Version 0.8

This is a larger release and the first update since our
[publication](http://dx.doi.org/10.1371/journal.pcbi.1004873).

CNVkit now runs under Python 3 as well as 2.7. (#3, #101; thanks @mpschr)

File format changes:

- New "depth" column in .cnn, .cnr, .cns
- In .cns, "weight" is the sum, not mean, of bin-level weights within the segment

New script ``cnn_updater.py`` can be used to add the "depth" column to existing
.cnn, .cnr and .cns files. However, most CNVkit commands should still work with
pre-v0.8 files without using this script first. For best results, rebuild the
.cnr and .cns for an ongoing study using the existing targetcoverage,
antitargetcoverage and reference .cnn files.

Algorithmic changes:

- `reference, `gender`, `call`, `diagram`, `export`: Gender, or chromosomal sex,
  is now inferred with a statistical test instead of a fixed threshold,
  significantly improving the inferences on noisy or aneuploid samples. (#116)
- `reference`, `fix`, `call`: Center log2 values by median of chromosome
  medians, by default. (#114)
- `reference`, `metrics`, `segmetrics`: Improve the calculation of biweight
  location and biweight midvariance (now in descriptives.py).

These deprecated components (since 0.7.x) have been removed:

- Commands `rescale` and `loh` -- use `call` and `scatter`, respectively, instead
- Some options in `export bed` and `export theta` -- use `call` first instead
- Script `genome2access.py` -- use `cnvkit.py access` instead

Updated commands:

`batch`:

- New option --method, with choices "hybrid" (default), "wgs", "amplicon", to
  simplify/streamline usage with whole-genome or amplicon sequencing protocols.
  See documentation for details; in short, "wgs" and "amplicon" do not use
  antitargets or the edge/density bias correction; "wgs" by default uses the
  sequencing-accessible genome as the targets, and uses a more stringent
  significance threshold for segmentation.
- Hide/deprecate --split option; it's always on now. To ensure bin coordinates
  do not change between `batch` runs (they generally won't anyway), use the
  -r/--reference option instead of specifying -t and -a in `batch`.
- Add --drop-low-coverage option, which is passed to `segment` internally.
- The -p/--processes option is also passed to `coverage` and `segment`
  internally (see below).

`antitarget`:

- Increase the default average bin size from 100kb to 200kb.

`coverage`:

- Parallelize coverage calculation over BED rows. The number of threads can be
  specified with the `-p` option. (#121; thanks @brentp)

`segment`:

- Parallelize CBS and Haar segmentation methods across chromosomes. (#123, #125;
  thanks @brentp)

`call`:

- New --filter option, with choices 'cn', 'ampdel', 'ci', 'sem' implemented.
- With VCF b-allele frequencies (`-v`, 'baf'), always calculate the
  allele-specific integer copy numbers 'cn1' and 'cn2' so that 'cn1' is the
  larger one. BAF mirror direction stays majority-rules. (#105; thanks @mpschr)
- If b-allele frequencies are used and total copy number is zero, report allelic
  copy numbers as 0, not NaN.

`scatter`:

- Add --title option.
- Allow selecting & labeling gene(s) w/ only segments as input

`heatmap`, `scatter`:

- Allow saving plots in any image file format supported by matplotlib, not just
  The file format is determined by the output filename's extension, e.g. 'png'
  saves in PNG format -- making it easier to integrate CNVkit plots with HTML
  reports. (#120; thanks @chapmanb)

`diagram`:

- Add -g/--gender option to specify sample's known gender.

`gainloss`:

- Make output tables more consistent across options. Show individual gene names
  (rather than all genes grouped within a segment in 1 row); don't show rows
  with no gene name; report the segment probe count instead of number of probes
  within the gene; show any extra columns present in the input .cns file. (#107,
  #108; thanks @mpschr)

`gender`:

- Show column headers and Y-chromosome log2 values in the output table.

