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v0.9.10
Version 0.9.10 ============== This long-awaited release includes major plotting enhancements in the `heatmap`, `scatter`, and `diagram` commands, as well as a new `export gistic` command, thanks to joint work by @tetedange13 and @tskir (see below). There are also significant infrastructure improvements including bug fixes, modernized packaging, and build/test automation. New features ------------ `diagram`: - New options `--no-gene-labels` to not display gene labels on the plot, and `-c` / `--chromosome` to plot a single chromosome (#628, #629, #634; thanks @tetedange13) `heatmap`: New CLI options (#35, #625, #632, #652; thanks @tetedange13 and @tskir): - `--vertical`: Transpose the plot, displaying the genome axis vertically instead of horizontally - `--delimit-samples`: Add an delimitation line between each sample row (or column, with `--vertical`) - `--title`: Set the plot title `scatter`: - New option `--fig-size`: Set the output image dimensions (#600, #641; thanks @tetedange13 and @tskir) - Show triangles at the bottom of the plot to indicate where segments are hidden below the plotted region by automatic pruning at 'ymin=-5'. Also log a warning when this happens. (#385, #643, #645; thanks @tetedange13, @tskir, and @micknudsen) `export gistic`: - New export command to generate an unsegmented "markers" file for use with GISTIC. GISTIC also takes a second input file with corresponding segments in SEG format, which CNVkit can generate with `export seg`. (#622, #623, #776; thanks @tetedange13, @tskir, @BioComSoftware) API and CLI changes ------------------- - Running `cnvkit.py` without any arguments will now display the full help text instead of an error message. - Supporting scripts (aside from `cnvkit.py`) are no longer installed automatically. They are still available in the source tree. Documentation ------------- - Clarified `bintest` usage, provided an example, and explained outputs. (#646; thanks @tetedange13 and @tskir) Bugfixes -------- - Fixed several errors and warnings due to outdated usage of dependencies, e.g. pandas, pysam. - Fixed the Dockerfile and Docker image to install R packages properly for CNVkit to use internally. (#765; thanks @28rietd) - Made the Makefile example/test workflow more portable across environments. (#661, #666, #695, #699; thanks @tetedange13) - `batch`: Apply --drop-low-coverage option in the segmetrics step. (#694) - `bintest`: Include 'probes' column in .cns output so that it is valid .cns (closes #693) - `fix`: Condense the error message when coordinate set contains duplicate values. (#637, #638; thanks @tskir) - `fix`: Choose a smoothing window fraction based on the data size to help correct biases better at the extremes of the GC range, where previously some residual GC bias could still be present after correction. (#379) - BED inputs: Handle UCSC BED 'browser' header line, as used in Agilent BED files with a 2-line header. (closes #696, #618) Internal -------- - Modernized the packaging configuration with pyproject.toml, leaving a stub setup.py for legacy setuptools compatibility. (#790) - Set up automated testing through GitHub Actions (GHA) to verify Python versions 3.7 through 3.10 using pytest and tox. The latter make local testing with multiple Python versions more reliable, too. (#792, #793, #794) - Updated minimum dependency versions to roughly match Ubuntu 22.04 LTS packages; these are used in CI, too. - Applied black and pylint to reformat the codebase consistently and replace deprecated calls to libraries. (#795) - Remove joblib pinning (#589, #770; thanks @DavidCain and @risicle) - Remove networkx pinning (#606, #771; thanks @DavidCain) - Make the extreme-GC filters more easily configurable via `params.py` (#738, #752, #753, #764; thanks @tetedange13 and @tsivaarumugam)
8d477b0
2023-02-25 02:19
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v0.9.9
Version 0.9.9 ------------- This release contains a new script and, more importantly, a volley of bug fixes by @tskir, a new CNVkit collaborator. New script `genome_instability_index.py`: - For each given sample (.cnr or .cns, ideally .call.cns), this script reports two values, the number of non-neutral segments and the fraction of the total sequencing-accessible genome that they cover. Together, these values have been described as the Genome Instability Index (G2I) by [Bonnet et al. (2012)](https://doi.org/10.1186/1755-8794-5-54). These numbers are not difficult to calculate directly from .cns files, but they are frequently requested, so here you go. Bug fixes by @tskir: Installation: - Set NetworkX minimum version to work with pomegranate on Python 3.9. (#614, #606; thanks @auberginekenobi) genemetrics, diagram, scatter: - Fix an error in iterating over chromosomes during gene-wise operations or gene selection. (#580, #573, #576, #579; thanks @diushiguzhi @eriktoo @hrkemp @drmrgd @HYan-lei) access: - Fix an error when all chromosomes listed in the exclusion BED file appear only once. (#581, #574; thanks @dajana17) autobin: - Allow specifying explicit output filenames via -o/--output. If this option is not used, the behavior is the same as before. Some pipeline frameworks such as Snakemake require output filenames to be explicit in wrapped commands. (#608, #607; thanks @enes-ak) - Fix median-size file selection. (#613, #611; thanks @michaelsykes) coverage: - Fix a potential crash with the -c option; generally make the -c option's results more stable. This changes the results you'd get with `coverage -c` compared to previous CNVkit versions, but