add_frag_info           decode fragment identifiers for spike-in
                        standards
bam_to_bins             create a tiled representation of a genome from
                        the BAM/CRAM file
bin_pmol                Binned estimation of picomoles of DNA present
                        in cfMeDIP assays
convertPairedGRtoGR     Convert Pairs to GRanges
covg_to_df              reshape 'scan_spiked_bam' results into
                        data.frames for model_glm_pmol
dedup                   spike-in counts for two samples, as a wide
                        data.frame
find_spike_contigs      find spike-in seqlevels in an object 'x', where
                        !is.null(seqinfo(x))
genbank_mito            various mitochondrial genomes sometimes used as
                        endogenous spike-ins
generate_spike_fasta    for CRAM files, a FASTA reference is required
                        to decode; this builds that
genomic_res             A Granges object with genomic coverage from
                        chr21q22, binned every 300bp for the genomic
                        contigs then averaged across the bin. (In other
                        words, the default output of
                        scan_genomic_contigs or scan_genomic_bedpe,
                        restricted to a small enough set of genomic
                        regions to be practical for examples.) This
                        represents what most users will want to
                        generate from their own genomic BAMs or BEDPEs,
                        and is used repeatedly in downstream examples
                        throughout the package.
get_base_name           refactored out of rename_spikes and
                        rename_spike_seqlevels
get_binned_coverage     tabulate read coverage in predefined bins
get_merged_gr           get a GRanges of (by default, standard)
                        chromosomes from seqinfo
get_spike_depth         get the (max, median, or mean) coverage for
                        spike-in contigs from a BAM/CRAM
get_spiked_coverage     tabulate coverage across assembly and spike
                        contig subset in natural order
kmax                    simple contig kmer comparisons
kmers                   oligonucleotideFrequency, but less letters and
                        more convenient.
methylation_specificity
                        compute methylation specificity for spike-in
                        standards
model_bam_standards     Build a Bayesian additive model from spike-ins
                        to correct bias in *-seq
model_glm_pmol          Build a generalized linear model from spike-ins
                        to correct bias in cfMeDIP
parse_spike_UMI         parse out the forward and reverse UMIs and
                        contig for a BED/BAM
phage                   lambda and phiX phage sequences, sometimes used
                        as spike-ins
predict_pmol            predict picomoles of DNA from a fit and read
                        counts (coverage)
process_spikes          QC, QA, and processing for a new spike database
read_bedpe              read a BEDPE file into Pairs of GRanges (as if
                        a GAlignmentPairs or similar)
rename_spike_seqlevels
                        for spike-in contigs in GRanges, match to
                        standardized spike seqlevels
rename_spikes           for BAM/CRAM files with renamed contigs, we
                        need to rename 'spike' rows
scan_genomic_bedpe      Scan genomic BEDPE
scan_genomic_contigs    scan genomic contigs in a BAM/CRAM file
scan_methylation_specificity
                        tabulate methylation specificity for multiple
                        spike-in BAM/CRAM files
scan_spike_bedpe        Scan spikes BEDPE
scan_spike_contigs      pretty much what it says: scan spike contigs
                        from a BAM or CRAM file
scan_spike_counts       run spike_counts on BAM/CRAM files and shape
                        the results for model_glm_pmol
scan_spiked_bam         pretty much what it says: scan standard chroms
                        + spike contigs from a BAM
seqinfo_from_header     create seqinfo (and thus a standard chromosome
                        filter) from a BAM header
spike                   spike-in contig properties for Sam's cfMeDIP
                        spikes
spike_bland_altman_plot
                        Bland-Altman plot for cfMeDIP spike standards
spike_counts            use the index of a spiked BAM/CRAM file for
                        spike contig coverage
spike_cram_counts       spike-in counts, as a long data.frame
spike_read_counts       spike-in counts, as a long data.frame
spike_res               A Granges object with spike-in sequence
                        coverage, and summarized for each spike contig
                        as (the default) 'max' coverage. (In other
                        words, the default output of scan_spike_contigs
                        or scan_spike_bedpe) This represents what most
                        users will want to generate from their own
                        spike-in BAMs or BEDPEs, and is used repeatedly
                        in downstream examples throughout the package.
spiky-methods           A handful of methods that I've always felt were
                        missing
ssb_res                 scan_spiked_bam results from a merged cfMeDIP
                        CRAM file (chr22 and spikes)
testGR                  a test GRanges with UMI'ed genomic sequences
                        used as controls
tile_bins               Tile the assembly-based contigs of a merged
                        assembly/spike GRanges.
