From f35d825630b80aa967b99802427d057a80675b21 Mon Sep 17 00:00:00 2001 From: sigven Date: Fri, 21 Apr 2017 00:59:09 +0200 Subject: [PATCH] automatic decomposition of multiallelics --- README.md | 36 +++++++------ docs/_build/doctrees/about.doctree | Bin 11844 -> 14940 bytes docs/_build/doctrees/environment.pickle | Bin 20720 -> 21471 bytes docs/_build/doctrees/getting_started.doctree | Bin 32753 -> 32753 bytes docs/_build/doctrees/output.doctree | Bin 156623 -> 152996 bytes docs/_build/html/_sources/about.rst.txt | 31 ++++++++--- .../html/_sources/getting_started.rst.txt | 16 +++--- docs/_build/html/_sources/output.rst.txt | 22 ++------ docs/_build/html/about.html | 35 +++++++++--- docs/_build/html/getting_started.html | 16 +++--- docs/_build/html/index.html | 1 + docs/_build/html/output.html | 18 ++----- docs/_build/html/searchindex.js | 2 +- docs/about.md | 15 +++++- docs/about.rst | 31 ++++++++--- docs/getting_started.md | 14 ++--- docs/getting_started.rst | 16 +++--- docs/output.md | 8 +-- docs/output.rst | 22 ++------ pcgr.py | 9 +++- src/Dockerfile | 51 ++++++++++-------- src/R/pcgrr2/.Rhistory | 14 ++--- src/pcgr.tgz | Bin 22217 -> 23691 bytes src/pcgr/lib/pcgrutils.py | 30 ++--------- src/pcgr/lib/utils.py | 48 ----------------- src/pcgr/pcgr_check_input.py | 46 ++++++++-------- 26 files changed, 230 insertions(+), 251 deletions(-) delete mode 100755 src/pcgr/lib/utils.py diff --git a/README.md b/README.md index 04121af6..c41f6a9f 100644 --- a/README.md +++ b/README.md @@ -2,20 +2,23 @@ ### Overview -The Personal Cancer Genome Reporter (PCGR) is a stand-alone software package intended for analysis and clinical interpretation of individual cancer genomes. It interprets both somatic SNVs/InDels and copy number aberrations. The software extends basic gene and variant annotations from the [Ensembl’s Variant Effect Predictor (VEP)](http://www.ensembl.org/info/docs/tools/vep/index.html) with oncology-relevant, up-to-date annotations retrieved flexibly through [vcfanno](https://github.com/brentp/vcfanno), and produces HTML reports that can be navigated by clinical oncologists (Figure 1). +The Personal Cancer Genome Reporter (PCGR) is a stand-alone software package for functional annotation and translation of individual cancer genomes for precision oncology. It interprets both somatic SNVs/InDels and copy number aberrations. The software extends basic gene and variant annotations from the [Ensembl’s Variant Effect Predictor (VEP)](http://www.ensembl.org/info/docs/tools/vep/index.html) with oncology-relevant, up-to-date annotations retrieved flexibly through [vcfanno](https://github.com/brentp/vcfanno), and produces interactive HTML reports intended for clinical interpretation (Figure 1). ![PCGR overview](PCGR_workflow.png) ### Example reports -* View an example report for a colorectal tumor sample (TCGA) -* View an example report for a breast tumor sample (TCGA) +* Report for a colorectal tumor sample (TCGA) +* Report for a breast tumor sample (TCGA) ### PCGR documentation [![Documentation Status](https://readthedocs.org/projects/pcgr/badge/?version=latest)](http://pcgr.readthedocs.io/en/latest/?badge=latest) +If you use PCGR, please cite our paper: -### Annotation resources included in PCGR (v0.3.2) +Sigve Nakken, Ghislain Fournous, Daniel Vodák, Lars Birger Aaasheim, and Eivind