in any case -c isn't recommended for production use, only for algorithm exploration. (#598, #593; thanks @joys8998) genemetrics: - Rename column `n_bins` to `probes` in output, for compatibility with 'call' and 'export' commands. (#586, #585; thanks @eriktoo) scatter: - Avoid losing short segments in rasterized PNG output, depending on DPI settings. (#615, #604; thanks @jimmy200340) - Allow NCBI-style chromosome names that contain a ".", e.g. "NC_039902.1". (#603, #602; thanks @amora197) segment: - Fix an IndexError during smoothing when the signal is shorter than a window, e.g. on chrY where the chromosome contains few bins. (#590, #587; thanks @tetedange13) Improvements from other contributors: - scripts/guess_baits.py: Fix a copy-paste error on script launch. (#588; thanks @sssimonyang) - Documentation: Link to the Debian package alongside other packages. (#562; thanks @mr-c)
aff02f9
2021-05-28 15:09
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v0.9.8
Version 0.9.8 ------------- Continuing a focus on stability and compatibility with other software: * Support for reading CRAM files with an optional user-provided local FASTA file for the reference genome sequence. (#555; thanks @johnegarza) * Call Rscript subprocess with safer flags for the R environment. Previously, `--vanilla` ignored R environments with the library path in a non-default location specified in the user's .Rprofile. Now, `--no-restore` and `--no-environ` ensure a clean environment but still respect the user's .Rprofile settings beyond that. (#491; thanks @pablo-gar) * Compatibility with the latest release of pandas. (#502, #523) This release also fixes some regressions reported since the release of CNVkit 0.9.7 (which introduced a number of new performance optimizations). * `scatter`: A bug when plotting a region of a chromosome. (#536, #457; thanks tskir) * `scatter`: An IndexError when plotting entire chromosomes, e.g. chr7. (#541, #461, #535; thanks @tskir) * `fix`: A bug that occurred after automatic bias corrections, introducing NaN-valued rows in placed of rejected bins, leading to a downstream crash in CBS segmentation. (#551, #436, #547; thanks @johnegarza)
b218280
2020-12-14 06:02
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v0.9.7
Version 0.9.7 Stable release with only minor changes from the previous beta release 0.9.7.b1. New contributions: - Cram support: Look for and use .cram + .crai alignment and index file pairs, in addition to .bam + .bai. (#495, #434; thanks @sridhar0605) - Update Docker file to use Python 3 apt packages and pip3 (#493; thanks @keiranmraine) - Documentation fix (#496; thanks @rollf)
7472df6
2020-05-29 14:04
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v0.9.7.b1
9486712
2019-12-01 06:59
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v0.9.7.b0
Version 0.9.7-beta This release contains several major enhancements particularly relevant to germline analysis. If used in production pipelines, further evaluation and benchmarking would be wise. Highlights: **Control sample clustering**: To make better use of larger reference sample pools, `reference --cluster` will correlate the given normal samples' bin-wise coverage depths to extract clusters to be used as reference profiles. The reference .cnn file produced this way will then contain the `log2` and `spread` summary statistics for each cluster, in addition to the global summary stats. Given this "clustered reference" profile, `fix --cluster` will then correlate each test sample to each clustered `log2` profile in the reference to choose the most relevant control pool for normalization. The `batch` option `--cluster` will perform both these steps. Nod to Gambin lab and the authors of ExomeDepth, CoNVaDING, CLAMMS, and others for inspiration. (#308) Calculation of bin weights has changed. **This will change your segmentation results**, hopefully for the better. Details below. (#429) The `batch` pipeline now performs some **segmentation post-processing** automatically: calculating and filtering segmentation calls by 50% confidence intervals of the segment mean log2 ratios, in order to reduce false positives, followed by separate bin-level testing to detect small (e.g. exon-size) CNVs that were not caught by segmentation. The bin- and segment-level results are returned as separate .cns files; deciding whether and how to combine or use these results together is left as an exercise for the user. We've **dropped Python 2.7 support**. Python version 3.5 or later is now required. This is a beta release. Please let me know how it works for you via the Issues page. If this release contains any issues that are blocking your work, try installing one of the previous stable versions 0.9.6 or 0.9.5:: conda install cnvkit=0.9.6 Dependencies ------------ - Remove all Python 2.7 compatibility shims. - Raise minimum pandas version from 0.20.1 to 0.23.3. - Add scikit-learn (dependency of pomegranate, for HMM segmentation). Remove the older hmmlearn implementation. Commands -------- `batch`: - Post-process segments with `segmetrics` (50% CI), `call` (filter by CI, but don't call integer copy number), and `bintest`. - Return `bintest` result as a separate, independent .cns output. - Add option '--segment-method', equivalent to `segment -m`. - Rename option '--method' to '--seq-method' (but '--method' still accepted for now). - Add option `--cluster`, passed to `reference` and `fix` if given. (#308) `bintest`: - New command superseding `cnv_ztest.py` script. - Report p-value as a column `p_bintest` (previously `ztest`) in the .cns output. - Fix probabilities for