IGF-HPC-Airflow/dags/dag9_tenx_single_cell_immune_profiling.py

from datetime import timedelta
import os,json,logging,subprocess
from airflow.models import DAG,Variable
from airflow.utils.dates import days_ago
from airflow.operators.python_operator import PythonOperator
from airflow.operators.python_operator import BranchPythonOperator
from airflow.operators.dummy_operator import DummyOperator
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import fetch_analysis_info_and_branch_func
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import configure_cellranger_run_func
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import run_sc_read_trimmming_func
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import run_cellranger_tool
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import decide_analysis_branch_func
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import load_cellranger_result_to_db_func
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import ftp_files_upload_for_analysis
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import irods_files_upload_for_analysis
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import run_singlecell_notebook_wrapper_func
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import load_analysis_files_func
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import task_branch_function
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import upload_analysis_file_to_box
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import convert_bam_to_cram_func
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import run_picard_for_cellranger
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import run_samtools_for_cellranger
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import run_multiqc_for_cellranger
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import index_and_copy_bam_for_parallel_analysis
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import change_pipeline_status
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import clean_up_files
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import create_and_update_qc_pages
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import load_cellranger_metrices_to_collection
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import generate_cell_sorted_bam_func
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import run_velocyto_func
from igf_airflow.utils.dag9_tenx_single_cell_immune_profiling_utils import run_scvelo_for_sc_5p_func

## ARGS
default_args = {
    'owner': 'airflow',
    'depends_on_past': False,
    'start_date': days_ago(2),
    'email_on_failure': False,
    'email_on_retry': False,
    'retries': 4,
    'catchup': True,
    'retry_delay': timedelta(minutes=5),
    'provide_context': True,
}

FEATURE_TYPE_LIST = \
  Variable.get('tenx_single_cell_immune_profiling_feature_types', default_var={})

## DAG
dag = \
  DAG(
    dag_id='dag9_tenx_single_cell_immune_profiling',
    schedule_interval=None,
    tags=['hpc', 'analysis', 'tenx', 'sc'],
    default_args=default_args,
    concurrency=100,
    max_active_runs=5,
    orientation='LR')

with dag:
  ## TASK
  fetch_analysis_info_and_branch = \
    BranchPythonOperator(
      task_id='fetch_analysis_info',
      dag=dag,
      queue='hpc_4G',
      params={
        'no_analysis_task': 'no_analysis',
        'analysis_description_xcom_key': 'analysis_description',
        'analysis_info_xcom_key': 'analysis_info'},
      python_callable=fetch_analysis_info_and_branch_func)
  ## TASK
  configure_cellranger_run = \
    PythonOperator(
      task_id='configure_cellranger_run',
      dag=dag,
      queue='hpc_4G',
      trigger_rule='none_failed_or_skipped',
      params={
        'xcom_pull_task_id': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'analysis_info_xcom_key': 'analysis_info',
        'library_csv_xcom_key': 'cellranger_library_csv'},
      python_callable=configure_cellranger_run_func)
  for analysis_name in FEATURE_TYPE_LIST.keys():
    ## TASK
    task_branch = \
      BranchPythonOperator(
        task_id=analysis_name,
        dag=dag,
        queue='hpc_4G',
        params={
          'xcom_pull_task_id': 'fetch_analysis_info',
          'analysis_info_xcom_key': 'analysis_info',
          'analysis_name': analysis_name,
          'task_prefix': 'run_trim'},
        python_callable=task_branch_function)
    run_trim_list = list()
    for run_id in range(0,10):
      ## TASK
      t = \
        PythonOperator(
          task_id='run_trim_{0}_{1}'.format(analysis_name, run_id),
          dag=dag,
          queue='hpc_4G',
          params={
            'xcom_pull_task_id': 'fetch_analysis_info',
            'analysis_info_xcom_key': 'analysis_info',
            'analysis_description_xcom_key': 'analysis_description',
            'analysis_name': analysis_name,
            'run_id': run_id,
            'r1-length': 0,
            'r2-length': 0,
            'fastq_input_dir_tag': 'fastq_dir',
            'use_ephemeral_space': True,
            'fastq_output_dir_tag': 'output_path'},
          python_callable=run_sc_read_trimmming_func)
      run_trim_list.append(t)
    ## TASK
    collect_trimmed_files = \
