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(e) Size distribution of the annotated small RNA sequences (i.e. abundance/reads) according the annotation classes.
(d) Size distribution of the annotated small RNA clusters (i.e. distinct sequences) according the annotation classes.
(b) Relative abundance of the annotation classes of 21-nt small RNAs between O. barthii (Ob) and O. glaberrima (Og).
(c) Relative abundance of the annotation classes of 24-nt small RNAs between O. barthii (Ob) and O. glaberrima (Og).
Different annotation classes were defined to deal not only with chemical compounds but also with chemical reactions, chemical adjectives, enzymes and chemical prefixes.
In this study, we present AncestrySNPminer, the first web-based bioinformatics tool specifically designed to retrieve Ancestry Informative Markers (AIMs) from genomic data sets and link these informative markers to genes and ontological annotation classes.
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If there are n GO terms in the annotation database, a vector with length n and containing 1 or 0 is defined as the annotation class for a gene, 1 for annotated terms and 0 for unannotated terms.
Summary of sequence number (clusters and reads) in each annotation class (i.e. sequence databases) for O. barthii and O. glaberrima small RNA sequences based on BLAST-filtering.
The estimated value is the proportion of a given annotation class seen in the set of hit SNPs divided by the proportion seen in the set of non-hit SNPs.
Each subsequent column represents a different annotation class.
The second value (in brackets) is the regression coefficient for annotation class and trait.
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