positive log2 values, i.e. gains, which previously always had p-value = 1.0. (#429) `fix`: - Change calculation of bin weights to be more consistent with `1-var` meaning, with more emphasis on reference spread. It is now simpler, more consistent with `import-rna`, and particularly improves the accuracy of `bintest`. (#429) - Squeeze the range of reference-free weights - Drop bins with gc outside [.3, .7]. CLAMMS paper shows these bins carry no useful signal. - With `--cluster` and a clustered reference input, calculate the test sample's Pearson correlation versus each cluster's log2, and take the best one for normalization. `reference`: - With `--cluster`, do k-means clustering of the sample bin-level read depth correlation matrix, per [Kusmirek et al. 2018](https://doi.org/10.1101/478313). Parameter k defaults to the cube root of number of samples. Only clusters of at least 4 samples are kept for emitting summary statistics in the reference profile. `segment`: - hmm: Fix pomegranate-based implementation. Use iterative Savitzky-Golay smoothing with a narrow bandwidth. - Use HMM for post-TCN segmentation on VCF allele freqs - Add parameter for smoothing before CBS (thanks @EwaMarek) `segmetrics`: - Add 'ttest' option for 1-sample t-test p-value. - Implement & expose --smooth-bootstrap option. For smoothing, KDE bandwidth is based on each bin's weight as a proxy for the SD of its log2 ratio values. To reduce the risk of over-smoothing on larger sample sizes, we use a loose interpretation of Silverman's Rule to reduce the bandwidth as the number of bins in a segment increases (k^-1/4). API --- - `do_heatmap`: Add 'ax' parameter (thanks @fbrundu) - `CNA.residuals()`: speed; keep index intact in returned pd.Series - smoothing: Linearly roll-off weights in mirrored wings. Affects CNA.smoothed() / savgol, but not rolling median bias correction. - Rename `CNA.smoothed()` to `CNA.smooth_log2()`, since it returns the smoothed log2 values, not a new/altered CNA. Bug fixes --------- - `batch`: Fix argparse formatting issue (#466) - `import-rna`: Fix a regression in reading 2-column per-gene counts (`-f counts`). - `reference`: Fix sex inference/usage when creating haploid-x reference (#459; thanks @duartemolha) - `scatter`: Use a safe matplotlib backend on OS X to avoid crash - VariantArray: Fix/streamline indexing of variants by bin/segment
ac14e5a
2019-11-30 02:45
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v0.9.6
Version 0.9.6 ============= Much-needed maintenance and bug fixes, for the most part. Some key dependencies have changed, though this should be generally painless for you, and one or two regressions introduced by recent optimizations have been fixed. This will be the last CNVkit version to run on Python 2.7. The next major release of pandas (0.25.0) will remove support for Python 2.7, and once that happens it will become increasingly difficult to install future versions of CNVkit on Python 2.7 -- so we're not going to try. The segmentation method `flasso` depends on the R package `cghFLasso`, which is unmaintained and has been removed from CRAN. For now, `segment -m flasso` is still supported if you already have `cghFLasso` installed. But given the above, `flasso` will be removed from the next CNVkit version in favor of the HMM-based methods. Dependencies ------------ - Raised minimum pandas version from 0.18.1 to 0.20.1, and support up to 0.24.2, resolving some warnings and an error in pandas 0.22+. (#413; thanks @chapmanb) - The soft dependency on `hmmlearn` is replaced with an explicit dependency on `pomegranate` for the HMM-based segmentation methods. This dependency will now be pulled in automatically when installing via `pip` or `conda`. - The R package `cghFLasso` has been removed from CRAN, and therefore is no longer a dependency of CNVkit and will not be installed automatically through the standard `conda` installation method. (#419) Commands -------- `antitarget`: - Be more specific in removing noncanonical chromosomes (e.g. alternate contigs, mitochondria) from the binned regions. This avoids skipping chromosomes of interest in some non-human genomes with non-numeric contig names, like yeast. (#388; credit for regexes to @brentp) `coverage`: - With `--count-reads`, use query aligned length to handle soft-clipped reads properly. Now the results with and without this option should be similar. (#411; thanks @desnar) `segment`: - For `-m flasso`, partition array by chromosome to avoid edge effects. (#409, #412; thanks @giladmishne) - Removed the deprecated option `--rlibpath`; use `--rscript-path` instead. - Note that the HMM methods are still provisional. A stable, supported version of these methods will be provided in the next CNVkit release. Python API ---------- - `do_scatter` now returns a figure (#408; thanks @jeremy9959) Bug fixes --------- - `scatter`: Whole chromosomes can once again be specified with `-c`. (In the previous release, a chromosome without coordinates would cause an IndexError.) (#393) - `import-rna`: Option --max-log2 can now be specified by users. (Previously, only the default value of +3.0 worked.) - VCF I/O (`skgenome.tabio`): Support GATK 4's VCF files that contain records with empty ALT alleles, substituting zero if ALT AD is missing. (#391; thanks @chapmanb) - Due to a certain versioning-dependent interaction between numpy, pandas, cython, and conda (details [here](https://github.com/numpy/numpy/pull/432)), CNVkit may have printed spurious RuntimeWarning messages which could be safely ignored. The current release attempts to silence these messages if they occur. (#390).