      DummyOperator(
        task_id='collect_trimmed_files_{0}'.format(analysis_name),
        trigger_rule='none_failed_or_skipped',
        dag=dag)
    ## PIPELINE
    fetch_analysis_info_and_branch >> task_branch
    task_branch >> run_trim_list
    run_trim_list >> collect_trimmed_files
    collect_trimmed_files >> configure_cellranger_run
  ## TASK
  no_analysis = \
    DummyOperator(
      task_id='no_analysis',
      dag=dag)
  ## PIPELINE
  fetch_analysis_info_and_branch >> no_analysis
  ## TASK
  run_cellranger = \
    PythonOperator(
      task_id='run_cellranger',
      dag=dag,
      queue='hpc_64G16t24hr',
      params={
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'library_csv_xcom_key': 'cellranger_library_csv',
        'library_csv_xcom_pull_task': 'configure_cellranger_run',
        'cellranger_xcom_key': 'cellranger_output',
        'cellranger_options': ['--localcores 14', '--localmem 60']},
      python_callable=run_cellranger_tool)
  ## PIPELINE
  configure_cellranger_run >> run_cellranger
  ## TASK
  decide_analysis_branch = \
    BranchPythonOperator(
      task_id='decide_analysis_branch',
      dag=dag,
      queue='hpc_4G',
      python_callable=decide_analysis_branch_func,
      params={
        'load_cellranger_result_to_db_task': 'load_cellranger_result_to_db',
        'run_scanpy_for_sc_5p_task': 'run_scanpy_for_sc_5p',
        'run_scirpy_for_vdj_task': 'run_scirpy_for_vdj',
        'run_scirpy_for_vdj_b_task': 'run_scirpy_for_vdj_b',
        'run_scirpy_vdj_t_task': 'run_scirpy_for_vdj_t',
        'run_seurat_for_sc_5p_task': 'run_seurat_for_sc_5p',
        'convert_cellranger_bam_to_cram_task': 'convert_cellranger_bam_to_cram',
        'library_csv_xcom_key': 'cellranger_library_csv',
        'library_csv_xcom_pull_task': 'configure_cellranger_run'})
  ## PIPELINE
  run_cellranger >> decide_analysis_branch
  ## TASK
  load_cellranger_result_to_db = \
    PythonOperator(
      task_id='load_cellranger_result_to_db',
      dag=dag,
      queue='hpc_4G',
      python_callable=load_cellranger_result_to_db_func,
      params={
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'cellranger_xcom_key': 'cellranger_output',
        'cellranger_xcom_pull_task': 'run_cellranger',
        'collection_type': 'CELLRANGER_MULTI',
        'html_collection_type': 'CELLRANGER_HTML',
        'collection_table': 'sample',
        'xcom_collection_name_key': 'sample_igf_id',
        'genome_column': 'genome_build',
        'analysis_name': 'cellranger_multi',
        'output_xcom_key': 'loaded_output_files',
        'html_xcom_key': 'html_report_file',
        'html_report_file_name': 'web_summary.html'})
  upload_cellranger_report_to_ftp = \
    PythonOperator(
      task_id='upload_cellranger_report_to_ftp',
      dag=dag,
      queue='hpc_4G',
      python_callable=ftp_files_upload_for_analysis,
      params={
        'xcom_pull_task': 'load_cellranger_result_to_db',
        'xcom_pull_files_key': 'html_report_file',
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'collection_type': 'FTP_CELLRANGER_HTML',
        'collection_table': 'sample',
        'collect_remote_file': True})
  upload_cellranger_report_to_box = \
    PythonOperator(
      task_id='upload_cellranger_report_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'load_cellranger_result_to_db',
        'xcom_pull_files_key': 'html_report_file',
        'analysis_tag': 'cellranger_multi'})
  upload_cellranger_results_to_irods = \
    PythonOperator(
      task_id='upload_cellranger_results_to_irods',
      dag=dag,
      queue='hpc_4G',
      python_callable=irods_files_upload_for_analysis,
      params={
        'xcom_pull_task': 'load_cellranger_result_to_db',
        'xcom_pull_files_key': 'loaded_output_files',
        'collection_name_key': 'sample_igf_id',
        'collection_name_task': 'load_cellranger_result_to_db',
        'analysis_name': 'cellranger_multi'})
  ## PIPELINE
  decide_analysis_branch >> load_cellranger_result_to_db
  load_cellranger_result_to_db >> upload_cellranger_report_to_ftp
  load_cellranger_result_to_db >> upload_cellranger_report_to_box
  load_cellranger_result_to_db >> upload_cellranger_results_to_irods
  ## TASK
  run_scanpy_for_sc_5p = \
    PythonOperator(
      task_id='run_scanpy_for_sc_5p',
      dag=dag,
      queue='hpc_4G',
      python_callable=run_singlecell_notebook_wrapper_func,
      params={
        'cellranger_xcom_key': 'cellranger_output',
        'cellranger_xcom_pull_task': 'run_cellranger',
        'scanpy_timeout': 1200,
        'allow_errors': False,
        'kernel_name': 'python3',
        'count_dir': 'count',
        'analysis_name': 'scanpy',
        'output_notebook_key': 'scanpy_notebook',
        'output_cellbrowser_key': 'cellbrowser_dirs',
        'output_scanpy_h5ad_key': 'scanpy_h5ad',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description'})
  load_cellranger_gex_matrics_to_db = \
    PythonOperator(
      task_id='load_cellranger_gex_matrics_to_db',
      dag=dag,
      queue='hpc_4G',
      python_callable=load_cellranger_metrices_to_collection,
      params={
        'cellranger_xcom_key': 'cellranger_output',
        'cellranger_xcom_pull_task': 'run_cellranger',
