SamPler – a novel method for selecting parameters for gene functional annotation routines

Abstract

Background As genome sequencing projects grow rapidly, the diversity of organisms with recently assembled genome sequences peaks at an unprecedented scale, thereby highlighting the need to make gene functional annotations fast and efficient. However, the (high) quality of such annotations must be guaranteed, as this is the first indicator of the genomic potential of every organism. Automatic procedures help accelerating the annotation process, though decreasing the confidence and reliability of the outcomes. Manually curating a genome-wide annotation of genes, enzymes and transporter proteins function is a highly time-consuming, tedious and impractical task, even for the most proficient curator. Hence, a semi-automated procedure, which balances the two approaches, will increase the reliability of the annotation, while speeding up the process. In fact, a prior analysis of the annotation algorithm may leverage its performance, by manipulating its parameters, hastening the downstream processing and the manual curation of assigning functions to genes encoding proteins. Results Here SamPler , a novel strategy to select parameters for gene functional annotation routines is presented. This semi-automated method is based on the manual curation of a randomly selected set of genes/proteins. Then, in a multi-dimensional array, this sample is used to assess the automatic annotations for all possible combinations of the algorithm’s parameters. These assessments allow creating an array of confusion matrices, for which several metrics are calculated (accuracy, precision and negative predictive value) and used to reach optimal values for the parameters. Conclusions The potential of this methodology is demonstrated with four genome functional annotations performed in merlin , an in-house user-friendly computational framework for genome-scale metabolic annotation and model reconstruction. For that, SamPler was implemented as a new plugin for the merlin tool. Electronic supplementary material The online version of this article (10.1186/s12859-019-3038-4) contains supplementary material, which is available to authorized users.

merlinv4.0: an updated platform for the reconstruction of high-quality genome-scale metabolic models

“…SamPler (11) is a semi-automatic method that relies on statistical metrics and the manual annotation of a genome sample to determine the optimal parameters. Such tool is available in the plugin form to configure merlin ’s annotation routine, semi-automatically.…”

Towards the Reconstruction of the Genome-Scale Metabolic Model of Lactobacillus acidophilus La-14

“…Enzymes annotation was performed using SamPler [37], a tool included in merlin that allows obtaining a semi-automatic annotation. Similarity searches were performed using Basic Local Alignment Search Tool (BLAST) [38] against Swiss-Prot and UniProtKB [39] in March 2018, setting an e-value threshold of 10 −30 .…”

Twelve quick steps for genome assembly and annotation in the classroom

“…However, it is highly recommended that beginners select automatic or semiautomatic annotation methods (including the workflow and guideline in Fig 1 ) because manual annotation can be very time- and labor-intensive and expensive. Note that while automatic procedures help accelerate the annotation process, they decrease the confidence and reliability of the outcomes because results from different servers and/or databases are often dissimilar [ 106 , 110 , 111 ]. Furthermore, automatic annotation algorithms, frequently based on orthologs from distantly related model organisms, cannot yet correctly identify all genes within a genome and manual annotation is often necessary to obtain accurate gene models and gene sets [ 106 , 110 , 111 ].…”

“…Note that while automatic procedures help accelerate the annotation process, they decrease the confidence and reliability of the outcomes because results from different servers and/or databases are often dissimilar [ 106 , 110 , 111 ]. Furthermore, automatic annotation algorithms, frequently based on orthologs from distantly related model organisms, cannot yet correctly identify all genes within a genome and manual annotation is often necessary to obtain accurate gene models and gene sets [ 106 , 110 , 111 ]. Thus, a scheme to obtain consensus annotations by integrating different results, a semiautomatic method, is in demand because this could balance automatic and manual approaches, which would increase the reliability of the annotation while accelerating the process [ 106 , 110 , 111 ].…”

“…Furthermore, automatic annotation algorithms, frequently based on orthologs from distantly related model organisms, cannot yet correctly identify all genes within a genome and manual annotation is often necessary to obtain accurate gene models and gene sets [ 106 , 110 , 111 ]. Thus, a scheme to obtain consensus annotations by integrating different results, a semiautomatic method, is in demand because this could balance automatic and manual approaches, which would increase the reliability of the annotation while accelerating the process [ 106 , 110 , 111 ]. In general, the identification of noncoding regions includes small and long sequences including repetitive and transposable elements ( Fig 1 and Table 3 ).…”