1c8d69d
2019-03-22 05:03
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v0.9.5
Minor bugfix and usability improvement. `autobin`: Ensure targets are non-empty and match BAM chrom names (closes #371) `segment`: segment: Suppress help text for deprecated --rlibpath (#317) segment: Fix help text display (#380)
fd35552
2018-08-13 11:53
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v0.9.4
6a6266b
2018-08-02 23:24
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v0.9.3
Version 0.9.3 This release fixes a single bug that caused the `segmetrics` command to crash (#325). Specifically, the command would crash unless at least one option from each of the following option sets was specified: - Location statistics: --mean, --median, --mode - Spread statistics: --stdev, --sem, --mad, --mse, --iqr, --bivar - Interval statistics: --ci, --pi This bug would not be triggered by calling `cnvlib.do_segmetrics` through the Python API, which is why it was not caught in automated testing.
9bdb083
2018-03-06 09:42
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v0.9.2
Version 0.9.2 This release contains a new command `import-rna` to infer coarse-grained copy number from RNA expression data. (#151) Three new HMM-based segmentation methods are offered: 'hmm', 'hmm-germline', and 'hmm-tumor'. These should be considered experimental and used with caution; the implementations are likely change in the next release. The option `--male-reference` in the commands `batch`, `reference`, `fix`, `call`, and `export` (at least) has been renamed to `--haploid-x-reference` everywhere to reduce user confusion. A shim is in place so `--male-reference` will continue to work. Documentation, logging, and some error messages are improved. Thanks to @chapmanb, @MajoroMask, and others for contributing to this release. Dependencies ------------ - 'pandas' version 0.22 is supported. - 'pysam' version 0.13.0 is supported. - 'hmmlearn' version 0.2 is a run-time requirement to use the new HMM-based segmentation methods. The rest of CNVkit can be run without it. To ensure the right version is installed, install CNVkit with conda as usual, then install hmmlearn with pip within the CNVkit conda environment. - Assume and require pip/setuptools for installation. (This is included with stock Python 2.7 and later.) Scripts ------- - New script "skg_convert.py" to convert between BED, GATK interval list, GFF, VCF, and tabular formats using the 'skgenome.tabio' sub-package, with options for simple post-processing. - Removed the deprecated script refFlat2bed.py. (Use skg_convert.py instead.) Commands -------- `access`: - Drop noncanonical, untargeted contigs/chromsomes by default. This affects analyses run from scratch with `batch`, too. (#169, #299) `segment`: - Three new methods can be specified with `-m`: `hmm`, `hmm-germline`, and `hmm-tumor`. - With `-m flasso`, force a breakpoint at centromeres, as was already done for the default 'cbs' method. `reference`: - The option `--antitargets` is no longer required to build a flat reference. Previously, building a flat reference for WGS or TAS required creating an empty file to use as antitargets alongside the target BED. - Print a warning if the sample sex inferred from targets does not match that of antitargets. (#281) `scatter`: - Removed the deprecated, invisible option `--background-marker`. (Use `--antitarget-marker` instead.) - Trendlines should reflect small CNVs better, while preserving overall smoothing. The implementation now uses the Savitzky-Golay method instead of a Kaiser window, and the smoothing bandwidth is better-tuned. (This can also slightly improve outlier filtering in `segment`.) `export seg`: - Add option `--enumerate-chroms` to replace chromosome or contig names with sequential integers. Previously, this renumbering was always done, following some version of the SEG format. But since most tools don't require the contigs to be sequential integers, and this behavior causes trouble for users, it's now disabled by default. (#282) `gainloss`/`genemetrics`: - Rename `gainloss` command to `genemetrics`. A shim is in place so `cnvkit.py gainloss` will continue to work. (#278) - Report segment- and bin-level weight and probes separately. (#107, #278) Bug fixes --------- - autobin: Require -g/--access for WGS (#289) - batch: Use the "access" regions for the WGS workflow to choose bin size; these were previously being ignored, so bin sizes were too large, being based on the size of the whole genome, not just sequencing-accessible regions. - call: Safely handle bins with zero weight when running `call --filter cn`. (chapmanb/bcbio-nextgen#2112; thanks @chapmanb) - coverage, guess_baits.py: Handle input BED files containing >4 columns. (#301) - gainloss: Without `-s`, make 'depth' the weighted mean of bins, not just the first bin's value. - segment: Ensure the .cns output file's columns are sorted properly (#291) - vcfio: Don't crash if a record has no ALT values (#279) - tabio: - Recognize BED format with decimal in chromosome name (#293) - Improvements to GFF/GTF/GFF3 parsing. The new options are mostly accessible through the Python API and the script 'skg_convert.py'. (#311) - In 'read_auto' (and all CNVkit commands that take regions as input), determine the file format first by checking the file extension and verifying the format of the first(-ish) line. Only if that doesn't work, fallback to the original method of testing the first(-ish) line against a brittle series of regular expressions. (#315) Python API ---------- - cnvlib.write: Newly available at the top level to write tabular files (like .cnr and .cns), symmetric with 'cnvlib.read()'. The 'cnvlib.tabio' alias to 'skgenome.tabio' has been removed; to read and write formats other than TSV-with-header ('tab'), import and use 'skgenome.tabio' directly. - CopyNumArray.squash_genes: remove deprecated keyword argument 'squash_background'. Use 'squash_antitarget' instead. - segmetrics: Move the functions supporting this command from 'cnvlib.command' to a new module 'cnvlib.segmetrics'.
