Merge pull request #244 from ENCODE-DCC/dev

v2.0.1
ENCODE-DCC · Nov 4, 2021 · 796317e · 796317e
2 parents 43c10a6 + 769ca5a
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diff --git a/.circleci/config.yml b/.circleci/config.yml
@@ -31,12 +31,20 @@ commands:
     steps:      
       - run:
           command: |
-            sudo apt-get update && sudo apt-get install software-properties-common git wget curl default-jre -y
+            sudo apt-get update && sudo apt-get install software-properties-common git wget curl -y
+
+            # install java 11
+            sudo add-apt-repository ppa:openjdk-r/ppa -y
+            sudo apt-get update && sudo apt-get install openjdk-11-jdk -y
+            # automatically set 11 as default java
+            sudo update-java-alternatives -a
+
             sudo add-apt-repository ppa:deadsnakes/ppa -y
             sudo apt-get update && sudo apt-get install python3.6 -y
             sudo wget --no-check-certificate https://bootstrap.pypa.io/get-pip.py
             sudo python3.6 get-pip.py
             sudo ln -s /usr/bin/python3.6 /usr/local/bin/python3
+
             pip3 install --upgrade pip
             pip3 install caper google-cloud-storage
 
@@ -51,11 +59,17 @@ commands:
 
             echo ${GCLOUD_SERVICE_ACCOUNT_SECRET_JSON} > tmp_secret_key.json
             export GOOGLE_APPLICATION_CREDENTIALS=$PWD/tmp_secret_key.json
+
+            # add docker image to input JSON
+            cat ${INPUT} | jq ".+{\"chip.docker\": \"${TAG}\"}" > input_with_docker.json
+
             caper run ../../../chip.wdl \
               --backend gcp --gcp-prj ${GOOGLE_PROJECT_ID} \
               --gcp-service-account-key-json $PWD/tmp_secret_key.json \
               --out-gcs-bucket ${CAPER_OUT_DIR} --tmp-gcs-bucket ${CAPER_TMP_DIR} \
-              -i ${INPUT} -m metadata.json --docker ${TAG}
+              -i input_with_docker.json -m metadata.json --docker ${TAG}
+
+            rm -f input_with_docker.json
 
             res=$(jq '.outputs["chip.qc_json_ref_match"]' metadata.json)
             [[ "$res" != true ]] && exit 100

diff --git a/README.md b/README.md
@@ -5,11 +5,33 @@
 
 ## Download new Caper>=2.0
 
-New Caper is out. You need to update your Caper to work with the latest ENCODE ATAC-seq pipeline.
+New Caper is out. You need to update your Caper to work with the latest ENCODE ChIP-seq pipeline.
 ```bash
 $ pip install caper --upgrade
 ```
 
+## Local/HPC users and new Caper>=2.0
+
+There are tons of changes for local/HPC backends: `local`, `slurm`, `sge`, `pbs` and `lsf`(added). Make a backup of your current Caper configuration file `~/.caper/default.conf` and run `caper init`. Local/HPC users need to reset/initialize Caper's configuration file according to your chosen backend. Edit the configuration file and follow instructions in there.
+```bash
+$ cd ~/.caper
+$ cp default.conf default.conf.bak
+$ caper init [YOUR_BACKEND]
+```
+
+In order to run a pipeline, you need to add one of the following flags to specify the environment to run each task within. i.e. `--conda`, `--singularity` and `--docker`. These flags are not required for cloud backend users (`aws` and `gcp`).
+```bash
+# for example
+$ caper run ... --singularity
+```
+
+For Conda users, **RE-INSTALL PIPELINE'S CONDA ENVIRONMENT AND DO NOT ACTIVATE CONDA ENVIRONMENT BEFORE RUNNING PIPELINES**. Caper will internally call `conda run -n ENV_NAME CROMWELL_JOB_SCRIPT`. Just make sure that pipeline's new Conda environments are correctly installed.
+```bash
+$ scripts/uninstall_conda_env.sh
+$ scripts/install_conda_env.sh
+```
+
+
 ## Introduction 
 This ChIP-Seq pipeline is based off the ENCODE (phase-3) transcription factor and histone ChIP-seq pipeline specifications (by Anshul Kundaje) in [this google doc](https://docs.google.com/document/d/1lG_Rd7fnYgRpSIqrIfuVlAz2dW1VaSQThzk836Db99c/edit#).
 