`segmetrics`:

- Add stats options for mean, median, mode
- Add MSE, SEM stats as options

`metrics`, `segmetrics`:

- Add --drop-low-coverage option (like in `segment` and `gainloss`)

Internals:

- New sub-package tabio: a more robust I/O framwork unifying support for tabular
  formats, including CNVkit's .cnn/.cnr/.cns, BED, SEG, VCF, GATK/Picard
  interval list, and text coordinates (chr:start:end).
  Base class GenomicArray and its derived classes CopyNumArray and VariantArray
  do not implement their own I/O, but rather are instantiated via tabio.
  The "import-" commands use this as well.
- Removed rary.RegionArray; all functionality is now in tabio and GenomicArray.
- New module "descriptives.py" implements descriptive statistics on plain numpy
  arrays or pandas Series instances, independent of CNVkit.
- Better testing on Travis, covering Python 2.7, 3.4 and 3.5, on both Linux and
  OS X (thanks @kyleabeauchamp, @rmcgibbo, and @mpharrigan; #110)

Bug fixes:

- `batch`: Errors in parallel processes will immediately be raised as exceptions
  at the top level, rather than dying silently. Previously, no error would occur
  until a missing output file was needed later in the pipeline. (#55)
- `segment`:

    - Skip possible R warning text when parsing CBS output (#106) and run
      Rscript with the --vanilla option (#112; thanks @jsmedmar). Non-isolated
      R processes were prone to add various warning messages to the expected SEG
      output, which could crash the "segment" command for some users.
    - Handle zero-weight bins better (#128; thanks @chapmanb).

- `scatter`:

    - Handle selected segments with an empty gene name (#104; thanks @mpschr).
    - Don't crash on zero-length GenomicArray/CopyNumArray inputs.

- VCF parsing (now within tabio) improved:

    - More robust to missing genotype (GT) & depth (DP) fields (#102)
    - Handle VCFs from MuTect2 (#122)

- `export theta`: don't crash when SNP VCF is a single, unpaired sample, or if
  segmented input (.cns) is empty.
- `heatmap`: Avoid a possible crash if a sample is missing a chromosome.

Packaging:

- Universal wheels are enabled for installation with pip (via setup.cfg).

New & updated dependencies:

- futures
- futurize
- numpy raised to version 1.9
- pandas raised to version 0.18.1
- pysam version 0.9.1.1 is specifically excluded

Version 0.7.11

New dependency on pyfaidx, a Python library for handling samtools-style
FASTA indexes (.fai).

export vcf:

- Add CNVkit version and current date (i.e. local calendar date that the
  "cnvkit.py export vcf" command was run) to the VCF header.

export theta:

- Given a VCF of SNVs called jointly in paired tumor and normal samples,
  extract SNP allele counts to THetA2's custom input format
  ("snp_formatted.txt"). The two additional files CNVkit generates this way can
  be used with THetA2's "--TUMOR_SNP" and "--NORMAL_SNP" options to improve
  estimates of tumor purity and clonality.
- Use CNVkit's segment weights and probe counts to estimate normal-sample read
  counts for each segment if no copy number reference profile (.cnn) or paired
  normal sample (.cnr) is given.
  The command's second argument is now optional and deprecated in favor of the
  "-r"/"--reference" option, which does the same thing.

import-theta:

- Save integer copy number in the "cn" column of the output file(s) (CNVkit's
  .cns format).

call, export nexus-ogt:

- When reading structural variants from a VCF file, interpret the END tag as the
  variant end position, not the length, per the VCF 4.2 specification.
  This bug could cause the b-allele frequencies calculated in `call` and
  `export nexus-ogt` to be erroneously repeated across many consecutive bins.

scatter:

- When loading CNVkit files (in any command), identify and drop rows with "NaN"
  log2 values. (CNVkit never emits these, but they could happen if a user
  generates .cnr files from Illumina CGH array data files using a custom
  script.) The other rows (spread, gc, rmask) can be NaN without a problem, but
  plotting with `scatter` would crash when adjusting the y-axis based on NaN
  log2 values. (#95)
- Detect & warn if input .cnr/.cns/.vcf is not sorted by genomic coordinates.
  This could happen if the input VCF or manually constructed .cnr/.cns file (not
  generated by CNVkit) was not sorted by genomic coordinates. Then the error
  message was cryptic, because some bins/segments/SNVs are selected successfully
  but plotting would crash when laying out the x-axis coordinates.

