EasyCluster: a fast and efficient gene-oriented clustering tool for large-scale transcriptome data

Abstract

Background: ESTs and full-length cDNAs represent an invaluable source of evidence for inferring reliable gene structures and discovering potential alternative splicing events. In newly sequenced genomes, these tasks may not be practicable owing to the lack of appropriate training sets. However, when expression data are available, they can be used to build EST clusters related to specific genomic transcribed loci. Common strategies recently employed to this end are based on sequence similarity between transcripts and can lead, in specific conditions, to inconsistent and erroneous clustering. In order to improve the cluster building and facilitate all downstream annotation analyses, we developed a simple genome-based methodology to generate gene-oriented clusters of ESTs when a genomic sequence and a pool of related expressed sequences are provided. Our procedure has been implemented in the software EasyCluster and takes into account the spliced nature of ESTs after an ad hoc genomic mapping.

RCDA: A highly sensitive and specific alternatively spliced transcript assembly tool featuring upstream consecutive exon structures

“…We first compared the performance of the RCDA clustering module, RCluster, with that of EasyCluster [26] using a set of 21,599 transcripts from HSA21 (EasyCluster transcript input, see Materials and Methods Section 4.2.2). RCDA generated 379 clusters, while EasyCluster produced 389.…”

“…Other tools either were unavailable or unable to handle a dataset as large as the >23,000 transcripts in the HSA21 complete dataset (see discussion in [26]). The dataset used as ECgene input included the HSA21 transcripts from the GRC36/hg18 (3/2006), while that used with RCDA was from GRC37/hg19 (12/2010).…”

“…To compare the performance of the RCDA clustering module, RCluster, with that of the EasyCluster software [26], the complete HSA21q transcript dataset was further filtered according to the EasyCluster criteria to exclude intronless mRNAs. This second transcript set contained 21,599 sequences and is considered the EasyCluster transcript input.…”

“…In the assembly step, composite transcripts are assembled from cluster components, generating a set of “complete” mRNA sequences representing all splice variants for the gene. Some recently developed tools, such as EasyCluster, EST2uni, ESTpass and ESTExplorer [26–29], use only the first step, clustering transcripts by mapping to their genome coordinates.…”

An improved procedure for clustering and assembly of large transcriptome data

“…However, to fully exploit their biological potential, correct and reliable EST clusters are required. To fill this gap we developed the program EasyCluster that resulted the most accurate when compared to software at the state of the art in this field [2]. Recent technological advances are dramatically increasing the number of available transcriptome reads.…”