Noise Quantification in High Throughput Sequencing Output


[Up] [Top]

Documentation for package ‘noisyr’ version 1.0.0

Help Pages

calculate_expression_profile Calculate the expression profile of a gene
calculate_expression_similarity_counts Calcualate the expression levels and expression levels similarity matrices using the count matrix
calculate_expression_similarity_transcript Calcualte the distance matrices using the BAM files
calculate_first_minimum_density Function to find the first local minimum of the density of a vector
calculate_noise_threshold Function to calculate the noise threshold for a given expression matrix and parameters
calculate_noise_threshold_method_statistics Function to tabulate statistics for different methods of calculating the noise threshold
cast_gtf_to_genes Function to extract exon names and positions from a gtf file
cast_matrix_to_numeric Cast a matrix of any type to numeric
filter_genes_transcript Function to filter the gene table for the transcript approach
get_methods_calculate_noise_threshold Show the methods for calculating a noise threshold
get_methods_correlation_distance Show the methods for calculating correlation or distance
noisyr Run the noisyR pipeline
noisyr_counts Run the noisyR pipeline for the count matrix approach
noisyr_transcript Run the noisyR pipeline for the transcript approach
optimise_window_length Optimise the elements per window for the count matrix approach
plot_expression_similarity Plot the similarity against expression levels
remove_noise_from_bams Function to remove the noisy reads from the BAM files
remove_noise_from_matrix Function to remove the noisy reads from the expression matrix