Hovig. __Personal Cancer Genome Reporter: Variant Interpretation Report For Precision Oncology__ (2017). bioRxiv. doi:[10.1101/122366](https://doi.org/10.1101/122366) + +### Annotation resources included in PCGR (v0.3.3) * [VEP v85](http://www.ensembl.org/info/docs/tools/vep/index.html) - Variant Effect Predictor release 85 (GENCODE v19 as the gene reference dataset) * [COSMIC v80](http://cancer.sanger.ac.uk/cosmic/) - Catalogue of somatic mutations in cancer (February 2017) @@ -53,16 +56,16 @@ A local installation of Python (it has been tested with [version 2.7.13](https:/ #### STEP 2: Download PCGR -April 19th 2017: New release (0.3.2) +April 20th 2017: New release (0.3.3) -1. Download and unpack the [latest release (0.3.2)](https://github.com/sigven/pcgr/releases/latest) +1. Download and unpack the [latest release (0.3.3)](https://github.com/sigven/pcgr/releases/latest) 2. Download and unpack the data bundle (approx. 17Gb) in the PCGR directory - * Download [the latest data bundle](https://drive.google.com/file/d/0B8aYD2TJ472mQjZOMmg4djZfT1k/) from Google Drive to `~/pcgr-X.X` (replace _X.X_ with the version number, e.g `~/pcgr-0.3.2`) + * Download [the latest data bundle](https://drive.google.com/file/d/0B8aYD2TJ472mQjZOMmg4djZfT1k/) from Google Drive to `~/pcgr-X.X` (replace _X.X_ with the version number, e.g `~/pcgr-0.3.3`) * Unpack the data bundle, e.g. through the following Unix command: `gzip -dc pcgr.databundle.GRCh37.YYYYMMDD.tgz | tar xvf -` A _data/_ folder within the _pcgr-X.X_ software folder should now have been produced -3. Pull the [PCGR Docker image (0.3.2)](https://hub.docker.com/r/sigven/pcgr/) from DockerHub (3.1Gb): - * `docker pull sigven/pcgr:0.3.2` (PCGR annotation engine) +3. Pull the [PCGR Docker image (0.3.3)](https://hub.docker.com/r/sigven/pcgr/) from DockerHub (3.2Gb): + * `docker pull sigven/pcgr:0.3.3` (PCGR annotation engine) #### STEP 3: Input preprocessing @@ -73,12 +76,9 @@ The PCGR workflow accepts two types of input files: PCGR can be run with either or both of the two input files present. -The following requirements __MUST__ be met by the input VCF for PCGR to work properly: +* We __strongly__ recommend that the input VCF is compressed and indexed using [bgzip](http://www.htslib.org/doc/tabix.html) and [tabix](http://www.htslib.org/doc/tabix.html) +* If the input VCF contains multi-allelic sites, these will be subject to [decomposition](http://genome.sph.umich.edu/wiki/Vt#Decompose) -1. Variants in the raw VCF that contain multiple alternative alleles (e.g. "multiple ALTs") must be split into variants with a single alternative allele. This can be done with the help of either [vt decompose](http://genome.sph.umich.edu/wiki/Vt#Decompose) or [vcflib's vcfbreakmulti](https://github.com/vcflib/vcflib#vcflib). We will add integrated support for this in an upcoming release -2. The contents of the VCF must be sorted correctly (i.e. according to chromosomal order and chromosomal position). This can be obtained by [vcftools](https://vcftools.github.io/perl_module.html#vcf-sort). - * We strongly recommend that the input VCF is compressed and indexed using [bgzip](http://www.htslib.org/doc/tabix.html) and [tabix](http://www.htslib.org/doc/tabix.html) - * 'chr' must be stripped from the chromosome names The tab-separated values file with copy number aberrations __MUST__ contain the following four columns: * Chromosome @@ -112,7 +112,7 @@ A tumor sample report is generated by calling the Python script __pcgr.py__ in t positional arguments: pcgr_dir PCGR base directory with accompanying data directory, - e.g. ~/pcgr-0.3.2 + e.g. ~/pcgr-0.3.3 output_dir Output directory sample_id Tumor sample/cancer genome identifier - prefix for output files @@ -146,7 +146,7 @@ A tumor sample report is generated by calling the Python script __pcgr.py__ in t The _examples_ folder contain sample files from TCGA. A report for a colorectal tumor case can be generated through the following command: -`python pcgr.py --input_vcf tumor_sample.COAD.vcf.gz --input_cna_segments tumor_sample.COAD.cna.tsv ~/pcgr-0.3.2 ~/pcgr-0.3.2/examples tumor_sample.COAD` +`python pcgr.py --input_vcf tumor_sample.COAD.vcf.gz --input_cna_segments tumor_sample.COAD.cna.tsv ~/pcgr-0.3.3 ~/pcgr-0.3.3/examples tumor_sample.COAD` This command will run the Docker-based PCGR workflow and produce the following output files in the _examples_ folder: @@ -157,3 +157,7 @@ This command will run the Docker-based PCGR workflow and produce the following o 5. __tumor_sample.COAD.pcgr.mutational_signatures.tsv__ - Tab-separated values file with estimated contributions by known mutational signatures and associated underlying etiologies 6. __tumor_sample.COAD.pcgr.snvs_indels.biomarkers.tsv__ - Tab-separated values file with clinical evidence items associated with biomarkers for diagnosis, prognosis or drug sensitivity/resistance 7. __tumor_sample.COAD.pcgr.cna_segments.tsv.gz__ - Tab-separated values file with annotations of gene transcripts that overlap with somatic copy number aberrations + +## Contact + +sigven@ifi.uio.no diff --git a/docs/_build/doctrees/about.doctree b/docs/_build/doctrees/about.doctree index 05efd90df3848c9bbce3d1f4203c6cada0250b0d..d23ecbb614c8dbfb88923f84e0263cbaca5914fd 100644 GIT binary patch literal 14940 zcmeHO37i~NnIDqO)k!7?B;g8H2uRP6p3ZOtGTela#J~_kDh$flsqU`ss+sDle&4H_ z11(KdG{IZE@CHvr#S;Z@@IcXB_jd1H-Fw%)++Fu@SO4F8Roy+)Ge81yfBt^?{gUab zSMPo2`@Z+R?|tv!qEb01MWO4-K|d(lGQ+Pm+YdA1r2a!M%UpLv`*NR zD_YVn8=+lt{J;yUGh*pTWUi7?QHE{^-U7c+wkuLBi^X!YuWpgF3pHCxs|tqt#>5J< zuM`o1>4FR*D%oP?h?yzdrGP9REmn<~tF0&uDnStXL1-6bXi+Fu?>@=wX3@B1DNc^X zDOsn>Tn4%1AeS6dF4j2RW~Ua)TBpZck%%Ohie#PBYi^!$tT5-w90Za}1(MSO$!UQk z{lTk(da9E#yHi=5<}5YWwMrt_B8k%@v!~>^UK!kpGseW3bJZ>F60?{Q>!IzlV(~0! zo2;os4u;ubc0phejo9EUGP{!Yvqy&@{=6xnzPxm+leV8HTiO`ritbIptuhU6Bb5DIyAEY8cCJ>{s*{iMi_fmhFx63_i(W>3*7 zO%SVdV9Z?1l0Sb;Y;x9GW~c6-8xw<0w-uR7JlD5He)l2(OD470>@0F1hN0|SIbf!E zc1BzPDO?zfi?WWP=JPdbK40u?aL#hhb~ZZan4PMp*y4cBOR`RO%;_I<2F9H8$DG_) zfeP@dP+N{IeY>UNp%ne)KEtqJj8Pc7wkg zVsRt$=Pv5#*awgD)c9g4SO(14FXt>T@NGi|m2e6(JyXa0f@d%)0U4FZSLOi+W%;mt zUg#=J?1piV(KDq(F?0>}E{PTI!KeK+2au1rc3AQ=du^b-7rTY@GV`q666 zUhh^TOpu}e!KO`^y^Z-OM%X-Wn$JACQ={CIg?$X2bYiL=^;8wlg?HE+i<{ZlPe||> zj2)BqhNw8#onk4qVK*f#e*54~%~LYT+=;*~5cuWq87j7)ydL8E#98%&C;Z_*xQ>8|GNbx+((C5eEHpovc+a}g8L=3$R z5sNV_?psH9gVtxzCyEyUZy^>3SZ~iTY&~Zjo*7mwii{!8GvnyoFsrzfs+i;WWVkar zx*^fq6T0$+bX0~gTfhk$f~drznkoRX6cpfSsgDBF@mddr1I%tL##une6Oq=3-EPJe zy*7ynXv&L4Efql$x|vNNuCVWUI!_4E920 zm%{`preZN|o;2W0N<^OKVxVAgcOdc|fz|5pnZv@FSlrH({sbSNN?7Pvh@5QOH_8Y+ zyr7O)pg3d5l8cbSl_3JLO2zeD&`?&UtHY;}fTrv!;wz&yigrsfvn}u?Hob0CYXnYu zN2lUK^uTsIiBLifYnQLLt2*-3@G^VTP1Q}(3k=goB?K^jf%!^NG7uF2BWHU(Pex!OvBdR~2A28BE!ik1l`UJlvb5sO!V zSGDdOY;}9Rzz(;kCz*I9x*m?j5f;m=FD+ubGZwGn?>Dm8p2=Cs0(^BUz%772A8_MI zr#wWuvMJKWykAI^uYo8RLiXhLC0+}Oy)G87PlbDDt8fv>cMPJ#8)ETB7MXh2qJ)oD z`}n(J@uqZax{p@-_&3ioN%0nEo!ZC0)#*|D_%l-De4F0K-yMs$GYU?uZJ(1^dk0Y7 z)w)N2=PcOC9=!qaU69CpVBQT*-V=-W0*%8U?^f<~?s8C!JkJgb9=u{k+ygVaHx}