Internals & packaging:

- Use the pyfaidx library to extract sequences from a genome FASTA file (used in
  the `reference` command), replacing some custom code in cnvlib. (#73; thanks
  @mdshw5)
- Documentation updates.

Version 0.7.10

diagram:

- Label genes even when given only segments (.cns). Plotting segments alone,
  without bin-level copy ratios (.cnr), can be convenient to produce an
  uncluttered PDF with a smaller file size while retaining most of the important
  CNV information.

scatter:

- For calculating and plotting SNV b-allele frequencies, select the sample of
  interest from the given VCF based on the .cnr/.cns base filename, unless
  specified with `--sample-id`.

export nexus-ogt:

- Use normal-sample BAFs if normal-sample .cnr given.  Previously, it would load
  tumor BAFs (taking the first tumor sample from the PEDIGREE tag) even if the
  properly-named .cnr file was for the normal sample in the VCF.
- Add --sample-id option to select VCF sample. Useful in case .cnr filename base
  doesn't match the sample IDs in the VCF header.
- Add filtering options --min-weight, --min-variant-depth.

    - The `--min-variant-depth` option works the same as in `scatter -v`,
      filtering SNVs by coverage depth (INFO field DP, usually) for the b-allele
      frequency calculation.
    - The `--min-weight` option allows the user to discard low-weight bins since
      Nexus Copy Number doesn't use CNVKit's weights for its own segmentation
      and could be misled by the noisier log2 ratios in less-reliable bins.  For
      choosing the cutoff value, 0.5 is suitable in our experience, but check
      the distribution of weights in your own data first.

export vcf:

- Add custom VCF "FORMAT" fields: FOLD_CHANGE, FOLD_CHANGE_LOG2, PROBES. (#91;
  thanks @pcingola)

segment:

- The "flasso" method now works again; it was broken for a few releases. (#88; thanks
  @pcingola)

Packaging & internal:

- Add GRCh37 "access" BED file for users' convenience. The `access` command will
  also now raise an error if the chromosome names don't match between the
  "access" and "target" BED files.
- Work with the latest version of pysam (0.9). (#86)
- Silence some superfluous warnings from the latest version of pandas (0.18).
- Documentation updates, including more details on the `call` command.

Version 0.7.9

Bug fixes, most importantly to work around a regression in pysam.

installation:

- Require pysam version earlier than buggy 0.9 (#86)

fix, reference:

- If the majority of target bins have no or very low coverage, warn the user
  about this, skip bias corrections, and mask out the low-coverage target bins
  during centering to ensure the output is still vaguely usable and sane.
  This issue could occur because the wrong target BED was used initially, or
  maybe hybridization failed in library prep.

reference:

- Ensure the output table's columns are ordered correctly. In some cases it was
  possible for the output tables columns to be ordered differently, which still
  works in CNVkit, but is weird.

call, rescale, export:

- Check specified gender more sensibly; on failure, default to female.
  Specifically, use case-insensitive string comparison to test whether the given
  argument means "male". Treating chrX as having neutral ploidy is probably a
  less surprising fallback, especially if the "-y" flag is forgotten elsewhere
  in the pipeline.

