DiffBind-globals: Constant variables used in DiffBind package
In DiffBind: Differential Binding Analysis of ChIP-Seq Peak Data

Description Usage Arguments Note Author(s)

Constant variables used in DiffBind package

DBA_ID
DBA_FACTOR
DBA_TISSUE
DBA_CONDITION
DBA_TREATMENT
DBA_REPLICATE
DBA_CALLER
DBA_CONSENSUS
DBA_CONTROL
DBA_READS
DBA_ALL_ATTRIBUTES

DBA_INTERVALS
DBA_FRIP

DBA_GROUP

DBA_OLAP_PEAKS
DBA_OLAP_ALL
DBA_OLAP_RATE

DBA_COR
DBA_OLAP
DBA_INALL

DBA_SCORE_READS
DBA_SCORE_NORMALIZED
DBA_SCORE_CONTROL_READS
DBA_SCORE_READS_MINUS
DBA_SCORE_READS_FULL
DBA_SCORE_READS_MINUS_FULL
DBA_SCORE_READS_EFFECTIVE
DBA_SCORE_READS_MINUS_EFFECTIVE
DBA_SCORE_READS_FOLD
DBA_SCORE_RPKM
DBA_SCORE_RPKM_FOLD
DBA_SCORE_RPKM_MINUS
DBA_SCORE_TMM_READS_FULL
DBA_SCORE_TMM_READS_EFFECTIVE
DBA_SCORE_TMM_MINUS_FULL
DBA_SCORE_TMM_MINUS_EFFECTIVE
DBA_SCORE_TMM_READS_FULL_CPM
DBA_SCORE_TMM_READS_EFFECTIVE_CPM
DBA_SCORE_TMM_MINUS_FULL_CPM
DBA_SCORE_TMM_MINUS_EFFECTIVE_CPM
DBA_SCORE_SUMMIT
DBA_SCORE_SUMMIT_ADJ
DBA_SCORE_SUMMIT_POS

DBA_READS_DEFAULT
DBA_READS_BAM
DBA_READS_BED

DBA_EDGER
DBA_DESEQ2
DBA_EDGER_BLOCK
DBA_DESEQ2_BLOCK
DBA_EDGER_GLM
DBA_ALL_METHODS
DBA_ALL_BLOCK
DBA_ALL_METHODS_BLOCK

DBA_DATA_FRAME
DBA_DATA_GRANGES
DBA_DATA_RANGEDDATA
DBA_DATA_SUMMARIZED_EXPERIMENT
DBA_DATA_DBAOBJECT

DBA_BLACKLIST_CE10
DBA_BLACKLIST_CE11
DBA_BLACKLIST_DM3
DBA_BLACKLIST_DM6
DBA_BLACKLIST_GRCH37
DBA_BLACKLIST_GRCH38
DBA_BLACKLIST_HG19
DBA_BLACKLIST_HG38
DBA_BLACKLIST_MM9
DBA_BLACKLIST_MM10
DBA_BLACKLIST
DBA_GREYLIST
DBA_BLACKLISTED_PEAKS

DBA_LIBSIZE_DEFAULT
DBA_LIBSIZE_FULL
DBA_LIBSIZE_PEAKREADS
DBA_LIBSIZE_BACKGROUND
DBA_LIBSIZE_USER
DBA_NORM_DEFAULT
DBA_NORM_NATIVE
DBA_NORM_LIB
DBA_NORM_TMM
DBA_NORM_RLE
DBA_NORM_SPIKEIN
DBA_NORM_USER
DBA_NORM_OFFSETS
DBA_NORM_OFFSETS_ADJUST
DBA_OFFSETS_LOESS
DBA_OFFSETS_USER

