ARSyNseq
(Package: NOISeq) :
ASCA Removal of Systematic Noise on Seq data
ARSyNseq filters the noise associated to identified or not identified batch effects considering the experimental design and applying Principal Component Analysis (PCA) to the ANOVA parameters and residuals.
Biodetection class generated from dat() function with type="biodetection". This object contains the percentage of each biological class (e.g. biotype) in the genome (i.e. in the whole set of features provided), the corresponding percentage detected by the sample and the percentage of the biotype within the sample.
CD class generated from dat() function with type="cd". This object contains the distributions of log-fold changes (M values) between each of the samples and a reference sample as well as confidence intervals for the median of these distributions that are used to detect a potential RNA composition bias in the data.
CountsBio class generated from dat() function with type="countsbio". This object contains the count distribution for each biological group and also the percentage of features with counts per million higher than 0, 1, 2, 5 or 10, per each sample independently and in at least one of the samples (total).
Function to generate plots showing different aspects of differential expression results. Expression plot is to compare the expression values in each condition for all features. Differentially expressed features can be highlighted. Manhattan plot is to compare the expression values in each condition across all the chromosome positions. Differentially expressed features can also be highlighted. MD plot shows the values for (M,D) statistics. Differentially expressed features can also be highlighted. Distribution plot displays the percentage of differentially expressed features per chromosome and biotype (if this information is provided by the user).
GCbias class generated from dat() function with type="GCbias". This object contains the trimmed mean of expression for each GC content bin of 200 features per sample or condition and also per biotype (if available). It also includes the corresponding spline regression model fitted to explain the relationship between length and expression.
lengthbias class generated from dat() function with type="lengthbias". This object contains the trimmed mean of expression for each length bin of 200 features per sample or condition and also per biotype (if available). It also includes the corresponding spline regression models fitted to explain the relationship between length and expression.
providing 
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