https://socictopen.socict.org/files/original/9e3dbd5b6d3a0c0e6199d21ac76dbbd6.pdf 64561dd1203805c71ab8db2cca28c22d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A consensus approach to vertebrate de novo transcriptome assembly from RNA-seq data: Assembly of the duck (Anas platyrhynchos) transcriptome. Creator An entity primarily responsible for making the resource Joanna eMoreton, Stephen P Dunham, Richard D. Emes Description An account of the resource For vertebrate organisms where a reference genome is not available, de novo transcriptome assembly enables a cost effective insight into the identification of tissue specific or differentially expressed genes and variation of the coding part of the genome. However, since there are a number of different tools and parameters that can be used to reconstruct transcripts, it is difficult to determine an optimal method. Here we suggest a pipeline based on (1) assessing the performance of three different assembly tools (2) using both single and multiple k-mer approaches (3) examining the influence of the number of reads used in the assembly (4) merging assemblies from different tools. We use an example dataset from the vertebrate Anas platyrhynchos domestica (Pekin duck). We find that taking a subset of data enables a robust assembly to be produced by multiple methods without the need for very high memory capacity. The use of reads mapped back to transcripts (RMBT) and CEGMA (Core Eukaryotic Genes Mapping Approach) provides useful metrics to determine the completeness of assembly obtained. For this dataset the use of multiple k-mers in the assembly generated a more complete assembly as measured by greater number of RMBT and CEGMA score. Merged single k-mer assemblies are generally smaller but consist of longer transcripts, suggesting an assembly consisting of fewer fragmented transcripts. We suggest that the use of a subset of reads during assembly allows the relatively rapid investigation of assembly characteristics and can guide the user to the most appropriate transcriptome for particular downstream use. Transcriptomes generated by the compared assembly methods and the final merged assembly are freely available for download at http://dx.doi.org/10.6084/m9.figshare.1032613. Date A point or period of time associated with an event in the lifecycle of the resource 2014 Subject The topic of the resource RNA-Seq, assembly, high-throughput sequencing, Illumina, de novo transcriptome Identifier An unambiguous reference to the resource within a given context DOI: 10.3389/fgene.2014.00190 Source A related resource from which the described resource is derived Frontiers in Genetics Publisher An entity responsible for making the resource available Frontiers Media S.A. Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Genetics Language A language of the resource EN