        'collection_type': 'CELLRANGER_MULTI',
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'metrics_summary_file': 'metrics_summary.csv',
        'attribute_prefix': 'CELLRANGER_COUNT'})
  load_scanpy_report_for_sc_5p_to_db = \
    PythonOperator(
      task_id='load_scanpy_report_for_sc_5p_to_db',
      dag=dag,
      queue='hpc_4G',
      python_callable=load_analysis_files_func,
      params={
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'file_name_task': 'run_scanpy_for_sc_5p',
        'file_name_key': 'scanpy_notebook',
        'analysis_name': 'scanpy_5p',
        'collection_type': 'SCANPY_HTML',
        'collection_table': 'sample',
        'output_files_key': 'output_db_files'})
  upload_scanpy_report_for_sc_5p_to_ftp = \
    PythonOperator(
      task_id='upload_scanpy_report_for_sc_5p_to_ftp',
      dag=dag,
      queue='hpc_4G',
      python_callable=ftp_files_upload_for_analysis,
      params={
        'xcom_pull_task': 'load_scanpy_report_for_sc_5p_to_db',
        'xcom_pull_files_key': 'output_db_files',
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'collection_type': 'FTP_SCANPY_HTML',
        'collection_table': 'sample',
        'collect_remote_file': True})
  upload_scanpy_report_for_sc_5p_to_box = \
    PythonOperator(
      task_id='upload_scanpy_report_for_sc_5p_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'load_scanpy_report_for_sc_5p_to_db',
        'xcom_pull_files_key': 'output_db_files',
        'analysis_tag': 'scanpy_single_sample_report'})
  upload_cellbrowser_for_sc_5p_to_ftp = \
    PythonOperator(
      task_id='upload_cellbrowser_for_sc_5p_to_ftp',
      dag=dag,
      queue='hpc_4G',
      python_callable=ftp_files_upload_for_analysis,
      params={
        'xcom_pull_task': 'run_scanpy_for_sc_5p',
        'xcom_pull_files_key': 'cellbrowser_dirs',
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'collection_type': 'FTP_CELLBROWSER',
        'collection_table': 'sample',
        'collect_remote_file': True})
  ## PIPELINE
  decide_analysis_branch >> run_scanpy_for_sc_5p
  run_scanpy_for_sc_5p >> load_scanpy_report_for_sc_5p_to_db
  run_scanpy_for_sc_5p >> load_cellranger_gex_matrics_to_db
  load_scanpy_report_for_sc_5p_to_db >> upload_scanpy_report_for_sc_5p_to_ftp
  load_scanpy_report_for_sc_5p_to_db >> upload_scanpy_report_for_sc_5p_to_box
  run_scanpy_for_sc_5p >> upload_cellbrowser_for_sc_5p_to_ftp
  ## TASK
  run_scirpy_for_vdj_b = \
    PythonOperator(
      task_id='run_scirpy_for_vdj_b',
      dag=dag,
      queue='hpc_4G',
      python_callable=run_singlecell_notebook_wrapper_func,
      params={
        'cellranger_xcom_key': 'cellranger_output',
        'cellranger_xcom_pull_task': 'run_cellranger',
        'scanpy_timeout': 1200,
        'allow_errors': False,
        'kernel_name': 'python3',
        'analysis_name': 'scirpy',
        'vdj_dir': 'vdj_b',
        'count_dir': 'count',
        'output_notebook_key': 'scirpy_notebook',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description'})
  load_cellranger_vdjB_matrics_to_db = \
    PythonOperator(
      task_id='load_cellranger_vdjB_matrics_to_db',
      dag=dag,
      queue='hpc_4G',
      python_callable=load_cellranger_metrices_to_collection,
      params={
        'cellranger_xcom_key': 'cellranger_output',
        'cellranger_xcom_pull_task': 'run_cellranger',
        'collection_type': 'CELLRANGER_MULTI',
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'metrics_summary_file': 'metrics_summary.csv',
        'attribute_prefix': 'CELLRANGER_VDJB'})
  load_scirpy_report_for_vdj_b_to_db = \
    PythonOperator(
      task_id='load_scirpy_report_for_vdj_b_to_db',
      dag=dag,
      queue='hpc_4G',
      python_callable=load_analysis_files_func,
      params={
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'file_name_task': 'run_scirpy_for_vdj_b',
        'file_name_key': 'scirpy_notebook',
        'analysis_name': 'scirpy_vdj_b',
        'collection_type': 'SCIRPY_VDJ_B_HTML',
        'collection_table': 'sample',
        'output_files_key': 'output_db_files'})
  upload_scirpy_report_for_vdj_b_to_ftp = \
    PythonOperator(
      task_id='upload_scirpy_report_for_vdj_b_to_ftp',
      dag=dag,
      queue='hpc_4G',
      python_callable=ftp_files_upload_for_analysis,
      params={
        'xcom_pull_task': 'load_scirpy_report_for_vdj_b_to_db',
        'xcom_pull_files_key': 'output_db_files',
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'collection_type': 'FTP_SCIRPY_VDJ_B_HTML',
        'collection_table': 'sample',
        'collect_remote_file': True})
  upload_scirpy_report_for_vdj_b_to_box = \
    PythonOperator(
      task_id='upload_scanpy_report_for_vdj_b_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'load_scirpy_report_for_vdj_b_to_db',
        'xcom_pull_files_key': 'output_db_files',
        'analysis_tag': 'scirpy_vdj_b_single_sample_report'})
  ## PIPELINE
  decide_analysis_branch >> run_scirpy_for_vdj_b
  run_scirpy_for_vdj_b >> load_scirpy_report_for_vdj_b_to_db
  run_scirpy_for_vdj_b >> load_cellranger_vdjB_matrics_to_db
  load_scirpy_report_for_vdj_b_to_db >> upload_scirpy_report_for_vdj_b_to_ftp
  load_scirpy_report_for_vdj_b_to_db >> upload_scirpy_report_for_vdj_b_to_box
