Merge pull request #56 from ENCODE-DCC/PIP-489_v1.1.7

Pip 489 v1.1.7
ENCODE-DCC · Apr 19, 2019 · 2f567e6 · 2f567e6
2 parents 9563c12 + 26d2143
commit 2f567e6
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Showing 39 changed files with 314 additions and 105 deletions.
diff --git a/.gitignore b/.gitignore
@@ -116,3 +116,6 @@ test_sample*
 tmp
 hg38
 *.fastq.gz
+
+metadata.json
+resume.*.json
diff --git a/backends/backend.conf b/backends/backend.conf
@@ -1,7 +1,7 @@
 include required(classpath("application"))
 
 backend {
-  default = "local"
+  default = "Local"
   providers {
 
     pbs {
@@ -214,13 +214,6 @@ backend {
       }
     }
 
-    local {
-      actor-factory = "cromwell.backend.impl.sfs.config.ConfigBackendLifecycleActorFactory"
-      config {
-        concurrent-job-limit = 10
-      }
-    }
-
     sge {
       actor-factory = "cromwell.backend.impl.sfs.config.ConfigBackendLifecycleActorFactory"
       config {

diff --git a/chip.wdl b/chip.wdl
@@ -2,7 +2,7 @@
 # Author: Jin Lee (leepc12@gmail.com)
 
 workflow chip {
-	String pipeline_ver = 'v1.1.6.1'
+	String pipeline_ver = 'v1.1.7'
 	### sample name, description
 	String title = 'Untitled'
 	String description = 'No description'
@@ -21,8 +21,13 @@ workflow chip {
 	Boolean true_rep_only = false 	# disable all analyses for pseudo replicates
 									# overlap and idr will also be disabled
 	Boolean disable_fingerprint = false # no JSD plot generation (deeptools fingerprint)
+	Boolean enable_count_signal_track = false 		# generate count signal track
+	Boolean use_bwa_mem_for_pe = false # THIS IS EXPERIMENTAL
+									# use bwa mem instead of bwa aln + bwa sampe
+									#for PE dataset with read len>=70bp
 
 	Int xcor_pe_trim_bp = 50 		# for cross-correlation analysis only (R1 of paired-end fastqs)
+	Boolean use_filt_pe_ta_for_xcor = false # PE only. use filtered PE BAM for cross-corr.
 
 	String dup_marker = 'picard'	# picard.jar MarkDuplicates (picard) or 
 									# sambamba markdup (sambamba)
@@ -181,6 +186,11 @@ workflow chip {
 	Array[File] jsd_qcs = []
 	File? jsd_plot
 
+	Array[File] count_signal_track_pos_bws = []
+	Array[File] count_signal_track_neg_bws = []
+	File? count_signal_track_pooled_pos_bw_ 
+	File? count_signal_track_pooled_neg_bw_ 
+
 	### temp vars (do not define these)
 	String peak_caller_ = if pipeline_type=='tf' then select_first([peak_caller,'spp'])
 						else select_first([peak_caller,'macs2'])
@@ -238,6 +248,7 @@ workflow chip {
 			idx_tar = bwa_idx_tar,
 			fastqs = merge_fastq.merged_fastqs, #[R1,R2]
 			paired_end = paired_end,
+			use_bwa_mem_for_pe = use_bwa_mem_for_pe,
 			cpu = bwa_cpu,
 			mem_mb = bwa_mem_mb,
 			time_hr = bwa_time_hr,
@@ -261,6 +272,7 @@ workflow chip {
 			idx_tar = bwa_idx_tar,
 			fastqs = fastq_set,
 			paired_end = false,
+			use_bwa_mem_for_pe = use_bwa_mem_for_pe,
 			cpu = bwa_cpu,
 			mem_mb = bwa_mem_mb,
 			time_hr = bwa_time_hr,
@@ -382,6 +394,24 @@ workflow chip {
 		}
 	}
 