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zOCHGvR8g>i`pY1OIfJhc%H=2Krp%dylspn+ISOaPygIbDr`ZL$+~a2f3d{R3w@Lc|RW?lZWD4=P4^z<;(^A^C%nvP^0)`Oy{WB zPtXS?4@PjnWO2%@5lHbI(!IHe6Ba7Q4Cw7K*>WXwbvlm&8OmvFWRYvFY6kJ~$;so; z)M?)wG{h)f#qxFD3?b9?$pi8;o6TAQvkjlE=I3%~<#gGs)9WKKrbDy=;=0iU?2@UP z3-$hJQjeWpv4)0P5)KRIVb#hUW)w6DSDTBJc?tC)AjlW%?GY^;Gwbm>dC**Kvhyqx z=X1n?q85!OzU zjM?@}9*1Koc$Hn=SmL9VG-PRBp))sY63BHu)G{-X-crof3T7NHEKNrOmR^D{*x|;dFbOWrtRT=8{K4zwBA~=zG()%P$ML zY5c-#c@dqnGeQ*386B7a8z=R{p@9Qea!Dk)$m_zYrh=?jnpylN52hlZvDe^_x-s}g H+|&O7U@fe^ diff --git a/docs/_build/html/_sources/about.rst.txt b/docs/_build/html/_sources/about.rst.txt index 9a1ab9eb..7f1232e7 100644 --- a/docs/_build/html/_sources/about.rst.txt +++ b/docs/_build/html/_sources/about.rst.txt @@ -5,14 +5,15 @@ What is the Personal Cancer Genome Reporter (PCGR)? ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ The Personal Cancer Genome Reporter (PCGR) is a stand-alone software -package intended for analysis and clinical interpretation of individual -cancer genomes. It interprets both somatic SNVs/InDels and copy number -aberrations. The software extends basic gene and variant annotations -from the `Ensembl’s Variant Effect Predictor +package for functional annotation and translation of individual cancer +genomes for precision oncology. It interprets both somatic SNVs/InDels +and copy number aberrations. The software extends basic gene and variant +annotations from the `Ensembl’s Variant Effect Predictor (VEP) `__ with oncology-relevant, up-to-date annotations retrieved flexibly through -`vcfanno `__, and produces HTML -reports that can be navigated by clinical oncologists (Figure 1). +`vcfanno `__, and produces +interactive HTML reports intended for clinical interpretation (Figure +1). .. figure:: PCGR_workflow.png :alt: @@ -22,6 +23,12 @@ affiliated with the `Norwegian Cancer Genomics Consortium `__, at the `Institute for Cancer Research/Oslo University Hospital `__. +Example reports +^^^^^^^^^^^^^^^ + +- Report for a colorectal tumor sample (TCGA) +- Report for a breast tumor sample (TCGA) + Why use PCGR? ~~~~~~~~~~~~~ @@ -37,6 +44,13 @@ and variant level. The application generates a tiered report that will aid the interpretation of individual cancer genomes in a clinical setting. +If you use PCGR, please cite our paper: + +Sigve Nakken, Ghislain Fournous, Daniel Vodák, Lars Birger Aaasheim, and +Eivind Hovig. **Personal Cancer Genome Reporter: Variant Interpretation +Report For Precision Oncology** (2017). bioRxiv. +doi:\ `10.1101/122366 `__ + Docker-based technology ~~~~~~~~~~~~~~~~~~~~~~~ @@ -50,3 +64,8 @@ for precision oncology `__. .. figure:: docker-logo50.png :alt: + +Contact +~~~~~~~ + +sigven@ifi.uio.no diff --git a/docs/_build/html/_sources/getting_started.rst.txt b/docs/_build/html/_sources/getting_started.rst.txt index cce4c2d5..762972a8 100644 --- a/docs/_build/html/_sources/getting_started.rst.txt +++ b/docs/_build/html/_sources/getting_started.rst.txt @@ -42,10 +42,10 @@ terminal window. Download PCGR ^^^^^^^^^^^^^ -**April 19th 2017**: New release (0.3.2) +**April 20th 2017**: New release (0.3.3) - Download and unpack the `latest release - (0.3.2) `__ + (0.3.3) `__ - Download and unpack the data bundle (approx. 