7faa7b0
2018-02-26 14:04
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v0.9.1
Version 0.9.1 Highlights: Useful enhancements and changes to plotting and segmentation, and a new script for single-exon CNV testing. Plus, bug fixes and usability improvements to avoid unexpected errors. (#250, #255, #262, etc.) Dependencies ------------ - Compatible with the most recent pandas version 0.21.0 (#273, #274; thanks @chapmanb) - R dependencies were reduced to simplify installation Scripts ------- - Renamed "cnn_*.py" to "cnv_*.py" - New script "cnv_ztest.py" to detect single-bin (e.g. single exon) deep deletions and high-level amplifications. - In "cnv_updater.py", rename "Background" (i.e. off-target) bins to "Antitarget", addition to adding a "depth" column if it's missing. Commands -------- `autobin`: - Raise the maximum target/antitarget bin sizes to 50kb/1Mb. `fix`: - Allow specifying sample_id via ``--sample-id``/``-id``, in case the input coverage filenames do not have the expected form "sample_id.targetcoverage.cnn" and "sample_id.antitargetcoverage.cnn". (#269; thanks @chapmanb) `segment`: - Process each chromosome arm separately (with 'cbs' and 'haar', but not 'flasso'). Centromere locations are guessed from the largest gap between sequencing-accessible regions, and are not necessarily the true locations, although they do match fairly well on the human genome. - Logging of dropped bins is streamlined somewhat. - New method `-m none` to only calculate arm-level segment means (for testing and experimentation). `scatter`: - Highlight non-neutral segments from .call.cns. If segments have the columns 'cn' and potentially also 'cn1' and 'cn2' (as added by the `call` command), use those fields to display copy number alterations, LOH and allelic imbalance with colorized segments (orange by default), and use gray for neutral segments. If a VCF is also given, the same is done for SNVs in the lower panel. Otherwise, all segments are colorized as before. (#18, #157) - New option `--by-bins` to display x-axis positions by sequential bin number on each chromosome, rather than genomic coordinates. This makes the plots much more useful with targeted amplicon sequencing data, or very small gene panels. (#63) - Trend line (`--trend`) now accounts for bin weights, which generally results in a better fit. - Improved interaction of -c and -g options: - Only apply the window margin (-w) if -g is used alone, or -c specifies a small chromosomal region with no genes. - Allow an empty gene list (-g '' or -g ',') to prevent highlighting and labeling of any genes / small non-genic "Selection" in the -c region. - If any gene in -g is not fully within the region specified by -c, name that gene and its coordinates in the error message. - If the -c region has size <=0, show a specific error message. - Handle NaN log2 values when calculating y-axis limits. `heatmap`: - Incorporate the `--by-bins` argument to match `scatter`. (#63) - Warn if selected region contains no data for a sample. This helps troubleshoot if a chromosome name was mis-specified on the command line. (#268) `export seg`: - Change column headers to match DNAcopy output. The column headers generally don't matter in the SEG format, but the DNAcopy dataframe is considered the canonical form. Python API ---------- - cnvlib.do_segment -- new keyword argument min_weight to drop bins with 'weight' below the specified value. If not used, then only bins with weight 0 will be dropped. This feature is not recommended for normal usage and is not available on the command line. - cnvlib.do_scatter -- Remove deprecated keyword argument 'background_marker' in favor of 'antitarget_marker', corresponding to `scatter` options deprecated in v0.9.0. - cnvlib.cnary.CopyNumArray: Add method 'smoothed', which calculates the trendline displayed by the `scatter` command. - skgenome.tabio: Add read support for samtools 'dict' format, which resembles the plain-text SAM header and can contain chromosome names and sizes. - skgenome.gary.GenomicArray: Add magic methods __bool__ (Py3) and __nonzero__ (Py2) to ensure an empty GenomicArray, i.e. 0 rows, is treated as false-ish on both Python 2.7 and 3.x.
