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GENOVA (development version)

  • Fixed a misplacement of na.rm in compartment_matrixplot() (#328)
  • The tornado_insulation() function now accepts a list of bed-like data.frames (#266).
  • Exposed the strand argument in ARA(), making it easier to do strand aware ARAs (#268)
  • Renamed cut.off to colour_lim and allow c(minimum, maximum) specification, rather than cut.off = maximum in hic_matrixplot() (#260).
  • Added a colour_bar legend option in *_matrixplot() family (#260).
  • The par() options now reset to original state after calling *_matrixplot() family of functions.
  • Fixed a bug with NAs in saddle() (#263).
  • Removed {bigwrig} as a dependency in favour of Bioconductor's {rtracklayer}.
  • Fixed a bug wherein the correct resolution couldn't be found in .mcool files due to scientific formatting of large numbers (#248, #249).
  • Fixed a bug in insulation_score() wherein formatting of sample names could throw errors (#246).
  • In load_contacts(), you can now set centromeres = FALSE to signal that the data doesn't contain centromeres (#241).
  • Fixed a balancing bug in .hic file loading (#225).

GENOVA v1.0 27-01-2021 (The Cartographer)

This version marks a large refactoring of the code base in an effort to increase consistency. However, it also breaks a lot of old code. It is the version that was used during submission of the GENOVA publication.

Data representation

  • A loaded Hi-C experiment is now dubbed a class object.
  • Added support for loading data from the cooler and juicer pipelines. Juicer import requires the {strawr} dependency and cooler import requires the {Rhdf5} dependency.
  • Centromere information is automatically estimated while loading the data by looking for the largest stretch of empty bins.
  • Added the sync_indices() function to harmonise data from various pipelines.

Analysis functions

  • Results from analysis functions have been dubbed class objects.
  • For quantification of analysis, the quantify() generic was added with methods for several objects.
  • Likewise, for visualising results, the visualise() generic was added with methods for several objects. Additionaly, some base R equivalents are available as methods to the plot() function.
  • New bundle() and unbundle() functions to more easily combine objects.
  • New ARA() functions for aggregating on-diagonal regions, convenient for stripe analysis.
  • New CSCAn() function for crosswise intersections of different sets of regions.
  • New anchors_*() family of functions for related analysis functions for repeated lookup analyses, to make these analyses more flexible.
  • New anchors_extendedloops() function to recapitulate the Haarhuis et al. (2017) strategy for loop anchors.
  • Standardised the APA(), ATA() and PESCAn() functions to use a common pattern for repeatedly looking up regions in the Hi-C map.
  • Speed-up of the repeated lookup functions by making better use of {data.table} joins.
  • The insulation_score() algorithm was sped up for larger data.
  • TAD calling via call_TAD_insulation() was sped up and closer to the description of the algorithm in Crane et al. (2015).
  • Compartment strength is no longer calculated in the deprecated visualise.compartmentStrength(), but in the quantify.saddle_discovery() method.
  • Refactored the RCP() function.

Plotting

  • Added colour palettes for sequential and divergent values (see ?GENOVA_colours). The default sequential palette can be changed using options("GENOVA.colour.palette" = {a character vector of colours}).
  • Wrappers for these colour palettes in {ggplot2} scales are in the scale_{colour/fill}_GENOVA() and scale_{colour/fill}_GENOVA_div() functions for sequential and divergent palettes respectively.
  • Added the pyramid() and pyramid_difference() function for plotting a Hi-C map at 45 degree angles.
  • The pyramid() plot can be annotated by the add_bed_graph(), add_bed_track(), add_ctcf_sites() functions.
  • The pyramid() plot can be annotated by compartment score, insulation score, directionality index, domainograms, virtual 4C or arbitrary ggplot2 layer using the as_track() function.
  • Most image()-based plotting now have the rasterise argument.
  • Replaced the visualise.{analysis}.ggplot() pattern functions by a visualise() generic with methods for objects.

Renamed

Generally, functions have been renamed to prevent dot.case functions implying S3 methods or lowerCamelCase implying S4 functions. Instead they now all use the snake_case.

Old name New name
hic.matrixplot() hic_matrixplot()
construct.experiment() load_contacts()
insulation.score() insulation_score()
insulation.domainogram() insulation_domainogram()
fastDI() direct_index()
chromosomeMatrix() chromsome_matrix()
compartment.score() compartment_score()
insulation.callTAD() call_TAD_insulation()
intra.inter.TAD.contacts() intra_inter_TAD()
select.subset() select_subset()
trans.compartment.plot() trans_matrixplot()

Deprecated

  • The badBin.find() function.
  • The badBin.plot() function.
  • The rescale() function in favour of scales::rescale().
  • The resize_mat() function.
  • The differential.TAD.dotplot/scatterplot() function in favour of the visualise.IIT_discovery() method.
  • The frequency.from.matrix() function.
  • The chrom.comparison.plot() function in favour of the visualise.chrommat_discovery() method.
  • The quantifyAPA() function in favour of the quantify.APA_discovery() method.
  • The cisTotal.perChrom() and cisTotal.scores() functions in favour of the cis_trans() function.
  • The insulation.plot.dual() and insulation.plot.single() functions in favour of the insulation_matrixplot().

