metagene: A class to manage metagene analysis.
In CharlesJB/metagene: A package to produce metagene plots

Description Usage Format Value Constructor Methods Examples

This class will allow to load, convert and normalize alignments and regions files/data. Once the data is ready, the user can then chose to produce metagene plots on the data (or a subset of the data).

metagene

A metagene experiment manager

metagene$new returns a metagene object which contains the normalized coverage values for every regions and for every BAM files.

: mg <- metagene$new(regions, bam_files, padding_size = 0, cores = SerialParam(), verbose = FALSE, force_seqlevels = FALSE, paired_end = FALSE, assay = 'chipseq'))
regions: Either a vector of BED, narrowPeak or broadPeak filenames, a GRanges object or a GRangesList object.
bam_files: A vector of BAM filenames. The BAM files must be indexed. i.e.: if a file is named file.bam, there must be a file named file.bam.bai or file.bai in the same directory.
padding_size: The regions will be extended on each side by the value of this parameter. The padding_size must be a non-negative integer. Default = 0.
cores: The number of cores available to parallelize the analysis. Either a positive integer or a BiocParallelParam. Default: SerialParam().
verbose: Print progression of the analysis. A logical constant. Default: FALSE.
force_seqlevels: If TRUE, Remove regions that are not found in bam file header. Default: FALSE. TRUE and FALSE respectively correspond to pruning.mode = "coarse" and "error" in ?seqinfo.
paired_end: If TRUE, metagene will deal with paired-ended data. If FALSE, single-ended data are expected. Default: FALSE
assay: 'chipseq' or 'rnaseq', the two available options. Default: 'chipseq'

metagene$new returns a metagene object that contains the coverages for every BAM files in the regions from the regions param.

: mg$plot(region_names = NULL, design_names = NULL, title = NULL, x_label = NULL)
region_names: The names of the regions to extract. If NULL, all the regions are returned. Default: NULL.
design_names: The names of the experiments to extract. If a design was added to the metagene object, design_names correspond to the column names in the design, otherwise design_names corresponds to the BAM name or the BAM filename. If NULL, all the experiments are returned. Default: NULL.
title: A title to add to the graph. If NULL, will be automatically created. Default: NULL
x_label: X-axis label to add to the metagene plot. If NULL, metagene will use generic label. Default: NULL.

: mg$produce_table(design, bin_count, noise_removal, normalization, flip_regions, bin_size = NULL
design: A data.frame that describe to experiment to plot. see plot function for more details. NA can be used keep previous design value. Default: NA.
bin_count: The number of bin to create. NA can be used to keep previous bin_count value. A bin_count value of 100 will be used if no value is specified. Default: NA.
noise_removal: The algorithm to use to remove control(s). Possible values are NA, NULL or "NCIS". By default, value is NULL. Use NA keep previous noise_removal value (i.e. if produce_table was called before). See Liand and Keles 2012 for the NCIS algorithm.
normalization: The algorithm to use to normalize samples. Possible default, value is NULL and no normalization will be performed. Use NA keep previous normalization value (i.e. if produce_table was called before).
flip_regions: Should regions on negative strand be flip_regions? Default: FALSE.
bin_size: Deprecated.

: mg$produce_data_frame(alpha = 0.05, sample_count = 1000, avoid_gaps = FALSE, gaps_threshold = 0)
alpha: The range of the estimation to be shown with the ribbon. 1 - alpha / 2 and alpha / 2 will be used. Default: 0.05.
sample_count: The number of draw to do in the bootstrap calculation. Default: 1000.
avoid_gaps: Provide the possibility to remove values = 0 and refit the data_frame for this suppression. Default : FALSE.
gaps_threshold: It works with avoid_gaps argument. It lets to remove values <= at gaps_threshold. Default : 0.

: mg$get_params()

: mg$get_design()

: mg$get_regions(region_names = NULL)
region_names: The names of the regions to extract. If NULL, all the regions are returned. Default: NULL.

: mg$get_table = function()

: mg$get_matrices = function()

: mg$get_data_frame(region_names = NULL, design_names = NULL)
region_names: The names of the regions to extract. If NULL, all the regions are returned. Default: NULL.
design_names: The names of the experiments to extract. If a design was added to the metagene object, design_names correspond to the column names in the design, otherwise design_names corresponds to the BAM name or the BAM filename. If NULL, all the experiments are returned. Default: NULL.

: get_plot = function()

: get_raw_coverages = function(filenames)
filenames: The name of the file to extract raw coverages. Can be the filename with the extension of the name of the bam file (if a named bam files was used during the creation of the metagene object). If NULL, returns the coverage of every bam files. Default: NULL.

: get_normalized_coverages = function(filenames)
filenames: The name of the file to extract normalized coverages (in RPM). Can be the filename with the extension of the name of the bam file (if a named bam files was used during the creation of the metagene object). If NULL, returns the coverage every bam files. Default: NULL.

: mg$export(bam_file, region, file)
bam_file: The name of the bam file to export.
region: The name of the region to export.
file: The name of the ouput file.

: mg$add_design(design = NULL, check_bam_files = FALSE)
design: A data.frame that describe to experiment to plot. See plot function for more details. NA can be used keep previous design value. Default: NA.
check_bam_files: Force check that all the bam files from the first columns of the design are present in current metagene object. Default: FALSE

: mg$unflip_regions()

: mg$flip_regions()

: mg$unflip_regions()

region <- get_demo_regions()[1]
bam_file <- get_demo_bam_files()[1]
mg <- metagene$new(regions = region, bam_files = bam_file)
## Not run: 
   df <- metagene$plot()

## End(Not run)