@@ -21,34 +43,35 @@ This ChIP-Seq pipeline is based off the ENCODE (phase-3) transcription factor an
 
 ## Installation
 
-
 1) Make sure that you have Python>=3.6. Caper does not work with Python2. Install Caper and check its version >=2.0.
 	```bash
 	$ python --version
 	$ pip install caper
-	$ caper -v
 	```
+2) Make a backup of your Caper configuration file `~/.caper/default.conf` if you are upgrading from old Caper(<2.0.0). Reset/initialize Caper's configuration file. Read Caper's [README](https://github.com/ENCODE-DCC/caper/blob/master/README.md) carefully to choose a backend for your system. Follow the instruction in the configuration file.
+	```bash
+	# make a backup of ~/.caper/default.conf if you already have it
+	$ caper init [YOUR_BACKEND]
 
-2) Git clone this pipeline.
-	> **IMPORTANT**: use `~/chip-seq-pipeline2/chip.wdl` as `[WDL]` in Caper's documentation.
+	# then edit ~/.caper/default.conf
+	$ vi ~/.caper/default.conf
+	```
 
+3) Git clone this pipeline.
+	> **IMPORTANT**: use `~/chip-seq-pipeline2/chip.wdl` as `[WDL]` in Caper's documentation.
 	```bash
 	$ cd
 	$ git clone https://github.com/ENCODE-DCC/chip-seq-pipeline2
 	```
 
-
-3) (Optional for Conda) Install pipeline's Conda environments if you don't have Singularity or Docker installed on your system. We recommend to use Singularity instead of Conda. If you don't have Conda on your system, install [Miniconda3](https://docs.conda.io/en/latest/miniconda.html).
+4) (Optional for Conda) Install pipeline's Conda environments if you don't have Singularity or Docker installed on your system. We recommend to use Singularity instead of Conda. If you don't have Conda on your system, install [Miniconda3](https://docs.conda.io/en/latest/miniconda.html).
 	```bash
 	$ cd chip-seq-pipeline2
+	# uninstall old environments (<2.0.0)
+	$ bash scripts/uninstall_conda_env.sh
 	$ bash scripts/install_conda_env.sh
 	```
 
-4) Follow [Caper's README](https://github.com/ENCODE-DCC/caper) carefully. Find an instruction for your platform and run `caper init`. Edit the initialized Caper's configuration file (`~/.caper/default.conf`).
-	```bash
-	$ caper init [YOUR_PLATFORM]
-	$ vi ~/.caper/default.conf
-	```
 
 ## Test run
 
@@ -63,10 +86,35 @@ The followings are just examples. Please read [Caper's README](https://github.co
 