  ## TASK
  run_scirpy_for_vdj_t = \
    PythonOperator(
      task_id='run_scirpy_for_vdj_t',
      dag=dag,
      queue='hpc_4G',
      python_callable=run_singlecell_notebook_wrapper_func,
      params={
        'cellranger_xcom_key': 'cellranger_output',
        'cellranger_xcom_pull_task': 'run_cellranger',
        'scanpy_timeout': 1200,
        'allow_errors': False,
        'kernel_name': 'python3',
        'analysis_name': 'scirpy',
        'vdj_dir': 'vdj_t',
        'count_dir': 'count',
        'output_notebook_key': 'scirpy_notebook',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description'})
  load_cellranger_vdjT_matrics_to_db = \
    PythonOperator(
      task_id='load_cellranger_vdjT_matrics_to_db',
      dag=dag,
      queue='hpc_4G',
      python_callable=load_cellranger_metrices_to_collection,
      params={
        'cellranger_xcom_key': 'cellranger_output',
        'cellranger_xcom_pull_task': 'run_cellranger',
        'collection_type': 'CELLRANGER_MULTI',
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'metrics_summary_file': 'metrics_summary.csv',
        'attribute_prefix': 'CELLRANGER_VDJT'})
  load_scirpy_report_for_vdj_t_to_db = \
    PythonOperator(
      task_id='load_scirpy_report_for_vdj_t_to_db',
      dag=dag,
      queue='hpc_4G',
      python_callable=load_analysis_files_func,
      params={
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'file_name_task': 'run_scirpy_for_vdj_t',
        'file_name_key': 'scirpy_notebook',
        'analysis_name': 'scirpy_vdj_t',
        'collection_type': 'SCIRPY_VDJ_T_HTML',
        'collection_table': 'sample',
        'output_files_key': 'output_db_files'})
  upload_scirpy_report_for_vdj_t_to_ftp = \
    PythonOperator(
      task_id='upload_scirpy_report_for_vdj_t_to_ftp',
      dag=dag,
      queue='hpc_4G',
      python_callable=ftp_files_upload_for_analysis,
      params={
        'xcom_pull_task': 'load_scirpy_report_for_vdj_t_to_db',
        'xcom_pull_files_key': 'output_db_files',
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'collection_type': 'FTP_SCIRPY_VDJ_T_HTML',
        'collection_table': 'sample',
        'collect_remote_file': True})
  upload_scirpy_report_for_vdj_t_to_box = \
    PythonOperator(
      task_id='upload_scirpy_report_for_vdj_t_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'load_scirpy_report_for_vdj_t_to_db',
        'xcom_pull_files_key': 'output_db_files',
        'analysis_tag': 'scirpy_vdj_t_single_sample_report'})
  ## PIPELINE
  decide_analysis_branch >> run_scirpy_for_vdj_t
  run_scirpy_for_vdj_t >> load_scirpy_report_for_vdj_t_to_db
  run_scirpy_for_vdj_t >> load_cellranger_vdjT_matrics_to_db
  load_scirpy_report_for_vdj_t_to_db >> upload_scirpy_report_for_vdj_t_to_ftp
  load_scirpy_report_for_vdj_t_to_db >> upload_scirpy_report_for_vdj_t_to_box
  ## TASK
  run_seurat_for_sc_5p = \
    PythonOperator(
      task_id='run_seurat_for_sc_5p',
      dag=dag,
      queue='hpc_4G',
      python_callable=run_singlecell_notebook_wrapper_func,
      params={
        'cellranger_xcom_key': 'cellranger_output',
        'cellranger_xcom_pull_task': 'run_cellranger',
        'scanpy_timeout': 1200,
        'allow_errors': False,
        'kernel_name': 'ir',
        'analysis_name': 'seurat',
        'vdj_dir': 'vdj',
        'count_dir': 'count',
        'output_notebook_key': 'seurat_notebook',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description'})
  load_seurat_report_for_sc_5p_db = \
    PythonOperator(
      task_id='load_seurat_report_for_sc_5p_db',
      dag=dag,
      queue='hpc_4G',
      python_callable=load_analysis_files_func,
      params={
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'file_name_task': 'run_seurat_for_sc_5p',
        'file_name_key': 'seurat_notebook',
        'analysis_name': 'seurat_5p',
        'collection_type': 'SEURAT_HTML',
        'collection_table': 'sample',
        'output_files_key': 'output_db_files'})
  upload_seurat_report_for_sc_5p_ftp = \
    PythonOperator(
      task_id='upload_seurat_report_for_sc_5p_ftp',
      dag=dag,
      queue='hpc_4G',
      python_callable=ftp_files_upload_for_analysis,
      params={
        'xcom_pull_task': 'load_seurat_report_for_sc_5p_db',
        'xcom_pull_files_key': 'output_db_files',
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'collection_type': 'FTP_SEURAT_HTML',
        'collection_table': 'sample',
        'collect_remote_file': True})
  upload_seurat_report_for_sc_5p_to_box = \
    PythonOperator(
      task_id='upload_seurat_report_for_sc_5p_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'load_seurat_report_for_sc_5p_db',
        'xcom_pull_files_key': 'output_db_files',
        'analysis_tag': 'seurat_single_sample_report'})
  ## PIPELINE
  decide_analysis_branch >> run_seurat_for_sc_5p
  run_seurat_for_sc_5p >> load_seurat_report_for_sc_5p_db
  load_seurat_report_for_sc_5p_db >> upload_seurat_report_for_sc_5p_ftp
  load_seurat_report_for_sc_5p_db >> upload_seurat_report_for_sc_5p_to_box
  ## TASK
  convert_cellranger_bam_to_cram = \
    PythonOperator(
      task_id='convert_cellranger_bam_to_cram',
      dag=dag,
      queue='hpc_4G4t',
      python_callable=convert_bam_to_cram_func,