Version 0.7.8

call:

- Put absolute copy number in a new "cn" column. When rescaling log2 ratios for
  purity, do not round to integer absolute copy number values. (#83)
- New `-v`/`--vcf` option: Calculate b-allele frequency (BAF) average for each
  segment and output as a new column "baf". Rescale BAFs if `--purity` is
  specified. Then, using BAF and total copy number (CN, the "cn" column), assign
  major and minor allele copy number to each segment and output as new columns
  "cn1" and "cn2". These values can indicate allelic imbalance, including loss
  of heterozygosity (LOH). (#84)
- New "--center" option that works the same as in "rescale".
- New method "-m none" to perform any specified transformations (rescaling,
  re-centering, adding b-allele frequencies), but do not call integer copy
  numbers.

rescale:

- Deprecated in favor of "call" with the "-m none" option, which does the same
  thing.
- If recentering is specified with `--center`, do it before, not after,
  rescaling log2 values for tumor sample purity.

export bed, vcf:

- Take absolute copy number from "cn" column if present (#83)

antitarget:

- Whitelist chromosomes X and Y along with integer chromosome names for
  inclusion as canonical mammalian chromosomes. Keep the fallback to "short"
  chromosome names if no such canonical chromosome names are detected. (#37)

reference:

- Expose bias corrections (GC, RepeatMasker, targeting density) as command-line
  options `--no-gc`, `--no-rmask`, and `--no-edge`, similar to the `fix`
  command. (#80)

Internal:

- VariantArray.read_vcf: somatic mask was the opposite of what it should have
  been, i.e. skip_somatic was skipping germline and retaining only somatic SNVs.

Version 0.7.7

Small improvements, bugfixes, and documentation updates.

fix:

    - Removed the hard filter on RepeatMasker fraction of antitarget bins. This
      filter doesn't appear to improve calling on current benchmarks.

    - Drop bins that have very high coverage in the reference, in addition to
      the low-coverage bins already dropped (normalized log2 values outside +/-
      5).

    - Ignore very-low-coverage bins when recentering (by default). For
      good-quality samples this doesn't make much difference, but it's safer and
      seems to improve the centering slightly on lower-quality samples.

    - Ensure antitarget bin weights are not set to 0 if the majority of target
      bins have no coverage -- this would cause segmentation to fail. (#82)

    - Don't crash if antitargets are empty (to support WGS and targeted amplicon
      capture), fixing a regression.

antitarget:

    - Keep untargeted contigs that appear to be "canonical" chromosomes. Prefer
      chromosomes with numeric names (autosomes in most mammalian reference
      genomes); but if none of the targeted chromosomes have numeric names, then
      fall back to chromosomes with names no longer than the longest-named
      targeted chromosome. (#37)

batch:

    - Disallow input BAMs with duplicate base filenames (#81). Now it will
      trigger an error instead of overwriting some output files.

segment:

    - `--drop-outlier` option now masks outliers according to multiples (default
      10x) of the 95'ile, not 90'ile. Benchmarking looks better.

Plots `scatter`, `heatmap`:

    - With the "-c/--chromosome" option, handle unbounded ranges (e.g.
      "chr1:100-" or "chr5:-100000") treating the missing start/end of the range
      as the start/end of the specified chromosome.

heatmap:

    - A more efficient implementation.  Now, plotting a heatmap of .cnr is
      feasible, and behavior is a bit more consistent (e.g. placement of
      rectangles is more accurate; plotting a selection where only some samples
      have data will still show all samples).

    - Don't crash if selection overlaps no segments, e.g. if the selection is a
      centromeric or telomeric region. Previously it would crash with an obscure
      error.

Misc. bugfixes:

    - batch: log # parallel processes correctly for "-p 0"
    - import-theta: fix crash; namedtuples are immutable (#77).
    - metrics: require --segments (#79)
    - rescale: fix crash if --purity is not specified
    - VariantArray: Fix VCF parsing if filters are not used.