b20dc5b
2017-11-10 04:05
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v0.9.0
Version 0.9.0 ============= In addition to bug fixes, documentation updates, and usability improvements, this release includes some larger changes: - The off-target bins in .cnn and .cnr files are now assigned the label "Antitarget" instead of "Background" in the "gene" column. The label "Background" in existing files will still be handled the same way, but new output files generated with CNVkit 0.9.0 and later will use the "Antitarget" label -- so, earlier versions of CNVkit may have problems with files produced by CNVkit 0.9.0. Some command line options and API keyword arguments similarly replace "background" with "antitarget", with shims in place for compatibility with existing scripts. (#171) - The sub-packages 'genome' and 'tabio' are now in a separate top-level package 'skgenome', still included in the CNVkit distribution. (See "Python API" below.) This does not affect the command-line usage of CNVkit, but clears the way to extract a scikit-genome package that can be installed and used separately from CNVkit for computing with genomic intervals. Documentation ------------- - Link to example VCF in the test suite - Describe the 'breaks' command's output columns ( #220) - Show an example customizing a plot with pyplot ( #196) Dependencies ------------ - pysam: raise minimum to 0.10; support new version 0.11.2.1 (#218; thanks @chapmanb) - pandas: support new version 0.20.1 (#215) - numpy: support new version 0.13 (#235, #238) Commands -------- `batch`: - Log the CNVkit version number at the start of the run - Print a message at the end if no tumor/test samples specified. (#214) - Clarify error messages for bad option combinations (#216) - Removed deprecated, suppressed/invisible option `--split`. It was a shim in the 0.8 series to support old scripts. `reference`: - Ensure the inferred chromosomal sex matches between the targets and antitargets for the same sample. If the inferences do not match, prefer antitargets. (#234, #237) `fix`: - Warn & don't reweight bins if most antitargets have no/low coverage. This avoids a variety of surprising downstream problems when the input was specified as hybrid capture (the default), but is actualy from targeted amplicon sequencing, or otherwise has no reads mapped to most off-target bins. `segment`: - Log the segmentation and p-value/q-value threshold `call`: - Add option --center-at - Let --center w/o argument do 'median' `diagram`: - New option `--title` to add a custom title to the top of the generated figure (#239; thanks @micknudsen) `export vcf`: - When given a .cnr file corresponding to the usual segmented input file (.cns), emit the CIPOS and CIEND tags in the generated VCF. These indicate the "fuzzy" coordinates of segment breakpoints. Here, the ranges are simply the widths of the underlying bins adjacent to each segment breakpoint. These tags can help meta-methods aggregate/harmonize CNVkit's calls with those of other structural variant callers. (#72) `import-picard`: - Don't accept directory as an argument (was deprecated). - Be a little more flexible in filenames accepted: instead of requiring input files to be named `*.targetcoverage.???` or `*.antitargetcoverage.???`, strip the full suffix and default to 'targetcoverage.cnn' output suffix, or 'antitargetcoverage.cnn' if input filename contains 'antitarget'. Works the same for filenames following the earlier convention, but now pretty safe for amplicon targets with arbitrary filenames, and slightly less spooky. Bug fixes --------- - `antitarget`: Don't crash if -g/--access is not given (#207) - `batch`: Don't crash in 'wgs' mode when given just targets (-t) without a FASTA reference genome sequence (-f) -`call --filter ampdel`: Drop segments with copy number (`cn` field) between 0 and 5, exclusive, as the documentation indicates. Previously, it was just merging adjacent segments with copy number 1--4, but not dropping them. (#222) - `export cdt`: Match the CDT spec. Fix a regression in which columns could be swapped/misaligned versus the header. Add a dummy "EWEIGHT" row to ensure Java TreeView starts reading data from the correct line in the file. - `export theta`: Don't crash on bins where reference is NaN. (#168) - `metrics`, `descriptives`: Handle degenerate/trivial cases consistently. (#202) - `segment`: Handle sample names that are integers with leading zeros (#213) - `sex`: Don't crash if chrX and chrY are both missing (#236) - VCF parsing (`call`, `scatter`, `segment`): - Safely handle small or empty VCF files that previously could trigger a crash during BAF calculation. Now, with an empty VCF an all-blank "baf" will be emitted. (#218, #224; thanks @chapmanb) - Improve handling of Mutect2 VCF files, somewhat. Mutect2 VCFs are still not recommended as input to CNVkit; try FreeBayes or GATK HaplotypeCaller instead. (#195) Python API ---------- Moved sub-packages 'genome' and 'tabio' to separate top-level package 'skgenome' (#201). The top-level `cnvlib` API is mostly the same otherwise, but supporting modules were refactored to decouple `skgenome` from `cnvlib` and remove redundancies. In particular: - Split module `cnvlib.core` split into `skgenome.tabio` and `cnvlib.cmdutil` - Remove GenomicArray static method `row2label` in favor of functions `to_label` and `from_label` in new module `skgenome.rangelabel`. - The SEG writer in 'tabio' now replaces chromosome names with 1-based integer indices, per SEG spec/convention. The `export seg` command now uses this writer directly. Scripts ------- - Remove the script `coverage_bin_size.py`, previously deprecated in favor of the `autobin` command. - Add `skg_convert.py` to convert between tabular formats. - Add `cnn_annotate.py` to replace the 'gene' field for each bin in a .cnn or .cnr file, given a gene annotation database like refFlat.txt. The need for this comes up occasionally when users notice at the end of an analysis that vendor-annotated targets are not the desired gene names.
87a0c6e
2017-08-18 02:02
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v0.8.5
Version 0.8.5 New 'autobin' command, replacing the script `coverage_bin_size.py`. Fixed some bugs and usability issues. Unit tests improved, especially for the 'cnvlib.genome' sub-package. Dependencies ------------ - Pandas 0.18.1 is once again supported. Previously the minimum version was 0.19.1. (chapmanb/bcbio-nextgen#1836) - Pysam minimum version is still 0.9.1.4, but slightly older versions in the 0.9 series may still work too. (#192) Commands -------- `autobin`: - New command, replacing and extending the script `coverage_bin_size.py`. The script is still included (and shares most of the same code), but is considered deprecated and will be removed in the 0.9.0 release. (#170) - In 'amplicon' and 'hybrid' modes, ensure sampling regions for coverage is the same in every run by set random seed. (#191) `antitarget`, `autobin`, `batch`: - Fix an issue in GenomicArray.subtract() that caused some of the expected output regions to be missing. In cases where this caused an entire chromosome to be lost, the `coverage_bin_size.py` script` and autobin` and `batch` commands in `hybrid` mode would crash. (chapmanb/bcbio-nextgen#1799) `batch`, `diagram`: - Fix creation of chromosomal diagrams with `--diagram` and the `diagram` command. (#190) `export`: - In `export seg`, use 1-based indexing in the SEG output. (#197) - Fix `export cdt` format; it was generating Java TreeView (jtv) earlier.