      params={
        'xcom_pull_files_key': 'cellranger_output',
        'xcom_pull_task': 'run_cellranger',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'use_ephemeral_space': True,
        'threads': 4,
        'cellranger_bam_path': 'count/sample_alignments.bam',
        'analysis_name': 'cellranger',
        'collection_type': 'ANALYSIS_CRAM',
        'collection_table': 'sample',
        'cram_files_xcom_key': 'cram_files'})
  ## PIPELINE
  decide_analysis_branch >> convert_cellranger_bam_to_cram
  ## TASK
  generate_cell_sorted_bam = \
    PythonOperator(
      task_id='generate_cell_sorted_bam',
      dag=dag,
      queue='hpc_16G8t',
      python_callable=generate_cell_sorted_bam_func,
      params={
        'xcom_pull_task': 'run_cellranger',
        'xcom_pull_files_key': 'cellranger_output',
        'cellranger_bam_path': 'count/sample_alignments.bam',
        'cellsorted_bam_path': 'count/cellsorted_sample_alignments.bam',
        'samtools_mem': '2G',
        'threads': 7})
  run_velocyto = \
    PythonOperator(
      task_id='run_velocyto',
      queue='hpc_16G_long',
      python_callable=run_velocyto_func,
      params={
        'xcom_pull_task': 'run_cellranger',
        'xcom_pull_files_key': 'cellranger_output',
        'cell_sorted_bam_name': 'count/cellsorted_sample_alignments.bam',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description' })
  run_scvelo_for_sc_5p = \
    PythonOperator(
      task_id='run_scvelo_for_sc_5p',
      dag=dag,
      queue='hpc_32G16t',
      python_callable=run_scvelo_for_sc_5p_func,
      params={
        'xcom_pull_task': 'run_cellranger',
        'xcom_pull_files_key': 'cellranger_output',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'loom_file_key': 'loom_output',
        'loom_file_task': 'run_velocyto',
        'scanpy_h5ad_task':'run_scanpy_for_sc_5p',
        'scanpy_h5ad_key': 'scanpy_h5ad',
        'timeout': 2400,
        'allow_errors': False,
        'cpu_threads': 14,
        'output_notebook_key': 'scvelo_notebook'})
  load_loom_file_to_rds = \
    PythonOperator(
      task_id='load_loom_file_to_rds',
      dag=dag,
      queue='hpc_4G',
      python_callable=load_analysis_files_func,
      params={
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'file_name_task': 'run_velocyto',
        'file_name_key': 'loom_output',
        'analysis_name': 'velocyto_5p',
        'collection_type': 'VELOCYTO_LOOM',
        'collection_table': 'sample',
        'output_files_key': 'output_db_files'})
  upload_loom_file_to_irods = \
    PythonOperator(
      task_id='upload_loom_file_to_irods',
      dag=dag,
      queue='hpc_4G',
      python_callable=irods_files_upload_for_analysis,
      params={
        'xcom_pull_task': 'load_loom_file_to_rds',
        'xcom_pull_files_key': 'output_db_files',
        'collection_name_key': 'sample_igf_id',
        'collection_name_task': 'load_cellranger_result_to_db',
        'analysis_name': 'velocyto_loom'})
  load_scvelo_report_to_rds = \
    PythonOperator(
      task_id='load_scvelo_report_to_rds',
      dag=dag,
      queue='hpc_4G',
      python_callable=load_analysis_files_func,
      params={
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'file_name_task': 'run_scvelo_for_sc_5p',
        'file_name_key': 'scvelo_notebook',
        'analysis_name': 'scvelo_5p',
        'collection_type': 'SCVELO_HTML',
        'collection_table': 'sample',
        'output_files_key': 'output_db_files'})
  upload_scvelo_report_to_ftp = \
    PythonOperator(
      task_id='upload_scvelo_report_to_ftp',
      dag=dag,
      queue='hpc_4G',
      python_callable=ftp_files_upload_for_analysis,
      params={
        'xcom_pull_task': 'load_scvelo_report_to_rds',
        'xcom_pull_files_key': 'output_db_files',
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'collection_type': 'FTP_SCVELO_HTML',
        'collection_table': 'sample',
        'collect_remote_file': True})
  upload_scvelo_report_to_box = \
    PythonOperator(
      task_id='upload_scvelo_report_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'load_scvelo_report_to_rds',
        'xcom_pull_files_key': 'output_db_files',
        'analysis_tag': 'scvelo_single_sample_report'})
  ## PIPELINE
  convert_cellranger_bam_to_cram >> generate_cell_sorted_bam
  generate_cell_sorted_bam >> run_velocyto
  run_velocyto >> run_scvelo_for_sc_5p
  run_scanpy_for_sc_5p >> run_scvelo_for_sc_5p
  run_velocyto >> load_loom_file_to_rds
  load_loom_file_to_rds >> upload_loom_file_to_irods
  run_scvelo_for_sc_5p >> load_scvelo_report_to_rds
  load_scvelo_report_to_rds >> upload_scvelo_report_to_ftp
  load_scvelo_report_to_rds >> upload_scvelo_report_to_box
  ## TASK
  copy_bam_for_parallel_runs = \
    BranchPythonOperator(
      task_id='copy_bam_for_parallel_runs',
      dag=dag,
      queue='hpc_4G',
      python_callable=index_and_copy_bam_for_parallel_analysis,
      params={
        'xcom_pull_files_key': 'cellranger_output',
        'xcom_pull_task': 'run_cellranger',
        'cellranger_bam_path': 'count/sample_alignments.bam',
        'list_of_tasks': [
          'run_picard_alignment_summary',
          'run_picard_qual_summary',
          'run_picard_rna_summary',