     # Or submit it as a leader job (with long/enough resources) to SLURM (Stanford Sherlock) with Singularity
     # It will fail if you directly run the leader job on login nodes
-    $ sbatch -p [SLURM_PARTITON] -J [WORKFLOW_NAME] --export=ALL --mem 4G -t 4-0 --wrap "caper chip atac.wdl -i https://storage.googleapis.com/encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR000DYI_subsampled_chr19_only.json --singularity"
+    $ sbatch -p [SLURM_PARTITON] -J [WORKFLOW_NAME] --export=ALL --mem 4G -t 4-0 --wrap "caper chip chip.wdl -i https://storage.googleapis.com/encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR000DYI_subsampled_chr19_only.json --singularity"
 	```
 
 
+## Running a pipeline on Terra/Anvil (using Dockstore)
+
+Visit our pipeline repo on [Dockstore](https://dockstore.org/workflows/github.com/ENCODE-DCC/chip-seq-pipeline2). Click on `Terra` or `Anvil`. Follow Terra's instruction to create a workspace on Terra and add Terra's billing bot to your Google Cloud account.
+
+Download this [test input JSON for Terra](https://storage.googleapis.com/encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR000DYI_subsampled_chr19_only.terra.json) and upload it to Terra's UI and then run analysis.
+
+If you want to use your own input JSON file, then make sure that all files in the input JSON are on a Google Cloud Storage bucket (`gs://`). URLs will not work.
+
+
+## Running a pipeline on DNAnexus (using Dockstore)
+
+Sign up for a new account on [DNAnexus](https://platform.dnanexus.com/) and create a new project on either AWS or Azure. Visit our pipeline repo on [Dockstore](https://dockstore.org/workflows/github.com/ENCODE-DCC/chip-seq-pipeline2). Click on `DNAnexus`. Choose a destination directory on your DNAnexus project. Click on `Submit` and visit DNAnexus. This will submit a conversion job so that you can check status of it on `Monitor` on DNAnexus UI.
+
+Once conversion is done download one of the following input JSON files according to your chosen platform (AWS or Azure) for your DNAnexus project:
+- AWS: https://storage.googleapis.com/encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR000DYI_subsampled_chr19_only_dx.json
+- Azure: https://storage.googleapis.com/encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR000DYI_subsampled_chr19_only_dx_azure.json
+
+You cannot use these input JSON files directly. Go to the destination directory on DNAnexus and click on the converted workflow `chip`. You will see input file boxes in the left-hand side of the task graph. Expand it and define FASTQs (`fastq_repX_R1`) and `genome_tsv` as in the downloaded input JSON file. Click on the `common` task box and define other non-file pipeline parameters.
+
+
+## Running a pipeline on DNAnexus (using our pre-built workflows)
+
+See [this](docs/tutorial_dx_web.md) for details.
+
+
 
 ## Input JSON file
 
@@ -82,13 +130,6 @@ You can run this pipeline on [truwl.com](https://truwl.com/). This provides a we
 
 If you do not run the pipeline on Truwl, you can still share your use-case/job on the platform by getting in touch at [[email protected]](mailto:[email protected]) and providing your inputs.json file.
 
-## Running a pipeline on DNAnexus
-
-You can also run this pipeline on DNAnexus without using Caper or Cromwell. There are two ways to build a workflow on DNAnexus based on our WDL.
-
-1) [dxWDL CLI](docs/tutorial_dx_cli.md)
-2) [DNAnexus Web UI](docs/tutorial_dx_web.md)
-
 ## How to organize outputs
 
 Install [Croo](https://github.com/ENCODE-DCC/croo#installation). **You can skip this installation if you have installed pipeline's Conda environment and activated it**. Make sure that you have python3(> 3.4.1) installed on your system. Find a `metadata.json` on Caper's output directory.

diff --git a/chip.wdl b/chip.wdl
@@ -7,16 +7,20 @@ struct RuntimeEnvironment {
 }
 
 workflow chip {
-    String pipeline_ver = 'v2.0.0'
+    String pipeline_ver = 'v2.0.1'
 
     meta {
-        version: 'v2.0.0'
-        author: 'Jin wook Lee ([email protected]) at ENCODE-DCC'
-        description: 'ENCODE TF/Histone ChIP-Seq pipeline'
+        version: 'v2.0.1'
+
+        author: 'Jin wook Lee'
+        email: '[email protected]'
+        description: 'ENCODE TF/Histone ChIP-Seq pipeline. See https://github.com/ENCODE-DCC/chip-seq-pipeline2 for more details. e.g. example input JSON for Terra/Anvil.'
+        organization: 'ENCODE DCC'
+
         specification_document: 'https://docs.google.com/document/d/1lG_Rd7fnYgRpSIqrIfuVlAz2dW1VaSQThzk836Db99c/edit?usp=sharing'
 
-        default_docker: 'encodedcc/chip-seq-pipeline:v2.0.0'
-        default_singularity: 'library://leepc12/default/chip-seq-pipeline:v2.0.0'