+	# generate count signal track
+	Array[File] tas_count_signal_track = if length(count_signal_track_pos_bws)>0 then []
+		else if enable_count_signal_track then tas_
+		else []
+	scatter(i in range(length(tas_count_signal_track))) {
+		call count_signal_track { input :
+			ta = tas_count_signal_track[i],
+			chrsz = chrsz,
+		}
+	}
+
+	if ( !defined(count_signal_track_pooled_pos_bw_) && enable_count_signal_track && length(tas_)>0 ) {
+		call count_signal_track as count_signal_track_pooled { input :
+			ta = select_first([pool_ta.ta_pooled, ta_pooled]),
+			chrsz = chrsz,
+		}
+	}
+
 	# align controls
 	Array[Array[File]] ctl_fastqs_rep1 = if length(ctl_fastqs_rep1_R2)>0 then transpose([ctl_fastqs_rep1_R1,ctl_fastqs_rep1_R2])
 									else transpose([ctl_fastqs_rep1_R1])
@@ -419,6 +449,7 @@ workflow chip {
 			idx_tar = bwa_idx_tar,
 			fastqs = merge_fastq_ctl.merged_fastqs, #[R1,R2]
 			paired_end = paired_end,
+			use_bwa_mem_for_pe = use_bwa_mem_for_pe,
 			cpu = bwa_cpu,
 			mem_mb = bwa_mem_mb,
 			time_hr = bwa_time_hr,
@@ -1038,6 +1069,7 @@ task bwa {
 	File idx_tar 		# reference bwa index tar
 	Array[File] fastqs 	# [read_end_id]
 	Boolean paired_end
+	Boolean use_bwa_mem_for_pe
 
 	Int cpu
 	Int mem_mb
@@ -1049,6 +1081,7 @@ task bwa {
 			${idx_tar} \
 			${sep=' ' fastqs} \
 			${if paired_end then "--paired-end" else ""} \
+			${if use_bwa_mem_for_pe then "--use-bwa-mem-for-pe" else ""} \
 			${"--nth " + cpu}
 	}
 	output {
@@ -1275,6 +1308,27 @@ task choose_ctl {
 	}	
 }
 
+task count_signal_track {
+	File ta 			# tag-align
+	File chrsz			# 2-col chromosome sizes file
+
+	command {
+		python $(which encode_count_signal_track.py) \
+			${ta} \
+			${"--chrsz " + chrsz}
+	}
+	output {
+		File pos_bw = glob("*.positive.bigwig")[0]
+		File neg_bw = glob("*.negative.bigwig")[0]
+	}
+	runtime {
+		cpu : 1
+		memory : "8000 MB"
+		time : 4
+		disks : "local-disk 50 HDD"
+	}
+}
+
 task macs2 {
 	Array[File] tas		# [ta, control_ta]. control_ta is optional
 	Int fraglen 		# fragment length from xcor
@@ -1399,7 +1453,7 @@ task idr {
 		Array[File] bfilt_idr_peak_hammock = glob("*.bfilt."+peak_type+".hammock.gz*")
 		File idr_plot = glob("*.txt.png")[0]
 		File idr_unthresholded_peak = glob("*.txt.gz")[0]
-		File idr_log = glob("*.log")[0]
+		File idr_log = glob("*.idr*.log")[0]
 		File frip_qc = if defined(ta) then glob("*.frip.qc")[0] else glob("null")[0]
 	}
 	runtime {

diff --git a/conda/install_dependencies.sh b/conda/install_dependencies.sh
@@ -74,6 +74,7 @@ source activate ${CONDA_ENV}
   cd ${CONDA_BIN}
   rm -f idr
   ln -s ../../${CONDA_ENV_PY3}/bin/idr
+  ln -s ../../${CONDA_ENV_PY3}/bin/python3
 