          'run_picard_gc_summary',
          'run_picard_base_dist_summary',
          'run_samtools_stats']})
  ## TASK
  upload_cram_to_irods = \
    PythonOperator(
      task_id='upload_cram_to_irods',
      dag=dag,
      queue='hpc_4G',
      python_callable=irods_files_upload_for_analysis,
      params={
        'xcom_pull_task': 'convert_cellranger_bam_to_cram',
        'xcom_pull_files_key': 'cram_files',
        'collection_name_key': 'sample_igf_id',
        'collection_name_task': 'load_cellranger_result_to_db',
        'analysis_name': 'cellranger_multi'})
  ## PIPELINE
  #convert_cellranger_bam_to_cram >> copy_bam_for_parallel_runs                  # we need to load metrics to cram
  generate_cell_sorted_bam >> copy_bam_for_parallel_runs
  convert_cellranger_bam_to_cram >> upload_cram_to_irods
  ## TASK
  run_picard_alignment_summary = \
    PythonOperator(
      task_id='run_picard_alignment_summary',
      dag=dag,
      queue='hpc_4G',
      python_callable=run_picard_for_cellranger,
      params={
        'xcom_pull_files_key': 'run_picard_alignment_summary',
        'xcom_pull_task': 'copy_bam_for_parallel_runs',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'use_ephemeral_space': True,
        'load_metrics_to_cram': True,
        'java_param': '-Xmx4g',
        'picard_command': 'CollectAlignmentSummaryMetrics',
        'picard_option': {},
        'analysis_files_xcom_key': 'picard_alignment_summary',
        'bam_files_xcom_key': None})
  ## PIPELINE
  copy_bam_for_parallel_runs >> run_picard_alignment_summary
  ## TASK
  cleanup_picard_alignment_summary_input = \
    PythonOperator(
      task_id='cleanup_picard_alignment_summary_input',
      dag=dag,
      queue='hpc_4G',
      python_callable=clean_up_files,
      params={
        'xcom_pull_files_key': 'run_picard_alignment_summary',
        'xcom_pull_task': 'copy_bam_for_parallel_runs'})
  ## PIPELINE
  run_picard_alignment_summary >> cleanup_picard_alignment_summary_input
  ## TASK
  upload_picard_alignment_summary_to_box = \
    PythonOperator(
      task_id='upload_picard_alignment_summary_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'run_picard_alignment_summary',
        'xcom_pull_files_key': 'picard_alignment_summary',
        'analysis_tag': 'Picard-CollectAlignmentSummaryMetrics'})
  ## PIPELINE
  run_picard_alignment_summary >> upload_picard_alignment_summary_to_box
  ## TASK
  run_picard_qual_summary = \
    PythonOperator(
      task_id='run_picard_qual_summary',
      dag=dag,
      queue='hpc_4G',
      python_callable=run_picard_for_cellranger,
      params={
        'xcom_pull_files_key': 'run_picard_qual_summary',
        'xcom_pull_task': 'copy_bam_for_parallel_runs',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'use_ephemeral_space': True,
        'load_metrics_to_cram': True,
        'java_param': '-Xmx4g',
        'picard_command': 'QualityScoreDistribution',
        'picard_option': {},
        'analysis_files_xcom_key': 'picard_qual_summary',
        'bam_files_xcom_key': None})
  ## PIPELINE
  copy_bam_for_parallel_runs >> run_picard_qual_summary
  ## TASK
  cleanup_picard_qual_summary_input = \
    PythonOperator(
      task_id='cleanup_picard_qual_summary_input',
      dag=dag,
      queue='hpc_4G',
      python_callable=clean_up_files,
      params={
        'xcom_pull_files_key': 'run_picard_qual_summary',
        'xcom_pull_task': 'copy_bam_for_parallel_runs'})
  ## PIPELINE
  run_picard_qual_summary >> cleanup_picard_qual_summary_input
  ## TASK
  upload_picard_qual_summary_to_box = \
    PythonOperator(
      task_id='upload_picard_qual_summary_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'run_picard_qual_summary',
        'xcom_pull_files_key': 'picard_qual_summary',
        'analysis_tag': 'Picard-QualityScoreDistribution'})
  ## PIPELINE
  run_picard_qual_summary >> upload_picard_qual_summary_to_box
  ## TASK
  run_picard_rna_summary = \
    PythonOperator(
      task_id='run_picard_rna_summary',
      dag=dag,
      queue='hpc_8G',
      python_callable=run_picard_for_cellranger,
      params={
        'xcom_pull_files_key': 'run_picard_rna_summary',
        'xcom_pull_task': 'copy_bam_for_parallel_runs',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'use_ephemeral_space': True,
        'load_metrics_to_cram': True,
        'java_param': '-Xmx7g',
        'picard_command': 'CollectRnaSeqMetrics',
        'picard_option': {},
        'analysis_files_xcom_key': 'picard_rna_summary',
        'bam_files_xcom_key': None})
  ## PIPELINE
  copy_bam_for_parallel_runs >> run_picard_rna_summary
  ## TASK
  cleanup_picard_rna_summary_input = \
    PythonOperator(
      task_id='cleanup_picard_rna_summary_input',
      dag=dag,
      queue='hpc_4G',
      python_callable=clean_up_files,
      params={
        'xcom_pull_files_key': 'run_picard_rna_summary',
        'xcom_pull_task': 'copy_bam_for_parallel_runs'})
  ## PIPELINE
  run_picard_rna_summary >> cleanup_picard_rna_summary_input
  ## TASK
  upload_picard_rna_summary_to_box = \
    PythonOperator(
      task_id='upload_picard_rna_summary_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'run_picard_rna_summary',
        'xcom_pull_files_key': 'picard_rna_summary',