Version 0.7.6

Minor bugfixes and improvements.

scatter:

- Tweaked plot colors for better visibility and accessibility: points are
  slightly darker, and segments are now a deep gold color instead of red.

fix:

- Downweight targets or antitargets proportionally to their relative variability
  of bin log2 values; i.e. if targets are twice twice as variable (by
  interquartile range of bin log2 values) as antitargets, divide all target bin
  weights by 2. This happens after all bias corrections and reference
  normalization, and appears to improve the final segmentation results.

antitarget:

- Don't emit antitargets for untargeted chromosomes with long names, e.g.
  "chr6_apd_hap1" -- these are presumably alternative/unassigned contigs, not
  real canonical chromosomes that deserve to be included for CNV calling.
  But do continue to keep untargeted chromosomes with names up to the length of
  the longest-named targeted chromosome.
  (Improves on #37)
- Indicate default --min-size in help message.

batch:

- Log the number parallel processes correctly when "-p 0" is used to
  automatically detect the number of CPUs -- previously, this option would print
  on the console that samples were being run in serial, but then launch multiple
  parallel processes.

segment:

- Change --drop-outliers default from 5 to 10, based on performance in
  benchmarking.

Internally:

- Fixed detection of autosomes to be used for re-centering bin log2 values and
  detecting gender.
- Fixed parsing the GATK/Picard "interval list" file format - strand and name
  were swapped.

Version 0.7.5

Global speedups, friendlier error handling and miscellaneous bug fixes.
Documentation updates (thanks @kyleabeauchamp; #67).
Expanded unit tests & restored continuous integration (TravisCI).
Raised the minimum pandas version to 0.17.1, the latest.

rescale (new command; #64):

- Adjust .cnr or .cns files for normal contamination or subclone fraction.
- Re-center log2 values by median (the usual), mode, mean, or biweight location.

segment:

- Detect outlier bins and ignore them during segmentation using a method similar
  to BIC-seq. Command line option: `--drop-outliers`; any outlier bins found
  will be logged.

coverage:

- If the given target BED files is missing the 4th column (gene names), fill in
  the dummy name "-" instead of crashing.

segmetrics:

- Expose alpha and #bootstraps as command-line options

antitarget:

- Reduce default bin size from 150kb to 100kb.

fix:

- Speed improvements: now about 20 times faster on exomes.

API changes:

- Gene names to treat as meaningless and to ignore in reporting (by default "-",
  ".", "CGH") can be globally configured in params.py
  (params.IGNORE_GENE_NAMES).
- vary.VariantArray (used in `scatter`) can now parse VCF files with no samples
  (genotypes).

Version 0.7.4

This is primarily a bugfix release.

heatmap:

- Sub-chromosomal regions can now be selected for display with the `-c` option,
  e.g. `-c chr7:125000000-145000000`, just like the same option in `scatter`.

segment:

- Fix the listing of gene names in each segment in the output .cns file.
  Previously, briefly, each gene's name was truncated to 1 character.

export:

- `bed --show variant` now filters CNAs on sex chromosomes correctly, taking
  reference and sample genders into account.
- `nexus-ogt` format now emits BAFs more similar to the original VCF allele
  frequencies. Previously, if multiple SNVs fell into a single CNVkit genomic
  bin, the allele frequencies of those SNVs would all be "mirrored" above 0.5
  before taking the median. Now the SNVs are mirrored in the direction of the
  majority of the SNVs in the bin, whether above or below 0.5, so that the
  output looks more balanced and low-frequency SNVs are more apparent.

Version 0.7.3

access:

- New command equivalent to the now-deprecated `genome2access.py` script.

target, antitarget:

- Always write output files in 4-column BED format.

scatter:

- Copy ratios (.cnr) are no longer required. Without this input file, behavior
  is similar to the now-deprecated `loh` command, but still more flexible.
- VCF input file can include multiple tumor samples and PEDIGREE tags; if a
  tumor sample ID is specified, all PEDIGREE tags will be checked to find the
  matching normal sample.
- VCFs processed by CLC Genomics Server are now parsed correctly.

loh:

- Deprecated. Use `scatter` with `-v` and no .cnr file instead.

segment:

- Preliminary support for segmenting SNP allele frequencies from a VCF in
  addition to total copy number (`-v` option). Details are likely to change in
  a later release. (#34)
- In the `weight` column of the output file, values are now the sum, not the
  mean, of the weights of the probes covered by that segment.
- The `haar` segmentation method is improved to avoid duplicate breakpoints and
  run much faster.