17Gb) in the PCGR directory @@ -53,7 +53,7 @@ Download PCGR - Download `the latest data bundle `__ from Google Drive to ``~/pcgr-X.X`` (replace *X.X* with the - version number, e.g. ``~/pcgr-0.3.2``) + version number, e.g. ``~/pcgr-0.3.3``) - Decompress and untar the bundle, e.g. through the following Unix command: ``gzip -dc pcgr.databundle.GRCh37.YYYYMMDD.tgz | tar xvf -`` @@ -62,10 +62,10 @@ Download PCGR have been produced - Pull the `PCGR Docker image - - 0.3.2 `__ from DockerHub - (3.1Gb) : + 0.3.3 `__ from DockerHub + (3.2Gb) : - - ``docker pull sigven/pcgr:0.3.2`` (PCGR annotation engine) + - ``docker pull sigven/pcgr:0.3.3`` (PCGR annotation engine) Run test - generation of clinical report for a cancer genome ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -89,7 +89,7 @@ A tumor sample report is generated by calling the Python script positional arguments: pcgr_dir PCGR base directory with accompanying data directory, - e.g. ~/pcgr-0.3.2 + e.g. ~/pcgr-0.3.3 output_dir Output directory sample_id Tumor sample/cancer genome identifier - prefix for output files @@ -125,7 +125,7 @@ sequenced within TCGA. A report for a colorectal tumor case can be generated by running the following command in your terminal window: ``python pcgr.py --input_vcf examples/tumor_sample.COAD.vcf.gz --input_cna_segments`` -``examples/tumor_sample.COAD.cna.tsv ~/pcgr-0.3.2 ~/pcgr-0.3.2/examples tumor_sample.COAD`` +``examples/tumor_sample.COAD.cna.tsv ~/pcgr-0.3.3 ~/pcgr-0.3.3/examples tumor_sample.COAD`` This command will run the Docker-based PCGR workflow and produce the following output files in the *examples* folder: diff --git a/docs/_build/html/_sources/output.rst.txt b/docs/_build/html/_sources/output.rst.txt index e59a1c9d..5ad23bcd 100644 --- a/docs/_build/html/_sources/output.rst.txt +++ b/docs/_build/html/_sources/output.rst.txt @@ -18,23 +18,11 @@ currently supported. VCF ^^^ -The following requirements **MUST** be met by the input VCF for PCGR to -work properly: - -1. Variants in the raw VCF that contain multiple alternative alleles - (e.g. "multiple ALTs") must be split into variants with a single - alternative allele. This can be done with the help of either `vt - decompose `__ or - `vcflib's vcfbreakmulti `__. - We will add integrated support for this in an upcoming release -2. The contents of the VCF must be sorted correctly (i.e. according to - chromosomal order and chromosomal position). This can be obtained by - `vcftools `__. - - - We **strongly** recommend that the input VCF is compressed and - indexed using `bgzip `__ and - `tabix `__ - - 'chr' must be stripped from the chromosome names +- We **strongly** recommend that the input VCF is compressed and + indexed using `bgzip `__ and + `tabix `__ +- If the input VCF contains multi-allelic sites, these will be subject + to `decomposition `__ **IMPORTANT NOTE 1**: Considering the VCF output for the `numerous somatic SNV/InDel callers `__ that diff --git a/docs/_build/html/about.html b/docs/_build/html/about.html index 45ef2300..635de714 100644 --- a/docs/_build/html/about.html +++ b/docs/_build/html/about.html @@ -89,9 +89,13 @@

Table of Contents

  • Getting started