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As several assembled transcripts were obtained from each sample, we used Cuffmerge to assemble them into a comprehensive set of transcripts for further downstream differential expression analysis.
The aim of this study was not simply to provide a comprehensive set of transcripts from these species but to pave the way, using SSR and COS markers, for further investigations including population genetics, QTL mapping, and marker-assisted selection.
The transcripts were constructed and quantified the expression FPKM values of transcripts in each sample by Cufflinks (v2.1.0) and merged into a final comprehensive set of transcripts using Cuffmerge.
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A Representative Transcript and Protein Sets (RTPS) pipeline was previously designed to identify the nonredundant and comprehensive set of mouse transcripts based on clustering of a large mouse full-length cDNA set (FANTOM2).
First, we retrieved a comprehensive set of 119,959 transcripts from the Transcriptome Shotgun Assembly (TSA) database, which was generated from de novo assemblies from RNA-seq datasets of seven tissues in the updated genome annotation of A. mellifera [ 39].
The assembled sequencing output consisted of 26,037 sequences, and large cDNAs from this assembly (>500 bp) were then joined to a previously available sequence dataset [ 6], to form a comprehensive set of representative transcripts.
Therefore, we created a set of putative transcribed ranges using a separate comprehensive set of wheat transcript data.
The two main objectives of this study were to develop a comprehensive set of reference transcript sequences for genome-scale gene discovery and expression studies in catfish; and to obtain a large number of full-length transcripts for whole genome annotation, duplicate gene identification, and facilitating detection of false SNPs derived from PSVs/MSVs.
The use of HTTS in conjunction with microarrays allowed us to detect a more comprehensive set of soybean gene transcripts.
To obtain information about the portion of a genome that is transcribed as RNAs and then translated into proteins, a comprehensive set of full-length transcripts is needed [ 4].
Using the transcripts annotated by UCSC Known Genes (see Methods for details), we determined that E2F1 is >55x more likely (lower bound of odds ratio (OR) 95% confidence interval) to bind a CGI promoter than a non-CGI promoter (Fisher's exact test; P <10-15 <10-15larly for the comprehensimilarlyoforencode v19 thenscomprehensive2; P <10-15).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com