export bed:

- Deprecate `--show-all` in favor of `--show` with possible arguments `all`
  (like --show-all), `ploidy` (default behavior), or `variant` (show the same
  regions as export vcf).

export vcf:

- Fix a typo in the SVLEN tag definition in the VCF header -- Number should be
  1, not -1 which caused GATK parsing to fail. (#57; thanks @chapmanb)

Python library `cnvlib`:

- Logging is now done with the Python standard library's `logging` module,
  making it easier to silence or redirect status messages. In particular, unit
  tests run more quietly. (#52)
- Internal refactoring (including new features in GenomicArray, RegionArray,
  VariantArray) resulting in changes to the `cnvlib` API , as well as some
  performance improvements.

Version 0.7.2

A variety of mostly minor improvements and bug fixes over v0.7.1.

segment, gainloss, segmetrics:

    - Don't exclude very-low-coverage bins from calculations by default;
      instead, expose this option as `--drop-low-coverage`. (This option
      usually helps on tumor samples with some normal contamination, but leads
      to problems on germline samples with homozygous deletions.)

segment:

    - Output .cns files now have a "weight" column which is the mean of the
      weights of the bins it covers.
    - Output of the 'haar' segmentation method now has each segment's gene
      names listed, as with the other methods.
    - Fixed a bug where every segment's probe count (the "probes" column) could
      be overwritten with the `_` character. (#53; thanks @chapmanb)

segmetrics:

    - Each statistic is now printed in its own column, instead of squeezing all
      stats into the "gene" column. The confidence/prediction interval stats
      get two columns, `_lo` and `_hi` (lower and upper bound).

loh, scatter:

    - Given a VCF called on a tumor-normal pair, use the paired normal to
      select appropriate germline SNPs for plotting.

export:

    - New format "nexus-ogt" combines bin-level copy number ratios with
      b-allele frequencies given a VCF and a .cnr file. This replaces
      "nexus-basic" with the `-v` option that was introduced in v0.7.1;
      "nexus-ogt" stores the same info but can be viewed in BioDiscovery Nexus
      Copy Number without any special configuration (load it as the
      "Custom-OGT" data format).
    - Renamed `bed` option `--show-neutral` to `--show-all`.
    - `vcf` option `-g`/`--gender` now works properly for identifying CNVs on
      sex chromosomes.

call:

    - Fixed the `threshold` method to calculate absolute copy number on sex
      chromosomes correctly (#49; thanks @tskir).

Version 0.7.1

This is primarily a bugfix release. Many more unit test cases were added to the
automated test suite. Code coverage is now monitored (thanks @stevepeak) at:
https://codecov.io/github/etal/cnvkit/commits

export nexus-basic:

    - New optional argument "-v"/"--vcf" extracts SNV b-allele frequencies from
      the given VCF file, matches them to the bins in the .cnr file, and prints
      an additional "baf" column in the output table. These allele frequencies
      can then be viewed in Nexus Copy Number, similar to a SNP array.

call:

    - Fixed a bug in the "threshold" method where the copy number of haploid
      chromosomes was twice what it should be. The "clonal" method already
      handled these chromosomes properly. (#49)

reference:

    - Handle blank/empty antitarget BED and coverage (.cnn) files. This was a
      regression from earlier releases in v0.7.0. (#51)

fix:

    - Catch duplicated target ranges, e.g. the exact same bait labeled with two
      different gene names, and report those ranges in the error message. The
      "target" command's "--split" option should usually fix these, but
      sometimes it's not used.

faidx:

    - Catch invalid ranges that extend beyond the length of the chromosome and
      raise an informative error. This would error before, too, but the message
      would be baffling.

Version 0.7.0

CNVkit now depends on pandas, scipy and pyvcf. The internals were largely
rewritten, so please report any bugs or other regressions you find.