        'analysis_tag': 'Picard-CollectRnaSeqMetrics'})
  ## PIPELINE
  run_picard_rna_summary >> upload_picard_rna_summary_to_box
  ## TASK
  run_picard_gc_summary = \
    PythonOperator(
      task_id='run_picard_gc_summary',
      dag=dag,
      queue='hpc_4G',
      python_callable=run_picard_for_cellranger,
      params={
        'xcom_pull_files_key': 'run_picard_gc_summary',
        'xcom_pull_task': 'copy_bam_for_parallel_runs',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'use_ephemeral_space': True,
        'load_metrics_to_cram': True,
        'java_param': '-Xmx4g',
        'picard_command': 'CollectGcBiasMetrics',
        'picard_option': {},
        'analysis_files_xcom_key': 'picard_gc_summary',
        'bam_files_xcom_key': None})
  ## PIPELINE
  copy_bam_for_parallel_runs >> run_picard_gc_summary
  ## TASK
  cleanup_picard_gc_summary_input = \
    PythonOperator(
      task_id='cleanup_picard_gc_summary_input',
      dag=dag,
      queue='hpc_4G',
      python_callable=clean_up_files,
      params={
        'xcom_pull_files_key': 'run_picard_gc_summary',
        'xcom_pull_task': 'copy_bam_for_parallel_runs'})
  ## PIPELINE
  run_picard_gc_summary >> cleanup_picard_gc_summary_input
  ## TASK
  upload_picard_gc_summary_to_box = \
    PythonOperator(
      task_id='upload_picard_gc_summary_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'run_picard_gc_summary',
        'xcom_pull_files_key': 'picard_gc_summary',
        'analysis_tag': 'Picard-CollectGcBiasMetrics'})
  ## PIPELINE
  run_picard_gc_summary >> upload_picard_gc_summary_to_box
  ## TASK
  run_picard_base_dist_summary = \
    PythonOperator(
      task_id='run_picard_base_dist_summary',
      dag=dag,
      queue='hpc_4G',
      python_callable=run_picard_for_cellranger,
      params={
        'xcom_pull_files_key': 'run_picard_base_dist_summary',
        'xcom_pull_task': 'copy_bam_for_parallel_runs',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'use_ephemeral_space': True,
        'load_metrics_to_cram': True,
        'java_param': '-Xmx4g',
        'picard_command': 'CollectBaseDistributionByCycle',
        'picard_option': {},
        'analysis_files_xcom_key': 'picard_base_summary',
        'bam_files_xcom_key': None})
  ## PIPELINE
  copy_bam_for_parallel_runs >> run_picard_base_dist_summary
  ## TASK
  cleanup_picard_base_dist_summary_input = \
    PythonOperator(
      task_id='cleanup_picard_base_dist_summary_input',
      dag=dag,
      queue='hpc_4G',
      python_callable=clean_up_files,
      params={
        'xcom_pull_files_key': 'run_picard_base_dist_summary',
        'xcom_pull_task': 'copy_bam_for_parallel_runs'})
  ## PIPELINE
  run_picard_base_dist_summary >> cleanup_picard_base_dist_summary_input
  ## TASK
  upload_picard_base_dist_summary_to_box = \
    PythonOperator(
      task_id='upload_picard_base_dist_summary_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'run_picard_base_dist_summary',
        'xcom_pull_files_key': 'picard_base_summary',
        'analysis_tag': 'Picard-CollectBaseDistributionByCycle'})
  ## PIPELINE
  run_picard_base_dist_summary >> upload_picard_base_dist_summary_to_box
  ## TASK
  run_samtools_stats = \
    PythonOperator(
      task_id='run_samtools_stats',
      dag=dag,
      queue='hpc_4G4t',
      python_callable=run_samtools_for_cellranger,
      params={
        'xcom_pull_files_key': 'run_samtools_stats',
        'xcom_pull_task': 'copy_bam_for_parallel_runs',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'use_ephemeral_space': True,
        'load_metrics_to_cram': True,
        'samtools_command': 'stats',
        'threads': 4,
        'analysis_files_xcom_key': 'samtools_stats'})
  ## PIPELINE
  copy_bam_for_parallel_runs >> run_samtools_stats
  ## TASK
  upload_samtools_stats_to_box = \
    PythonOperator(
      task_id='upload_samtools_stats_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'run_samtools_stats',
        'xcom_pull_files_key': 'samtools_stats',
        'analysis_tag': 'Samtools-stats'})
  ## PIPELINE
  run_samtools_stats >> upload_samtools_stats_to_box
  ## TASK
  run_samtools_idxstats = \
    PythonOperator(
      task_id='run_samtools_idxstats',
      dag=dag,
      queue='hpc_4G4t',
      python_callable=run_samtools_for_cellranger,
      params={
        'xcom_pull_files_key': 'run_samtools_stats',
        'xcom_pull_task': 'copy_bam_for_parallel_runs',
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'use_ephemeral_space': True,
        'load_metrics_to_cram': True,
        'samtools_command': 'idxstats',
        'threads': 4,
        'analysis_files_xcom_key': 'samtools_idxstats'})
  ## PIPELINE
  run_samtools_stats >> run_samtools_idxstats
  ## TASK
  cleanup_samtools_stats_input = \
    PythonOperator(
      task_id='cleanup_samtools_stats_input',
      dag=dag,
      queue='hpc_4G',
      python_callable=clean_up_files,
      params={
        'xcom_pull_files_key': 'run_samtools_stats',
        'xcom_pull_task': 'copy_bam_for_parallel_runs'})
  ## PIPELINE
  run_samtools_idxstats >> cleanup_samtools_stats_input
  ## TASK
  upload_samtools_idxstats_to_box = \
    PythonOperator(
      task_id='upload_samtools_idxstats_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'run_samtools_idxstats',
