Get CN Segments.
get_cn_segments.RdRetrieve all copy number segments from the GAMBL outputs
Usage
get_cn_segments(
these_samples_metadata,
projection = "grch37",
flavour = "combined",
this_seq_type,
fill_missing_with = "nothing",
verbose = FALSE
)Arguments
- these_samples_metadata
User must provide a metadata table to restrict the data to the samples in your table. The metadata also ensures the proper handling of duplicate sample_id across seq_types and ensures the seq_type in the metadata faithfully represents the seq_type of the data
- projection
Desired genome coordinate system for returned CN segments. Default is "grch37".
- flavour
Specify what pipeline or source of data to use. Available options are "combined" or "battenberg". Battenberg outputs are incomplete.
- this_seq_type
Deprecated.
- fill_missing_with
Specify how to fill values in dummy segments that were created to satisfy GISTIC. The default is "nothing", which causes these to be dropped so empty regions can be handled in subsequent processing steps. For creating a GISTIC input, you would typically want to set this to "avg_ploidy". This is taken care of for you by GAMBLR.utils::prepare_gistic_inputs
- verbose
Set to TRUE for a chattier experience
Details
This merely loads and returns all the seg_data available for a projection (genome build) and can assign a single value to dummy segments if they are present/identified in the source file
Examples
# Example for just exome/capture samples:
# Get metadata for just a few capture samples
capture_metadata <- suppressMessages(get_gambl_metadata()) %>%
dplyr::filter(seq_type == "capture") %>%
head()
# Load the copy number segments for capture samples using hg38 projection
capture_segments_hg38 <- get_cn_segments(
these_samples_metadata = capture_metadata,
projection = "hg38"
)
#> dummy segments are not annotated in the inputs
#> fill_missing_with parameter will be ignored
print(capture_segments_hg38)
#> SEG Data Object
#> Genome Build: hg38
#> Showing first 10 rows:
#> ID chrom start end LOH_flag log.ratio seg_seq_type
#> 1 00-22011_tumorB chr1 10001 69372 NA 0.0000 capture
#> 2 00-22011_tumorB chr1 69373 10335564 NA 1.0000 capture
#> 3 00-22011_tumorB chr1 10335564 12723042 NA 0.0000 capture
#> 4 00-22011_tumorB chr1 12723043 13184564 NA 0.0000 capture
#> 5 00-22011_tumorB chr1 13184565 33302847 NA 0.0000 capture
#> 6 00-22011_tumorB chr1 33302847 33309697 NA 2.5453 capture
#> 7 00-22011_tumorB chr1 33309697 40850005 NA 0.0000 capture
#> 8 00-22011_tumorB chr1 40850005 40922631 NA 2.8912 capture
#> 9 00-22011_tumorB chr1 40922631 47396477 NA 0.0000 capture
#> 10 00-22011_tumorB chr1 47396477 47439416 NA 2.0000 capture
#> CN
#> 1 2.00000
#> 2 4.00000
#> 3 2.00000
#> 4 2.00000
#> 5 2.00000
#> 6 11.67459
#> 7 2.00000
#> 8 14.83775
#> 9 2.00000
#> 10 8.00000
genome_metadata <- suppressMessages(get_gambl_metadata()) %>%
dplyr::filter(seq_type == "genome") %>%
head()
# Create a metadata table with a mix of seq_types
mixed_seq_type_meta <- dplyr::bind_rows(capture_metadata, genome_metadata)
## We can load the copy number segments for all samples across seq_types
capture_segments_default <- get_cn_segments(
these_samples_metadata = mixed_seq_type_meta
)
#> dummy segments are not annotated in the inputs
#> fill_missing_with parameter will be ignored
dplyr::group_by(capture_segments_default, ID) %>%
dplyr::summarize(n = dplyr::n())
#> # A tibble: 12 × 2
#> ID n
#> <chr> <int>
#> 1 00-12637_CLC02086 116
#> 2 00-14595_tumorB 144
#> 3 00-14595_tumorC 166
#> 4 00-14595_tumorD 142
#> 5 00-22011_tumorB 598
#> 6 FL1011T1 22548
#> 7 FL1011T2 134
#> 8 PA003 225
#> 9 PA007 297
#> 10 PA065 3903
#> 11 PA081 200
#> 12 PTCL002_tumour 195
# Note the default projection is "grch37"
print(capture_segments_default)
#> SEG Data Object
#> Genome Build: grch37
#> Showing first 10 rows:
#> ID chrom start end LOH_flag log.ratio seg_seq_type
#> 1 00-22011_tumorB 1 10001 69372 NA 0.0000 capture
#> 2 00-22011_tumorB 1 69373 10395622 NA 1.0000 capture
#> 3 00-22011_tumorB 1 10395622 12783034 NA 0.0000 capture
#> 4 00-22011_tumorB 1 12783034 13292951 NA -2.0000 capture
#> 5 00-22011_tumorB 1 13292951 33768448 NA 0.0000 capture
#> 6 00-22011_tumorB 1 33768448 33775298 NA 2.5453 capture
#> 7 00-22011_tumorB 1 33775298 41315677 NA 0.0000 capture
#> 8 00-22011_tumorB 1 41315677 41388303 NA 2.8912 capture
#> 9 00-22011_tumorB 1 41388303 47862149 NA 0.0000 capture
#> 10 00-22011_tumorB 1 47862149 47905088 NA 2.0000 capture
#> CN
#> 1 2.00000
#> 2 4.00000
#> 3 2.00000
#> 4 0.50000
#> 5 2.00000
#> 6 11.67459
#> 7 2.00000
#> 8 14.83775
#> 9 2.00000
#> 10 8.00000