   # make an executable symlink for cromwell.jar on conda bin dir
   CONDA_SHARE="${CONDA_PREFIX}/share"

diff --git a/docker_image/Dockerfile b/docker_image/Dockerfile
@@ -147,4 +147,4 @@ ENV PATH="/software/chip-seq-pipeline:/software/chip-seq-pipeline/src:${PATH}"
 # make some temporary directories
 RUN for i in $(seq 0 9); do mkdir -p /mnt/ext_$i; done
 
-ENTRYPOINT ["/bin/bash","-c"]
+#ENTRYPOINT ["/bin/bash","-c"]
diff --git a/docs/dev.md b/docs/dev.md
@@ -2,8 +2,8 @@
 
 ## Command line for version change
 ```bash
-PREV_VER=v1.1.6.1
-NEW_VER=v1.1.6.1
+PREV_VER=v1.1.7
+NEW_VER=v1.1.7
 for f in $(grep -rl ${PREV_VER} --include=*.{wdl,md,sh})
 do
   sed -i "s/${PREV_VER}/${NEW_VER}/g" ${f}
@@ -24,7 +24,7 @@ Run the following command line locally to build out DX workflows for this pipeli
 
 ```bash
 # version
-VER=v1.1.6.1
+VER=v1.1.7
 
 # general
 java -jar ~/dxWDL-0.77.jar compile chip.wdl -project "ENCODE Uniform Processing Pipelines" -extras workflow_opts/docker.json -f -folder /ChIP-seq2/workflows/$VER/general -defaults examples/dx/template_general.json

diff --git a/docs/input.md b/docs/input.md
@@ -29,8 +29,8 @@ Let us take a close look at the following template JSON. Comments are not allowe
 
     // Cloud platforms (Google Cloud, DNAnexus): [GENOME]=hg38,hg19,mm10,mm9
     //   Google Cloud: gs://encode-pipeline-genome-data/[GENOME]_google.tsv
-    //   DNAnexus: dx://project-BKpvFg00VBPV975PgJ6Q03v6:data/pipeline-genome-data/[GENOME]_dx.tsv
-    //   DNAnexus(Azure): dx://project-F6K911Q9xyfgJ36JFzv03Z5J:data/pipeline-genome-data/[GENOME]_dx_azure.tsv
+    //   DNAnexus: dx://project-BKpvFg00VBPV975PgJ6Q03v6:pipeline-genome-data/[GENOME]_dx.tsv
+    //   DNAnexus(Azure): dx://project-F6K911Q9xyfgJ36JFzv03Z5J:pipeline-genome-data/[GENOME]_dx_azure.tsv
 
     // On other computers download or build reference genome database and pick a TSV from [DEST_DIR].
     //   Downloader: ./genome/download_genome_data.sh [GENOME] [DEST_DIR]
@@ -115,10 +115,16 @@ Let us take a close look at the following template JSON. Comments are not allowe
     // Disable deeptools fingerprint (JS distance)
     "chip.disable_fingerprint" : false,
 
+    // Enable count signal track generation
+    "chip.enable_count_signal_track" : false,
+
     // Trim R1 of paired ended fastqs for cross-correlation analysis only
     // Trimmed fastqs will not be used for any other analyses
     "chip.xcor_pe_trim_bp" : 50,
 