Documentation is much improved.

export:
    - VCF format is supported (#5, #41). The generated VCFs are compatible with
      many third-party tools, including development versions of MetaSV. (Thanks
      @chapmanb)
    - Removed the "freebayes" sub-command; use "export bed" instead.

segment:
    - The names of genes (or other targeted loci) covered by each segment are
      now included in the output .cns file.
    - The p-value or q-value threshold (depending on the method) can now be
      specified with -t/--threshold.
    - The "haar" method works properly now (#6). This segmentation algorithm is
      implemented in Python and does not require R to run. It is a bit faster
      than CBS, but not as accurate.

loh:
    - Plot variant allele frequencies (VAFs) as their actual values, 0 to 1,
      instead of the mirrored b-allele frequency (0.5 to 1). Draw segment mean
      allele frequencies separately above and below 0.5. This matches how the
      equivalent SNP array data are typically viewed.

antitarget:
    - Generate off-target bins for all chromosomes present in the "access" BED
      file, not just those where targeted regions occur. (#37)

coverage:
    - A minimum read mapping quality (MAPQ) value can now be specified with
      -q/--min-mapq. The default value is 0, i.e. reads are no longer excluded
      for low MAPQ or ambiguous mapping location. This should generally improve
      calling accuracy and avoid some spurious deletion calls.

Version 0.6.1

Small fixes in segmentation, affecting the output of `segment` and preventing
crashes in `segmetrics`:

- Exclude fewer low-coverage bins from segmentation (using a lower minimum
  coverage threshold).
- In case the first or last bins on a chromosome were excluded from
  segmentation, adjust the first and last segments on each chromosome so that
  their endpoints match the first and last bins.
- If no bins on a chromosome passed the coverage filter, instead of omitting
  the chromosome from segmentation output, generate a single segment covering
  the full chromosome, with segment log2 ratio 0.0. (So, all chromosomes in the
  .cnr file will be present in the .cns file, too.)

Version v0.6.0

Added two new commands, `call` and `segmetrics`, and a new `export` format, BED.

`segmetrics`::

- Calculates summary statistics of the residual bin-level log2 ratio estimates
  from the segment means, similar to the existing `metrics` command, but for
  each segment individually. Results are output in the same format as the CNVkit
  segmentation file (.cns), with the stat names and calculated values printed in
  the "gene" column.
- Supported stats: standard deviation, median absolute deviation, inter-quartile
  range, Tukey's biweight midvariance (as in `metrics`); also confidence
  interval, estimated by bootstrap; and prediction interval, estimated by the
  range between the 2.5-97.5 percentiles of bin-level log2 ratio values within
  the segment.
- Thanks to @mjafin for suggesting this feature (#28).

`call`::

- Given segmented log2 ratio estimates (.cns file), round the copy ratio
  estimates to integer values using either:

    - A list of threshold log2 values for each copy number state, or
    - Some algebra, given known tumor cell fraction and normal ploidy.

- The output is another .cns file, where the values in the `log2` column are
  still log2-transformed, but represent integers in log2 scale. E.g. neutral
  diploid state is represented as "0.0", not the integer 2. These output files
  are still compatible with the other CNVkit commands that accept .cns files.
- These calculations were previously done by the `export freebayes` command.
  That command is deprecated but still available in this release; it will be
  removed in the next release. The recommended approach is to instead run `call`
  first on each .cns file, and then `export bed` on all the adjusted .cns files
  to get an equivalent BED file compatible with FreeBayes `--cnv-map` option.

`export bed`:

- New format supporting the same features as `export freebayes` that were not
  moved into the `call` command (see above). The output BED file is still
  compatible with the FreeBayes `--cnv-map` option.
- New option `--show-neutral` to also output neutral-CN segments/regions, in
  addition to the CNV regions output by default.

Smaller changes:

- `gainloss`: Reduced the default log2 ratio threshold from .5 to .2
- `import-picard`: Use the un-normalized mean coverage instead of the normalized
  coverage of each target as the log2 coverage values in the output .cnn file.
  This matches the output of the `coverage` command; CNVkit normalizes coverages
  later in the pipeline.
- Some internal refactoring. Please report any bugs, real or perceived, on
  our GitHub issue tracker.