        'xcom_pull_files_key': 'samtools_idxstats',
        'analysis_tag': 'Samtools-idxstats'})
  ## PIPELINE
  run_samtools_idxstats >> upload_samtools_idxstats_to_box
  ## TASK
  run_multiqc = \
    PythonOperator(
      task_id='run_multiqc',
      dag=dag,
      queue='hpc_4G',
      trigger_rule='none_failed_or_skipped',
      python_callable=run_multiqc_for_cellranger,
      params={
        'list_of_analysis_xcoms_and_tasks': {
          'run_cellranger': 'cellranger_output',
          'run_picard_alignment_summary': 'picard_alignment_summary',
          'run_picard_qual_summary': 'picard_qual_summary',
          'run_picard_rna_summary': 'picard_rna_summary',
          'run_picard_gc_summary': 'picard_gc_summary',
          'run_picard_base_dist_summary': 'picard_base_summary',
          'run_samtools_stats': 'samtools_stats',
          'run_samtools_idxstats': 'samtools_idxstats'},
        'analysis_description_xcom_pull_task': 'fetch_analysis_info',
        'analysis_description_xcom_key': 'analysis_description',
        'use_ephemeral_space': True,
        'multiqc_html_file_xcom_key': 'multiqc_html',
        'multiqc_data_file_xcom_key': 'multiqc_data',
        'tool_order_list': ['picad', 'samtools']})
  ## PIPELINE
  run_picard_alignment_summary >> run_multiqc
  run_picard_qual_summary >> run_multiqc
  run_picard_rna_summary >> run_multiqc
  run_picard_gc_summary >> run_multiqc
  run_picard_base_dist_summary >> run_multiqc
  run_samtools_idxstats >> run_multiqc
  ## TASK
  load_multiqc_html = \
    PythonOperator(
      task_id='load_multiqc_html',
      dag=dag,
      queue='hpc_4G',
      python_callable=load_analysis_files_func,
      params={
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'file_name_task': 'run_multiqc',
        'file_name_key': 'multiqc_html',
        'analysis_name': 'multiqc',
        'collection_type': 'MULTIQC_HTML',
        'collection_table': 'sample',
        'output_files_key': 'output_db_files'})
  ## PIPELINE
  run_multiqc >> load_multiqc_html
  ## TASK
  upload_multiqc_to_ftp = \
    PythonOperator(
      task_id='upload_multiqc_to_ftp',
      dag=dag,
      queue='hpc_4G',
      python_callable=ftp_files_upload_for_analysis,
      params={
        'xcom_pull_task': 'load_multiqc_html',
        'xcom_pull_files_key': 'output_db_files',
        'collection_name_task': 'load_cellranger_result_to_db',
        'collection_name_key': 'sample_igf_id',
        'collection_type': 'FTP_MULTIQC_HTML',
        'collection_table': 'sample',
        'collect_remote_file': True})
  ## PIPELINE
  load_multiqc_html >> upload_multiqc_to_ftp
  ## TASK
  upload_multiqc_to_box = \
    PythonOperator(
      task_id='upload_multiqc_to_box',
      dag=dag,
      queue='hpc_4G',
      python_callable=upload_analysis_file_to_box,
      params={
        'xcom_pull_task': 'load_multiqc_html',
        'xcom_pull_files_key': 'output_db_files',
        'analysis_tag': 'multiqc_report'})
  ## PIPELINE
  load_multiqc_html >> upload_multiqc_to_box
  ## TASK
  update_analysis_and_status = \
    PythonOperator(
      task_id='update_analysis_and_status',
      dag=dag,
      queue='hpc_4G',
      python_callable=change_pipeline_status,
      trigger_rule='none_failed_or_skipped',
      params={
        'new_status': 'FINISHED',
        'no_change_status': 'SEEDED'})
  ## PIPELINE
  upload_multiqc_to_ftp >> update_analysis_and_status
  upload_scanpy_report_for_sc_5p_to_ftp >> update_analysis_and_status
  upload_scanpy_report_for_sc_5p_to_box >> update_analysis_and_status
  upload_cellbrowser_for_sc_5p_to_ftp >> update_analysis_and_status
  #upload_scirpy_report_for_vdj_to_ftp >> update_analysis_and_status            # no more ambiguous VDJ
  #upload_scirpy_report_for_vdj_to_box >> update_analysis_and_status
  upload_scirpy_report_for_vdj_b_to_ftp >> update_analysis_and_status
  upload_scirpy_report_for_vdj_b_to_box >> update_analysis_and_status
  upload_scirpy_report_for_vdj_t_to_ftp >> update_analysis_and_status
  upload_scirpy_report_for_vdj_t_to_box >> update_analysis_and_status
  upload_seurat_report_for_sc_5p_ftp >> update_analysis_and_status
  upload_seurat_report_for_sc_5p_to_box >> update_analysis_and_status
  upload_cellranger_results_to_irods >> update_analysis_and_status
  upload_cellranger_report_to_ftp >> update_analysis_and_status
  upload_cellranger_report_to_box >> update_analysis_and_status
  upload_cram_to_irods >> update_analysis_and_status
  upload_scvelo_report_to_box >> update_analysis_and_status
  upload_scvelo_report_to_ftp >> update_analysis_and_status
  ## TASK
  update_qc_pages = \
    PythonOperator(
      task_id='update_qc_pages',
      dag=dag,
      queue='hpc_4G',
      python_callable=create_and_update_qc_pages,
      params={
        'use_ephemeral_space': True,
        'collection_type_list': [
          'FTP_MULTIQC_HTML',
          'FTP_SEURAT_HTML',
          'FTP_SCIRPY_VDJ_T_HTML',
          'FTP_SCIRPY_VDJ_B_HTML',
          'FTP_SCIRPY_VDJ_HTML',
          'FTP_CELLBROWSER',
          'FTP_SCANPY_HTML',
          'FTP_SCVELO_HTML',
          'FTP_CELLRANGER_HTML']})
  ## PIPELINE
  update_analysis_and_status >> update_qc_pages