+    // Use filtered PE BAM/TAG-ALIGN for cross-correlation analysis ignoring the above trimmed R1 fastq
+    "chip.use_filt_pe_ta_for_xcor" : false,
+
     // Choose a dup marker between picard and sambamba
     // picard is recommended, use sambamba only when picard fails.
     "chip.dup_marker" : "picard",
@@ -234,8 +240,8 @@ Choose one TSV file for `"chip.genome_tsv"` in your input JSON. `[GENOME]` shoul
 |platform|path/URI|
 |-|-|
 |Google Cloud Platform|`gs://encode-pipeline-genome-data/[GENOME]_google.tsv`|
-|DNAnexus (CLI)|`dx://project-BKpvFg00VBPV975PgJ6Q03v6:data/pipeline-genome-data/[GENOME]_dx.tsv`|
-|DNAnexus (CLI, Azure)|`dx://project-F6K911Q9xyfgJ36JFzv03Z5J:data/pipeline-genome-data/[GENOME]_dx_azure.tsv`|
+|DNAnexus (CLI)|`dx://project-BKpvFg00VBPV975PgJ6Q03v6:pipeline-genome-data/[GENOME]_dx.tsv`|
+|DNAnexus (CLI, Azure)|`dx://project-F6K911Q9xyfgJ36JFzv03Z5J:pipeline-genome-data/[GENOME]_dx_azure.tsv`|
 |DNAnexus (Web)|Choose `[GENOME]_dx.tsv` from [here](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/pipeline-genome-data)|
 |DNAnexus (Web, Azure)|Choose `[GENOME]_dx.tsv` from [here](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/pipeline-genome-data)|
 |Stanford Sherlock|`/home/groups/cherry/encode/pipeline_genome_data/[GENOME]_sherlock.tsv`|

diff --git a/docs/output.md b/docs/output.md
@@ -8,7 +8,7 @@ Final HTML report (`qc.html`) and QC json (`qc.json`) files do not have any pref
 
 2. `Cromwell`: `Cromwell` will store outputs for each task under `cromwell-executions/[WORKFLOW_ID]/call-[TASK_NAME]/shard-[IDX]`. For all tasks except two peak calling tasks `idr` (irreproducible discovery rate) and `overlap` (naive overlapping peaks), `[IDX]` means a zero-based index for each replicate. For two tasks `idr` and `overlap`, `[IDX]` stands for a zero-based index for all possible pair of replicates. For example, you have 3 replicates and all possible combination of two replicates are `[(rep1,rep2), (rep1,rep3), (rep2,rep3)]`. Therefore, `call-idr/shard-2` should be an output directory for the pair of replicate 2 and 3.
 
-For more details, refer to the file table section in an HTML report generated by the pipeline. Files marked as (E) are outputs to be uploaded during ENCODE accession.
+There can be duplicate output files on `execution/` and `execution/glob-*/` directories. A file on the latter (`execution/glob-*/`) is a symbolic link of an actual output file on the former. For Google Cloud Storage bucket (`gs://`) there is no `execution/` directory and files on `glob-*/` are actual outputs.
 
 |task|filename| description|
 |-|-|-|

diff --git a/docs/tutorial_dx_web.md b/docs/tutorial_dx_web.md
@@ -15,8 +15,8 @@ This document describes instruction for the item 2).
 
 3. Move to one of the following workflow directories according to the platform you have chosen for your project (AWS or Azure). These DX workflows are pre-built with all parameters defined.
 
-* [AWS test workflow](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.6.1/test_ENCSR936XTK_subsampled_chr19_only)
-* [Azure test workflow](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.6.1/test_ENCSR936XTK_subsampled_chr19_only)
+* [AWS test workflow](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.7/test_ENCSR936XTK_subsampled_chr19_only)
+* [Azure test workflow](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.7/test_ENCSR936XTK_subsampled_chr19_only)
 
 4. Copy it to your project by right-clicking on the DX workflow `chip` and choose "Copy". 
 
@@ -40,16 +40,16 @@ This document describes instruction for the item 2).
 1. DNAnexus allows only one copy of a workflow per project. The example workflow in the previous section is pre-built for the subsampled test sample [ENCSR936XTK](https://www.encodeproject.org/experiments/ENCSR936XTK/) with all parameters defined already.
 
