PAMES has been completely rewritten to work with our new framework MiMeSis
Major changes:
- all functions now return a data.frame instead of a vector: according to our experience, data.frames integrate better with pipelines;
- get_AUC
replaces compute_AUC
and takes as input a matrix of beta-values as originally produced by Illumina Beadchips (instead of rounded percentages);
- find_informative_sites
and find_informative_regions
replace select_informative_sites
and select_informative_regions
, respectively, and integrate the new control_constraints
parameter;
- get_purity
replace compute_purity
and takes as input a data.frame (generated by find_informative_sites
/find_informative_regions
).
median_of_regions
: reduce_region
method
parameter to reduce_to_regions
: allow choice between "median" (default) or meanselect_informative_regions_ext
with flag return_info=TRUE
platform
to ref_table
compute_AUC
compute_AUC
now returns a vector with the names of the CpG probes.platform
parameter to compute_purity
to address issue #7)reduce_to_regions
(see issue #6)compute_AUC
percentiles
parameter for a more flexible selection of sitesselect_informative_sites
is_too_close
cluster_reduction
method
to select_informative_sites
and select_informative_regions
to select even, top, hyper or hypo methylated sites.PAMES have been rewritten to make the code simpler and the analysis run faster.
Thanks to GMFranceschini for suggesting to
use GenomicRanges
.
Removed function:
compute_islands_indexes.R
reduce_to_islands.R
-> reduce_to_regions.R
cpg_islands_df
-> cpg_islands
bs_toy_indexes
compute_AUC
with argument ncores
.cpg_islands
has been renamed as cpg_islands_df
bs_tumor_toy_data
and bs_control_toy_data
has been merged into bs_toy_matrix
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