`DBA_ID`	DBA peakset metadata: Peakset ID
`DBA_FACTOR`	DBA peakset metadata: Factor
`DBA_TISSUE`	DBA peakset metadata: Tissue
`DBA_CONDITION`	DBA peakset metadata: Condition
`DBA_TREATMENT`	DBA peakset metadata: Treatment
`DBA_REPLICATE`	DBA peakset metadata: Replicate
`DBA_CALLER`	DBA peakset metadata: Peak Caller
`DBA_CONSENSUS`	DBA peakset metadata: Is this a consensus peakset?
`DBA_CONTROL`	DBA peakset metadata: ID of Control sample
`DBA_READS`	Number of reads counted in BAM file.
`DBA_ALL_ATTRIBUTES`	DBA peakset metadata: all attributes that can be used in certain plot labels (cf `dba.plotVenn`), equivalent to `c(DBA_ID, DBA_TISSUE, DBA_FACTOR, DBA_CONDITION,DBA_TREATMENT, DBA_REPLICATE, DBA_CALLER)`
`DBA_INTERVALS`	DBA peakset metadata: Number of intervals in peakset
`DBA_FRIP`	DBA peakset metadata: Fraction of Reads in Peaks (number of reads in intervals divided by total number of reads in library)
`DBA_GROUP`	DBA peakset metadata: color PCA plot using contras groups
`DBA_OLAP_PEAKS`	dba.overlap mode: return overlapping/unique peaksets
`DBA_OLAP_ALL`	dba.overlap mode: return report of correlations/overlaps for each pair of samples
`DBA_OLAP_RATE`	dba.overlap mode: return overlap rates
`DBA_COR`	When plotting a heatmap from an overlap record, use the correlation value.
`DBA_OLAP`	When plotting a heatmap from an overlap record, use the percentage overlap value.
`DBA_INALL`	When plotting a heatmap from an overlap record, use the number of peaks in common to both samples.
`DBA_SCORE_READS`	dba.count score is number of reads in ChIP
`DBA_SCORE_CONTROL_READS`	dba.count score is number of reads in Control
`DBA_SCORE_READS_FOLD`	dba.count score is number of reads in ChIP divided by number of reads in Control
`DBA_SCORE_READS_MINUS`	dba.count score is number of reads in ChIP minus number of reads in Control
`DBA_SCORE_READS_FULL`	dba.count score is normalized ChIP read counts, using Full Library size
`DBA_SCORE_READS_MINUS_FULL`	dba.count score is normalized ChIP read counts minus Control read counts, using Full Library size
`DBA_SCORE_READS_EFFECTIVE`	dba.count score is normalized ChIP read counts, using Effective Library size
`DBA_SCORE_READS_MINUS_EFFECTIVE`	dba.count score is normalized ChIP read counts minus Control read counts, using Effective Library size
`DBA_SCORE_NORMALIZED`	dba.count score is normalized reads
`DBA_SCORE_RPKM`	dba.count score is RPKM of ChIP
`DBA_SCORE_RPKM_FOLD`	dba.count score is RPKM of ChIP divided by RPKM of Control
`DBA_SCORE_RPKM_MINUS`	dba.count score is RPKM of ChIP minus RPKM of Control
`DBA_SCORE_TMM_READS_FULL`	dba.count score is TMM normalized (using edgeR), using ChIP read counts and Full Library size
`DBA_SCORE_TMM_READS_EFFECTIVE`	dba.count score is TMM normalized (using edgeR), using ChIP read counts and Effective Library size
`DBA_SCORE_TMM_MINUS_FULL`	dba.count score is TMM normalized (using edgeR), using ChIP read counts minus Control read counts and Full Library size
`DBA_SCORE_TMM_MINUS_EFFECTIVE`	dba.count score is TMM normalized (using edgeR), using ChIP read counts minus Control read counts and Effective Library size
`DBA_SCORE_TMM_READS_FULL_CPM`	dba.count score is TMM normalized (using edgeR), using ChIP read counts and Full Library size, reported in counts-per-million.
`DBA_SCORE_TMM_READS_EFFECTIVE_CPM`	dba.count score is TMM normalized (using edgeR), using ChIP read counts and Effective Library size, reported in counts-per-million.
`DBA_SCORE_TMM_MINUS_FULL_CPM`	dba.count score is TMM normalized (using edgeR), using ChIP read counts minus Control read counts and Full Library size, reported in counts-per-million.