 2. Copy one of the following workflows according to the platform you have chosen for your project (AWS or Azure).
-* [AWS general](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.6.1/general) without pre-defined reference genome.
-* [AWS hg38](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.6.1/hg38) with pre-defined hg38 reference genome.
-* [AWS hg19](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.6.1/hg19) with pre-defined hg19 reference genome.
-* [AWS mm10](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.6.1/mm10) with pre-defined mm10 reference genome.
-* [AWS mm9](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.6.1/mm9) with pre-defined mm9 reference genome.
-* [Azure general](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.6.1/general) without pre-defined reference genome.
-* [Azure hg38](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.6.1/hg38) with pre-defined hg38 reference genome.
-* [Azure hg19](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.6.1/hg19) with pre-defined hg19 reference genome.
-* [Azure mm10](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.6.1/mm10) with pre-defined mm10 reference genome.
-* [Azure mm9](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.6.1/mm9) with pre-defined mm9 reference genome.
+* [AWS general](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.7/general) without pre-defined reference genome.
+* [AWS hg38](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.7/hg38) with pre-defined hg38 reference genome.
+* [AWS hg19](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.7/hg19) with pre-defined hg19 reference genome.
+* [AWS mm10](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.7/mm10) with pre-defined mm10 reference genome.
+* [AWS mm9](https://platform.DNAnexus.com/projects/BKpvFg00VBPV975PgJ6Q03v6/data/ChIP-seq2/workflows/v1.1.7/mm9) with pre-defined mm9 reference genome.
+* [Azure general](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.7/general) without pre-defined reference genome.
+* [Azure hg38](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.7/hg38) with pre-defined hg38 reference genome.
+* [Azure hg19](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.7/hg19) with pre-defined hg19 reference genome.
+* [Azure mm10](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.7/mm10) with pre-defined mm10 reference genome.
+* [Azure mm9](https://platform.DNAnexus.com/projects/F6K911Q9xyfgJ36JFzv03Z5J/data/ChIP-seq2/workflows/v1.1.7/mm9) with pre-defined mm9 reference genome.
 
 3. Click on the DX workflow `chip`.
 

diff --git a/docs/tutorial_local_singularity.md b/docs/tutorial_local_singularity.md
@@ -33,7 +33,7 @@
 
 6. Pull a singularity container for the pipeline. This will pull pipeline's docker container first and build a singularity one on `~/.singularity`.
     ```bash
-    $ mkdir -p ~/.singularity && cd ~/.singularity && SINGULARITY_CACHEDIR=~/.singularity SINGULARITY_PULLFOLDER=~/.singularity singularity pull --name chip-seq-pipeline-v1.1.6.1.simg -F docker://quay.io/encode-dcc/chip-seq-pipeline:v1.1.6.1
+    $ mkdir -p ~/.singularity && cd ~/.singularity && SINGULARITY_CACHEDIR=~/.singularity SINGULARITY_PULLFOLDER=~/.singularity singularity pull --name chip-seq-pipeline-v1.1.7.simg -F docker://quay.io/encode-dcc/chip-seq-pipeline:v1.1.7
     ```
 
 7. Run a pipeline for the test sample.
@@ -53,7 +53,7 @@
     ```javascript
     {
         "default_runtime_attributes" : {
-            "singularity_container" : "~/.singularity/chip-seq-pipeline-v1.1.6.1.simg",
+            "singularity_container" : "~/.singularity/chip-seq-pipeline-v1.1.7.simg",
             "singularity_bindpath" : "/your/,YOUR_OWN_DATA_DIR1,YOUR_OWN_DATA_DIR2,..."
         }
     }

diff --git a/docs/tutorial_scg.md b/docs/tutorial_scg.md
@@ -27,48 +27,43 @@ Our pipeline supports both [Conda](https://conda.io/docs/) and [Singularity](htt
 
 ## For Conda users
 
-4. [Install Conda](https://conda.io/miniconda.html). Skip this if you already have equivalent Conda alternatives (Anaconda Python). Download and run the [installer](https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh). Agree to the license term by typing `yes`. It will ask you about the installation location. On Stanford clusters (Sherlock and SCG4), we recommend to install it outside of your `$HOME` directory since its filesystem is slow and has very limited space. At the end of the installation, choose `yes` to add Miniconda's binary to `$PATH` in your BASH startup script.
-    ```bash
-    $ wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
-    $ bash Miniconda3-latest-Linux-x86_64.sh
-    ```
-
-5. Install Conda dependencies.
+4. Install Conda dependencies.
     ```bash
+    $ module load miniconda/3
     $ bash conda/uninstall_dependencies.sh  # to remove any existing pipeline env
     $ bash conda/install_dependencies.sh
     ```
 