e8e4c9a
2017-03-05 06:59
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v0.8.4
Version 0.8.4 This minor release focuses on improving usability and fixing some bugs. Documentation is updated (thanks @kyleabeauchamp for #186). Dependencies ------------ - Raise minimum pandas version from 0.18.1 to 0.19.0 - Raise minimum matplotlib version to 1.3.1 Commands -------- `fix`, `metrics`: - Set PRNG seed to ensure reproducible results. The pipeline is now fully repeatable with identical results if run in serial, i.e. without `-p`. `fix`, `reference`: - Ensure bias smoothing window size is at least 5. This reduces the occurrence of 0-log2, 0-spread bins on a 32-bin dataset, but doesn't eliminate it. (#181) `fix`: - Don't complain about mismatched sample IDs if antitargets are blank. This allows reusing a blank "MT" file in a shell loop for WGS and amplicon data. `reference`: - Make antitargets (antitarget.bed or \*.antitargetcoverage.cnn) an optional argument. Previously this argument was required, so processing WGS or amplicon data, which has no off-target regions or reads, required the user to create and provide a blank BED file or appropriately named, empty .cnn files. (#183) `segment`: - Don't log "Dropped 0 low-coverage bins". Only log when it actually drops bins. `diagram`, `heatmap`: - Add option `--no-shift-xy`. Shifting X and Y according reference and sample sex was done in diagram, but not heatmap. Now it's optional in both. `heatmap`: - Add a legend of log2 ratio colors to the plot. (#36) - Add options `-x`/`--sample-sex` and `-y`/`--male-reference`. (#172) `gender`/`sex`: - Rename 'gender' command to 'sex', with shim for backward compatibility. (#182) - In other commands, the `-g`/`--gender`` argument is renamed to `-x`/`--sample-sex`, also with a compatibility shim. Argument values `x` and `y` are accepted in addition to `f`/`female` and `m`/`male`, respectively. `import-picard`: - Deprecate searching a directory tree for files. It was a vestige of early lab work, and makes a shaky assumption about Picard CalculateHsMetrics ``--PER_TARGET_COVERAGE`` output filenames. API --- - The ``do_*`` function implementations moved to their named modules. The ``do_*`` functions can still be called or imported from the `cnvlib` and `cnvlib.commands` modules. - All parsing and serialization of "chr:start-end" genomic region labels is consolidated under a new module, `cnvlib.genome.rangelabel`. These functions are used in in tabio.textcoord, GenomicArray.labels(), and elsewhere to ensure consistent behavior. Internal -------- - `cnvlib.genome`: Handle nested bins correctly in the `merge`, `flatten`, and `intersect` modules, functions and GenomicArray methods. Verified with thorough unit tests. - VCF: If the paired normal sample's genotypes are all 0/0 or missing, fall back to `--zygosity-freq` (inference from b-allele frequency) rather than marking all variants as somatic. Then infer and drop additional somatic SNVs based on genotype after parsing, and only if that wouldn't drop all records. This allows CNVkit to safely distinguish somatic vs. germline in VCFs from Mutect2, though Mutect2 is still not recommended. (#184)
8a5e3c2
2017-02-16 08:00
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v0.8.3
fa44480
2017-01-18 08:39
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v0.8.2
Version 0.8.2 This release covers a number of internal changes to improve the stability and consistency of CNVkit, as well as new and improved command options to make more features available from the command line. Due to a slight change in the binning procedure (see `target` and `antitarget` below), newly generated target and antitarget BED files, or a reference generated with `batch`, may not use the same bin boundaries as earlier versions. CNVkit will check these files for consistency and alert you if your BED or .cnn files do not match because of this change, e.g. running `batch` from scratch with the same panel but with two different CNVkit versions. If you want to update CNVkit mid-project, either keep using the same reference.cnn file as before for all new samples (as always), or regenerate all your targetcoverage.cnn and antitargetcoverage.cnn files to build a new reference. Dependencies ------------ - pyvcf: No longer needed. Instead, parse VCFs with pysam, which is noticeably faster and better able to handle newer VCF and gVCF features. (#159) - pysam: Raise minimum version to 0.9.1.4. Global changes -------------- - When extracting a sample ID from a filename, instead of trimming everything after the first '.' character, only drop known or single-part extensions. For example, "Case1.exome.tumor.bam" and "Case1.exome.tumor.vcf.gz" will now resolve to the sample ID "Case1.exome.tumor" instead of "Case1". Output files will be named like "Case1.exome.tumor.cnr" instead of "Case1.cnr", avoiding potential naming conflicts in the `batch` command when processing multiple samples. (#48) - Always sort regions by genomic coordinates after reading a file. This doesn't modify the input file in-place, but ensures the output files are always sorted the same way. - Gender detection is more robust. It now uses Mood's median test instead of the Mann-Whitney rank test. As a fallback for edge cases, e.g. only one segment per chromosome, it compares difference of weighted medians in autosomes versus sex chromosomes. VCF parsing: - Improve handling of VCFs from Mutect2 (#122, #153) and bcftools (#146). - Don't reject records where FILTER is 'PASS' or '.'