Miscelaneous

  • Added the get_test_data() function and 40k/150k datasets of two small chromosomes to quickly try some functions with some data. It uses the {pkgfilecache}

  • Limit the number of threads used by {data.table} to 1 by default. We noticed that this is faster if functions are executed in a loop.

  • Removed {reshape2} and {dplyr} dependencies.

  • Replaced {bigwrig} dependency to {rtracklayer} for importing bigwig data.

  • Added the expnames() function to glance which samples were involved in a or object.

  • Added the resolution() function to glance at which resolution a object was calculated or object has.

GENOVA 0.9.995 - 20-3-2019 (The Old Lighthouse)

Added

  • HiCseg.callTAD: a function to call TADs with HiCseq (Levy-Leduc) per chromosome-arm or windowed chromosomes.
  • construct.experiment: added an option to get Z-score normalised experiment-objects.
  • hic.matrixplot: added an option to use Z-score normalised experiment-objects.
  • insulation.heatmap: added option to set leftlost bin to 0
  • insulation.heatmap: added option to use a borders-file (also for peaks!)

Changed

  • APA: sped up by using a vapply loop (@MarijneMia)
  • ATA: sped up by using a vapply loop
  • select.subset: sped up the pos-lookup
  • visualise.APA.ggplot: better divergent colors (same as Z-score colors in hic.matrixplot)
  • visualise.ATA.ggplot: better divergent colors (same as Z-score colors in hic.matrixplot)
  • genome.wide.insulation: added speudocounts
  • compartment.score: uses a more robust handing of comparable tracks.
  • genome.wide.insulation::matrix.insulation: shifted output half a bin upstream.
  • genome.wide.insulation: forcing even window-sizes to get score between bins.
  • insulation.heatmap: nicer plotting of profile and heatmap without grid
  • insulation.heatmap: refactored the scripts.

GENOVA 0.9.98 - 27-02-2019

Github-hash: 9951098

Added

  • ATA: outputs also the used TADs.bed
  • HiC_matrixplot: smoothing of the regions with no data (e.g. the white stripes) has been implemented. This is done by filling these bins with the result of a Nadaraya/Watson normalization of the kernel. Set smoothNA to true to use and smoothBandwidth to tweak
  • HiC_matrixplot: If chip.yMax is NULL, a warning will be given for the used yMaxes.
  • PE-SCAn: A maximal distance can be given with maxDist.
  • PE-SCAn: verbosity can be limited off with verbose = F
  • PE-SCAn: Catches errors when no matrices are found by cov2d.
  • PE-SCAn: A treshold for the minimum amount of BED-entries per chromosome is added: minComparables.
  • PE-SCAn: Shifted bed-entries bigger than their chromosome are now fixed (they "wrap around" to the start)
  • PE-SCAn: Returns not only the O/E matrix, but a list with a O/E score-matrix (if shift != 0), otherwise an observed score-matrix, the underlying signal and background-matrices and the shift used.
  • visualise.PESCAn.ggplot: several checks to see if the input-data is comparable (including shift).
  • visualise.PESCAn.ggplot: colorscales for O/E and O are better (i.e. no log2-divergent scale for shift==0 matrices).
  • cis.compartment.plot: a second experiment-object can be used. This is plotted in the lower-left corner. Note: only the first matrix is invisibly returned.
  • cis.compartment.plot: smoothing of the regions with no data (e.g. the white stripes) has been implemented. This is done by filling these bins with the result of a Nadaraya/Watson normalization of the kernel. Set smoothNA to true to use and smoothBandwidth to tweak
  • getTADstats: a new function to get some stats on ATA-results. Still quite buggy.
  • saddle: Forces user for either CS or chip.
  • README now contains actual text.

Changed

  • HiC_matrixplot: bed.col and bw.col are merged to chip.col. This argument can take a vector of four colours, parallel to the chip-argument.
  • HiC_matrixplot: yMax is renamed to chip.ymax.
  • visualise.PESCAn.ggplot: works woth new output of PE-SCAn
  • PE-SCAn: cov2d loops over a vectorised list without duplicates, which speeds up the code.
  • PE-SCAn: cleaned up cov2d's return-code
  • quantifyAPA: the enrichmentType argument lets you choose between pixel/mean(backgroundRegions) and the fraction of loops with more than 50% higher signal than the background.
  • visualise.compartmentStrength: at least one bin is used (bugfix).
  • saddle: extra effort to use the CS is taken by matching the CS-vector and the eigen-vector. This will fix problems due to big centromeres or shaky/different centromere-calls.
  • vignette: fixed typo's

GENOVA 0.9.971 - 13-06-2018

Github-hash: 8edef82

GENOVA 0.9.97 - 11-06-2018

Github-hash: 35772ec

GENOVA 0.9.96 - 22-05-2018

Github-hash: 7deebca