-6. Run a pipeline for the test sample. You must have a paid account on SCG4.
+5. Run a pipeline for the test sample. You must have a paid account on SCG4.
     ```bash
     $ sbatch --account [YOUR_PAID_ACCOUNT_ON_SCG4] examples/scg/ENCSR936XTK_subsampled_chr19_only_scg_conda.sh
     ```
 
 ## For singularity users
 
-6. Run a pipeline for the test sample. You must have a paid account on SCG4.
+4. Run a pipeline for the test sample. You must have a paid account on SCG4.
     ```bash
     $ sbatch --account [YOUR_PAID_ACCOUNT_ON_SCG4] examples/scg/ENCSR936XTK_subsampled_chr19_only_scg_singularity.sh
     ```
 
 ## For all users
 
-7. It will take about an hour. You will be able to find all outputs on `cromwell-executions/chip/[RANDOM_HASH_STRING]/`. See [output directory structure](output.md) for details. You can monitor your jobs with the following command:
+6. It will take about an hour. You will be able to find all outputs on `cromwell-executions/chip/[RANDOM_HASH_STRING]/`. See [output directory structure](output.md) for details. You can monitor your jobs with the following command:
     ```bash
     $ squeue -u $USER
     ```
 
-8. See full specification for [input JSON file](input.md).
+7. See full specification for [input JSON file](input.md).
 
-9. You can resume a failed pipeline from where it left off by using `PIPELINE_METADATA`(`metadata.json`) file. This file is created for each pipeline run. See [here](../utils/resumer/README.md) for details. Once you get a new input JSON file from the resumer, then edit your shell script (`examples/scg/ENCSR936XTK_subsampled_chr19_only_scg_*.sh`) to use it `INPUT=resume.[FAILED_WORKFLOW_ID].json` instead of `INPUT=examples/...`.
+8. You can resume a failed pipeline from where it left off by using `PIPELINE_METADATA`(`metadata.json`) file. This file is created for each pipeline run. See [here](../utils/resumer/README.md) for details. Once you get a new input JSON file from the resumer, then edit your shell script (`examples/scg/ENCSR936XTK_subsampled_chr19_only_scg_*.sh`) to use it `INPUT=resume.[FAILED_WORKFLOW_ID].json` instead of `INPUT=examples/...`.
 
 ## For singularity users
 
-10. IF YOU WANT TO RUN PIPELINES WITH YOUR OWN INPUT DATA/GENOME DATABASE, PLEASE ADD THEIR DIRECTORIES TO `workflow_opts/scg.json`. For example, you have input FASTQs on `/your/input/fastqs/` and genome database installed on `/your/genome/database/` then add `/your/` to `singularity_bindpath`. You can also define multiple directories there. It's comma-separated.
+9. IF YOU WANT TO RUN PIPELINES WITH YOUR OWN INPUT DATA/GENOME DATABASE, PLEASE ADD THEIR DIRECTORIES TO `workflow_opts/scg.json`. For example, you have input FASTQs on `/your/input/fastqs/` and genome database installed on `/your/genome/database/` then add `/your/` to `singularity_bindpath`. You can also define multiple directories there. It's comma-separated.
     ```javascript
     {
         "default_runtime_attributes" : {
-            "singularity_container" : "~/.singularity/chip-seq-pipeline-v1.1.6.1.simg",
+            "singularity_container" : "~/.singularity/chip-seq-pipeline-v1.1.7.simg",
             "singularity_bindpath" : "/reference/ENCODE,/scratch,/srv/gsfs0,YOUR_OWN_DATA_DIR1,YOUR_OWN_DATA_DIR1,..."
         }
     }