`DBA_SCORE_TMM_MINUS_EFFECTIVE_CPM`	dba.count score is TMM normalized (using edgeR), using ChIP read counts minus Control read counts and Effective Library size, reported in counts-per-million.
`DBA_SCORE_SUMMIT`	dba.count score is summit height (highest pile-up).
`DBA_SCORE_SUMMIT_ADJ`	dba.count score is summit height (highest pile-up), adjusted for library size.
`DBA_SCORE_SUMMIT_POS`	dba.count score is summit location (position of highest pile-up).
`DBA_READS_DEFAULT`	When counting read files, use the file extension to determine the file type.
`DBA_READS_BAM`	When counting read files, assume the file type is BAM, regardless of the file extension.
`DBA_READS_BED`	When counting read files, assume the file type is BED (or zipped BED), regardless of the file extension.
`DBA_EDGER`	differential analysis method: edgeR (default: DBA_EDGER_GLM)
`DBA_DESEQ2`	differential analysis method: DESeq2 (using a single-factor GLM)
`DBA_EDGER_BLOCK`	differential analysis method: edgeR with blocking factors (GLM)
`DBA_DESEQ2_BLOCK`	differential analysis method: DESeq2 with blocking factors (GLM)
`DBA_EDGER_GLM`	differential analysis method: use GLM in edgeR for two-group comparisons
`DBA_ALL_METHODS`	use both analysis methods: `c(DBA_EDGER, DBA_DESEQ2)`
`DBA_ALL_BLOCK`	report on block results for both analysis methods: `c(DBA_EDGER_BLOCK, DBA_DESEQ2_BLOCK)`
`DBA_ALL_METHODS_BLOCK`	report on block results for all analysis methods, both blocked and unblocked: `c(DBA_ALL_METHODS, DBA_ALL_BLOCK)`
`DBA_DATA_GRANGES`	Use GRanges class for peaksets and reports. This is the default (DBA$config$DataType = DBA_DATA_GRANGES).
`DBA_DATA_RANGEDDATA`	Use RangedData class for peaksets and reports. Can be set as default (DBA$config$DataType = DBA_DATA_RANGEDDATA).
`DBA_DATA_FRAME`	Use data.frame class for peaksets and reports. Can be set as default (DBA$config$DataType = DBA_DATA_FRAME).
`DBA_DATA_SUMMARIZED_EXPERIMENT`	Return report as a `SummarizedExperiment`.
`DBA_DATA_DBAOBJECT`	Return a result-based DBA object from `dba.plotVenn`.
`DBA_BLACKLIST_HG19`	Homo sapiens 19 (chromosomes have "chr")
`DBA_BLACKLIST_HG38`	Homo sapiens 38 (chromosomes have "chr")
`DBA_BLACKLIST_GRCH37`	Homo sapiens 37 (chromosomes are numbers)
`DBA_BLACKLIST_GRCH38`	Homo sapiens 38 (chromosomes are numbers)
`DBA_BLACKLIST_MM9`	Mus musculus 9
`DBA_BLACKLIST_MM10`	Mus musculus 10
`DBA_BLACKLIST_CE10`	C. elegans 10
`DBA_BLACKLIST_CE11`	C. elegans 11
`DBA_BLACKLIST_DM3`	Drosophila melanogaster 3
`DBA_BLACKLIST_DM6`	Drosophila melanogaster 6
`DBA_BLACKLIST`	Retrieve blacklist
`DBA_GREYLIST`	Retrieve greylist
`DBA_BLACKLISTED_PEAKS`	Retrieve blacklisted peaks
`DBA_LIBSIZE_DEFAULT`	Default library size (`DBA_LIBSIZE_FULL` if no background, and `DBA_LIBSIZE_CHR` if background present)
`DBA_LIBSIZE_FULL`	Full library size (all reads in library)
`DBA_LIBSIZE_PEAKREADS`	Library size is Reads in Peaks
`DBA_LIBSIZE_BACKGROUND`	Library size is Reads in Background
`DBA_LIBSIZE_USER`	User supplied library sizes
`DBA_NORM_DEFAULT`	Default normalization method
`DBA_NORM_NATIVE`	"Native"" normalization method (TMM for `DBA_EDGER` and RLE for `DBA_DESEQ2`)
`DBA_NORM_LIB`	Normalize by library size only
`DBA_NORM_TMM`	Normalize using TMM method (`edgeR`)
`DBA_NORM_RLE`	Normalize using RLE method (`DESeq2`)
`DBA_NORM_SPIKEIN`	Normalize based on spike-ins
`DBA_NORM_USER`	User supplied normalization factors
`DBA_NORM_OFFSETS`	Use offsets instead of normalization factors
`DBA_NORM_OFFSETS_ADJUST`	Use offsets instead of normalization factors; adjust based on library size (DESeq)
`DBA_OFFSETS_LOESS`	Compute offsets using loess fit
`DBA_OFFSETS_USER`	Use offsetrs supplied by user