Version 0.5.0:

This release includes a variety of improvements to CNVkit's calling accuracy
and robustness. All CNVkit files built with previous versions will continue to
work with this version, but for best results, I recommend rebuilding your
reference.cnn file(s) from the targetcoverage.cnn and antitargetcoverage.cnn
files.

`coverage`:
    - Output target/antitarget coverage (.cnn) files are no longer
      median-centered. Read depths in each bin are still log2-scaled, but the
      observed read depth can now be easily recovered from .cnn files.

`reference`, `fix`:
    - Include a "flat pseudocount" in addition to the given normals, making
      paired tumor-normal calling much more robust and accurate.
    - Perform bias corrections on the input normal samples before calculating
      the average and spread of log2 values.

`fix`:
    - Do bias corrections before subtracting the reference, instead of after,
      because the reference already includes bias corrections now.
    - In addition to weighting bins by spread (which can only be observed with
      a pooled reference), also weight by bin size and deviation of reference
      log2 values in each bin from the global median. So, useful bin weights
      are now derived from "flat" and single-normal-sample references, too.

`segment`:
    - Recalculate CBS segment means using bin weights (in the R library this
      simply the mean, arguably a bug).
    - Set CBS segment start/end positions to match the underlying bin start/end
      positions.
    - Improved centromere detection -- only exclude one "large gap", if any,
      from each chromosome.
    - Tuned CBS calling parameters to improve accuracy (see benchmarks in the
      repo etal/cnvkit-examples).

`diagram`:
    - Label genes using the same criteria as the `gainloss` command: if
      segments are given, use the segment value at each gene, otherwise
      calculate the weighted average of bin-level log2 values within each gene.
    - New option -m/--min-probes to match `gainloss`.
    - Guess gender from chrX more reliably, so that the same gender is called
      from the bin-level (.cnr) and segmented (.cns) values given.

`scatter`, `loh`:
    - When plotting allele frequencies from a VCF, if segments are given
      (.cns), also apply those segments to allele frequencies to show LOH
      regions that match CNVs.
    - Skip somatic variants identified in a VCF, and try to retain only
      germline variants, when plotting LOH. (This is not very well standardized
      across callers, so please watch for bad behavior from callers other than
      FreeBayes and MuTect, and let me know about it!)
    - `scatter` only: Added options `--y-min`, `--y-max` to set y-axis limits
      on the plot.
    - Removed the deprecated `-r` option. Use `-c` instead.

The long-deprecated `cbs` command has been removed. Use `segment` instead.

Bugs in parsing and writing empty and 1-line VCF, BED and CNVkit files, and
other VCF quirks, have now been fixed (Thanks @chapmanb!)

Version 0.4.1

New features:

- `scatter` command:
    Option -c can now take coordinate ranges like -r, so -r is deprecated and
    will be removed in the next release.

- `genome2access.py` script:
    New -x option to exclude additional regions. Added a new file
    "data/access-5k-mappable.hg19.bed" which used this option to exclude the
    Encode "Duke" and "Dac" low-mappability regions.

Also:

- Improved the help/usage messages for several commands. Added a "version"
  command that prints the current CNVkit version. (Thanks @HenrikBengtsson)
- Tuned CBS calling parameters to improve segmentation accuracy according to
  some benchmarks.
- Sped up a few slow functions identified by profiling. In particular,
  `metrics` is much faster now.
- Fixed bugs/incompatibilities in plotting commands and cleaned up the source
  code (Thanks @chapmanb and @roryk)

CNVkit can now be obtained and run as a Docker container:
https://registry.hub.docker.com/u/etal/cnvkit/

Version 0.4.0:

- Now safely operates without off-target bins (i.e. empty "antitargets"), so
  CNVkit can be used on WGS and amplicon capture datasets.
- New options in the "scatter" and "loh" plots, including contributions by
  @chapmanb and @roryk.
- Bug fixes in export and plotting commands, among others.
- Substantially improved documentation.