. - VCF options are now consistent across the commands that can use them (`call`, `scatter`, `segment`, `export theta` and `export nexus-ogt`). - New VCF option -z/--zygosity-freq to override VCF genotype calls. (#153, #132) Commands -------- target, antitarget: - Divide bins evenly, using the same internal mechanism (the new GenomicArray.subdivide() method). Previously, subdivided regions were not always equal-sized as they should have been. Now, the coordinates of newly generated targets from a baits BED file may be a little different than before. target: - Drop zero-width bins (#167). - Improve assignment of gene names to targets in WGS datasets. (#164) - Accept any supported region format for --annotate, including BED, interval list and GFF, in addition to the already supported UCSC refFlat. The format is detected automatically. (#163) - Raise an error if the given annotations file (refFlat or equivalent) and the given baited/targeted intervals do not have any overlapping chromosomes. antitarget: - Set the default average bin size to 150kb. Previously, the CLI default was 200kb, but the API default was 100kb; experience shows 150kb works well. access: - Avoid a possible error when more than 1000 small regions are excluded from a single sequencing-accessible region. (#150) coverage: - Fix a unicode vs. bytes incompatibility on Python 3. (#147) - Fix a crash if the input BED has more than 4 columns. reference: - Add -g/--gender option to declare the chromosomal sex of the input sample(s) (same for all), instead of detecting/guessing for each sample. (#161) - Ensure printed table of bad bins is a reasonable width. (#140) segment: - With a VCF (`-v`), don't output 'cn1' and 'cn2' columns; calculate the 'baf' column the same as in `call`. (#148) - Improve memory efficiency somewhat when using a VCF. (#162) - Fix possible 1-base overlap of output segments when using the `cbs` or `flasso` methods. Specifically, the start positions were erroneously all shifted 1 base to the left before. (#158) scatter, heatmap: - Improve rendering of genomes much smaller than the human genome, e.g. yeast, by scaling telomere padding to the total genome size. The blank space at chromosome boundaries was set to a fixed number of basepairs, but is now calculated as 0.3% of the whole genome size (sum of chromosome lengths) -- which works out the same for the human genome. (#155) scatter: - Add option `--segment-color`. Now you can choose 'red' if you like. metrics: - Input `-s`/`--segments` is now optional. If not given, compare bin log2 values to chromosome medians instead of segment means. import-theta, export theta: - Drop sex chromosomes, since THetA2 doesn't handle them well. (#103, #153) API changes ----------- tabio: - Read new formats: GFF (simply); UCSC genePred refFlat; sub-formats bed3, bed4 - Detect more formats with `tabio.read_auto`: BED, interval list, text coordinates (chr:start-end), refFlat, GFF, TSV with column names. - Remove module `ngfrills.regions`, no longer needed. GenomicArray: - Moved to new sub-package 'genome' - Rename method `select` to `filter` - Rename method `match_to_bins` to `into_ranges` and generalize. - New methods `flatten`, `merge`, `resize_ranges`, `subdivide`, `subtract` In general, the 'genome' functionality can be reached by using the `tabio` sub-package to load a GenomicArray instance and use its methods directly: from cnvlib import tabio regions = tabio.read_auto(filename) # Generate 500bp flanking regions regions.resize_ranges(500).merge().subtract(regions)
7b78a27
2016-12-15 05:50
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v0.8.1
Version 0.8.1 This is primarily a bugfix release. The [documentation](https://cnvkit.readthedocs.io/) is also improved, particularly covering the cnvlib API. API: - For convenience in scripting, the relevant functions for running each CLI command (`cnvlib.commands.do_*`) are exported to the top level. For example: `import cnvlib; cnvlib.do_batch(...)` Bug fixes: - `access`: Avoid a type-validation error on Python 3. (#141) - `batch`: Parallel processing now selects an appropriate number of workers for each step of the pipeline, reducing CPU contention when processing multiple samples in parallel. (#138) - `call`: Apply the `ci` and `sem` filters before calculating b-allele frequencies and absolute copy number, as these filters can alter the final calls. - `reference`: Safely handle an edge case in detecting gender from sample coverage depths when all bins have identical coverage depth, e.g. no coverage. (#144) - `segment`: Fix handling and segmentation of SNV allele frequencies from a VCF. Ensure output column ordering is correct. Avoid a crash that could occur when SNV segmentation produces a segment that does not cover any coverage bins. (chapmanb/bcbio-nextgen#1590) - tabio: Improve handling of empty files, including VCFs with no samples and/or no locus records. If records and samples are present but genotypes are missing or undetectable, `scatter`, `call` and `export` would previously reject all records when filtering for SNPs, but will now accept all records instead.
fb83f23
2016-10-12 02:50
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v0.8.0
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
ab9c400
2016-09-14 06:43
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v0.7.11
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.
ceeaa0f
2016-04-21 06:43
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