+        default_docker: 'encodedcc/chip-seq-pipeline:v2.0.1'
+        default_singularity: 'library://leepc12/default/chip-seq-pipeline:v2.0.1'
         croo_out_def: 'https://storage.googleapis.com/encode-pipeline-output-definition/chip.croo.v5.json'
 
         parameter_group: {
@@ -67,8 +71,8 @@ workflow chip {
     }
     input {
         # group: runtime_environment
-        String docker = 'encodedcc/chip-seq-pipeline:v2.0.0'
-        String singularity = 'library://leepc12/default/chip-seq-pipeline:v2.0.0'
+        String docker = 'encodedcc/chip-seq-pipeline:v2.0.1'
+        String singularity = 'library://leepc12/default/chip-seq-pipeline:v2.0.1'
         String conda = 'encode-chip-seq-pipeline'
         String conda_macs2 = 'encode-chip-seq-pipeline-macs2'
         String conda_spp = 'encode-chip-seq-pipeline-spp'
@@ -117,9 +121,9 @@ workflow chip {
         Array[File] bams = []
         Array[File] nodup_bams = []
         Array[File] tas = []
-        Array[File?] peaks = []
-        Array[File?] peaks_pr1 = []
-        Array[File?] peaks_pr2 = []
+        Array[File] peaks = []
+        Array[File] peaks_pr1 = []
+        Array[File] peaks_pr2 = []
         File? peak_ppr1
         File? peak_ppr2
         File? peak_pooled
@@ -1703,7 +1707,7 @@ workflow chip {
     # we have all tas and ctl_tas (optional for histone chipseq) ready, let's call peaks
     scatter(i in range(num_rep)) {
         Boolean has_input_of_call_peak = defined(ta_[i])
-        Boolean has_output_of_call_peak = i<length(peaks) && defined(peaks[i])
+        Boolean has_output_of_call_peak = i<length(peaks)
         if ( has_input_of_call_peak && !has_output_of_call_peak && !align_only_ ) {
             call call_peak { input :
                 peak_caller = peak_caller_,
@@ -1748,7 +1752,7 @@ workflow chip {
 
         # call peaks on 1st pseudo replicated tagalign
         Boolean has_input_of_call_peak_pr1 = defined(spr.ta_pr1[i])
-        Boolean has_output_of_call_peak_pr1 = i<length(peaks_pr1) && defined(peaks_pr1[i])
+        Boolean has_output_of_call_peak_pr1 = i<length(peaks_pr1)
         if ( has_input_of_call_peak_pr1 && !has_output_of_call_peak_pr1 && !true_rep_only ) {
             call call_peak as call_peak_pr1 { input :
                 peak_caller = peak_caller_,
@@ -1777,7 +1781,7 @@ workflow chip {
 
         # call peaks on 2nd pseudo replicated tagalign
         Boolean has_input_of_call_peak_pr2 = defined(spr.ta_pr2[i])
-        Boolean has_output_of_call_peak_pr2 = i<length(peaks_pr2) && defined(peaks_pr2[i])
+        Boolean has_output_of_call_peak_pr2 = i<length(peaks_pr2)
         if ( has_input_of_call_peak_pr2 && !has_output_of_call_peak_pr2 && !true_rep_only ) {
             call call_peak as call_peak_pr2 { input :
                 peak_caller = peak_caller_,
@@ -2061,7 +2065,7 @@ workflow chip {
         call reproducibility as reproducibility_overlap { input :
             prefix = 'overlap',
             peaks = select_all(overlap.bfilt_overlap_peak),
-            peaks_pr = overlap_pr.bfilt_overlap_peak,
+            peaks_pr = if defined(overlap_pr.bfilt_overlap_peak) then select_first([overlap_pr.bfilt_overlap_peak]) else [],
             peak_ppr = overlap_ppr.bfilt_overlap_peak,
             peak_type = peak_type_,
             chrsz = chrsz_,
@@ -2074,7 +2078,7 @@ workflow chip {
         call reproducibility as reproducibility_idr { input :
             prefix = 'idr',
             peaks = select_all(idr.bfilt_idr_peak),
-            peaks_pr = idr_pr.bfilt_idr_peak,
+            peaks_pr = if defined(idr_pr.bfilt_idr_peak) then select_first([idr_pr.bfilt_idr_peak]) else [],
             peak_ppr = idr_ppr.bfilt_idr_peak,
             peak_type = peak_type_,
             chrsz = chrsz_,
@@ -2112,7 +2116,7 @@ workflow chip {
         ctl_lib_complexity_qcs = select_all(filter_ctl.lib_complexity_qc),
 
         jsd_plot = jsd.plot,
-        jsd_qcs = jsd.jsd_qcs,
+        jsd_qcs = if defined(jsd.jsd_qcs) then select_first([jsd.jsd_qcs]) else [],
 
         frip_qcs = select_all(call_peak.frip_qc),
         frip_qcs_pr1 = select_all(call_peak_pr1.frip_qc),
@@ -2122,13 +2126,13 @@ workflow chip {
         frip_qc_ppr2 = call_peak_ppr2.frip_qc,
 
         idr_plots = select_all(idr.idr_plot),
-        idr_plots_pr = idr_pr.idr_plot,
+        idr_plots_pr = if defined(idr_pr.idr_plot) then select_first([idr_pr.idr_plot]) else [],
         idr_plot_ppr = idr_ppr.idr_plot,
         frip_idr_qcs = select_all(idr.frip_qc),
-        frip_idr_qcs_pr = idr_pr.frip_qc,
+        frip_idr_qcs_pr = if defined(idr_pr.frip_qc) then select_first([idr_pr.frip_qc]) else [],
