct splicing graphs. While doing so, a contig of length l was represented by a 4 × l matrix (called a consensus matrix), in which each element was the base count of the aligned reads so far. A representative sequence was obtained by taking the majority in each column of the consensus matrix to be used for further read alignment. Once the splicing graphs had been obtained, we used IsoLasso to find paths with a noticeable read depth. The experiments using real and simulated reads show that the method provided considerable improvement in sensitivity and moderately better performance when comparing sensitivity and precision. This was achieved by the error-aware graph construction using the consensus matrix, with which the reads having errors were made usable for the graph construction (otherwise, they might have been eventually discarded). This improved the quality of the coverage depth information used in the subsequent path search step and finally the reliability of the graph.ConclusionsDe novo assembly is mainly used to explore undiscovered isoforms and must be able to represent as many reads as possible in an efficient way. In this sense, TraRECo provides us with a potential alternative for improving graph reliability even though the computational burden is much higher than the single k-mer in the de Bruijn graph approach.

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“…To verify the quality of the de novo transcriptome assembly we calculated the N50 [40], which gives information about the required contig length to cover 50% of the whole transcriptome. The N50 for all four replicates was in the range of 840 to 1400 nucleotides (Table S1).…”

Section: The De Novo Transcriptome Assembly Of Tomato Pollenmentioning

confidence: 99%