         frip_idr_qc_ppr = idr_ppr.frip_qc,
         frip_overlap_qcs = select_all(overlap.frip_qc),
-        frip_overlap_qcs_pr = overlap_pr.frip_qc,
+        frip_overlap_qcs_pr = if defined(overlap_pr.frip_qc) then select_first([overlap_pr.frip_qc]) else [],
         frip_overlap_qc_ppr = overlap_ppr.frip_qc,
         idr_reproducibility_qc = reproducibility_idr.reproducibility_qc,
         overlap_reproducibility_qc = reproducibility_overlap.reproducibility_qc,
@@ -2945,7 +2949,7 @@ task reproducibility {
                             # in a sorted order. for example of 4 replicates,
                             # 1,2 1,3 1,4 2,3 2,4 3,4.
                             # x,y means peak file from rep-x vs rep-y
-        Array[File]? peaks_pr    # peak files from pseudo replicates
+        Array[File] peaks_pr    # peak files from pseudo replicates
         File? peak_ppr            # Peak file from pooled pseudo replicate.
         String peak_type
         File chrsz            # 2-col chromosome sizes file
@@ -3060,9 +3064,9 @@ task qc_report {
         Array[File] xcor_plots
         Array[File] xcor_scores
         File? jsd_plot
-        Array[File]? jsd_qcs
+        Array[File] jsd_qcs
         Array[File] idr_plots
-        Array[File]? idr_plots_pr
+        Array[File] idr_plots_pr
         File? idr_plot_ppr
         Array[File] frip_qcs
         Array[File] frip_qcs_pr1
@@ -3071,10 +3075,10 @@ task qc_report {
         File? frip_qc_ppr1 
         File? frip_qc_ppr2 
         Array[File] frip_idr_qcs
-        Array[File]? frip_idr_qcs_pr
+        Array[File] frip_idr_qcs_pr
         File? frip_idr_qc_ppr 
         Array[File] frip_overlap_qcs
-        Array[File]? frip_overlap_qcs_pr
+        Array[File] frip_overlap_qcs_pr
         File? frip_overlap_qc_ppr
         File? idr_reproducibility_qc
         File? overlap_reproducibility_qc

diff --git a/example_input_json/terra/ENCSR000DYI_subsampled_chr19_only.terra.json b/example_input_json/terra/ENCSR000DYI_subsampled_chr19_only.terra.json
@@ -0,0 +1,15 @@
+{
+    "chip.pipeline_type" : "tf",
+    "chip.genome_tsv" : "gs://encode-pipeline-genome-data/genome_tsv/v3/hg38_chr19_chrM.terra.tsv",
+    "chip.fastqs_rep1_R1" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR000DYI/fastq_subsampled/rep1.subsampled.25.fastq.gz"
+    ],
+    "chip.fastqs_rep2_R1" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR000DYI/fastq_subsampled/rep2.subsampled.20.fastq.gz"
+    ],
+    "chip.ctl_fastqs_rep1_R1" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR000DYI/fastq_subsampled/ctl1.subsampled.25.fastq.gz"
+    ],
+    "chip.ctl_fastqs_rep2_R1" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR000DYI/fastq_subsampled/ctl2.subsampled.25.fastq.gz"
+    ],
+    "chip.paired_end" : false,
+    "chip.title" : "ENCSR000DYI (subsampled 1/25, chr19_chrM only)",
+    "chip.description" : "CEBPB ChIP-seq on human A549 produced by the Snyder lab"
+}
diff --git a/example_input_json/terra/ENCSR936XTK_subsampled_chr19_only.terra.json b/example_input_json/terra/ENCSR936XTK_subsampled_chr19_only.terra.json
@@ -0,0 +1,23 @@
+{
+    "chip.pipeline_type" : "tf",
+    "chip.genome_tsv" : "gs://encode-pipeline-genome-data/genome_tsv/v3/hg38_chr19_chrM.terra.tsv",
+    "chip.fastqs_rep1_R1" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR936XTK/fastq_subsampled/rep1-R1.subsampled.50.fastq.gz"
+    ],
+    "chip.fastqs_rep1_R2" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR936XTK/fastq_subsampled/rep1-R2.subsampled.50.fastq.gz"
+    ],
+    "chip.fastqs_rep2_R1" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR936XTK/fastq_subsampled/rep2-R1.subsampled.50.fastq.gz"
+    ],
+    "chip.fastqs_rep2_R2" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR936XTK/fastq_subsampled/rep2-R2.subsampled.50.fastq.gz"
+    ],
+    "chip.ctl_fastqs_rep1_R1" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR936XTK/fastq_subsampled/ctl1-R1.subsampled.80.fastq.gz"
+    ],
+    "chip.ctl_fastqs_rep1_R2" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR936XTK/fastq_subsampled/ctl1-R2.subsampled.80.fastq.gz"
+    ],
+    "chip.ctl_fastqs_rep2_R1" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR936XTK/fastq_subsampled/ctl2-R1.subsampled.80.fastq.gz"
+    ],
+    "chip.ctl_fastqs_rep2_R2" : ["gs://encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR936XTK/fastq_subsampled/ctl2-R2.subsampled.80.fastq.gz"
+    ],
+    "chip.paired_end" : true,
+    "chip.title" : "ENCSR936XTK (subsampled 1/50, chr19 and chrM Only)",
+    "chip.description" : "ZNF143 ChIP-seq on human GM12878"
+}