RNAseq pipeline: Difference between revisions

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(Created page with "==TSCC pipeline for single-cell RNAseq analysis== ===Smart-seq pipeline=== *This pipeline is designed for mapping and transcript quantification of Smart-seq data. *It assumes ...")
 
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*We are currently using hg19 for human and mm10 for mouse. LifeTech's ERCC transcripts were included. For transcript models, we are using GENCODE V14 for human, and UCSC Genes for mouse.
*We are currently using hg19 for human and mm10 for mouse. LifeTech's ERCC transcripts were included. For transcript models, we are using GENCODE V14 for human, and UCSC Genes for mouse.
*We use one script to submit jobs for all samples in one folder, one job per sample. Here is how to start the job.
*We use one script to submit jobs for all samples in one folder, one job per sample. Here is how to start the job.
    # First, copy the job submission script to your own path, such as your HOME/bin
    # First, copy the job submission script to your own path, such as your HOME/bin
     cp /home/k4zhang/bin/batch_STAR_cufflink2_mm10.pl MY_HOME/bin
     cp /home/k4zhang/bin/batch_STAR_cufflink2.pl MY_HOME/bin
    # Next edit this script, replace the email address "kun.zhang.ucsd@gmail.com" with your own address.  
    # Next edit this script, replace the email address "kun.zhang.ucsd@gmail.com" with your own address.  
    # This only need to be done once. For human data, use batch_STAR_cufflink2_hg19.pl
    # This only need to be done once.  
    # As a rehearsal, you can copy two test data sets to your own folder.
    # As a rehearsal, you can copy two test data sets to your own folder.
     cp /home/k4zhang/my_oasis_tscc/test_data MY_FOLDER
     cp /home/k4zhang/my_oasis_tscc/test_data MY_FOLDER
    # Now you can change to this folder.
    # Now you can change to this folder.
     cd MY_FOLDER
     cd MY_FOLDER
    # Then you can submit all the jobs to process the samples in this folder
    # Then you can submit all the jobs to process the samples in this folder.
     batch_STAR_cufflink2_mm10.pl
    # For human data, replace mm10 with hg19.
    # To check the status, use qstat
     batch_STAR_cufflink2.pl mm10
    # To check the status, use qstat.
    # You should also receive emails when the jobs are started or completed.
     qstat | grep YOUR_USER_NAME
     qstat | grep YOUR_USER_NAME
    # The results are in xxx_mapped folder (one folder per sample).

Revision as of 04:31, 31 October 2013

TSCC pipeline for single-cell RNAseq analysis

Smart-seq pipeline

  • This pipeline is designed for mapping and transcript quantification of Smart-seq data.
  • It assumes that the data cover the full length of the transcripts, and have no strand specificity.

Pipeline A.

  • This pipeline uses Tophat2 and Cufflink2.

Pipeline B.

  • This pipeline uses STAR and Cufflink2 (much faster, but requires more RAM, doesn't work on genome-miner).
  • The input data files should follow the SOP of UCSD SCAP center. Basically, all PE gzip compressed fastq files for one cell are stored in one folder (the name starts with Sample_). One folder per cell or sequencing library.
  • We are currently using hg19 for human and mm10 for mouse. LifeTech's ERCC transcripts were included. For transcript models, we are using GENCODE V14 for human, and UCSC Genes for mouse.
  • We use one script to submit jobs for all samples in one folder, one job per sample. Here is how to start the job.
    # First, copy the job submission script to your own path, such as your HOME/bin
   cp /home/k4zhang/bin/batch_STAR_cufflink2.pl MY_HOME/bin
    # Next edit this script, replace the email address "kun.zhang.ucsd@gmail.com" with your own address. 
    # This only need to be done once. 
    # As a rehearsal, you can copy two test data sets to your own folder.
   cp /home/k4zhang/my_oasis_tscc/test_data MY_FOLDER
    # Now you can change to this folder.
   cd MY_FOLDER
    # Then you can submit all the jobs to process the samples in this folder. 
    # For human data, replace mm10 with hg19.
   batch_STAR_cufflink2.pl mm10
    # To check the status, use qstat. 
    # You should also receive emails when the jobs are started or completed.
   qstat | grep YOUR_USER_NAME
    # The results are in xxx_mapped folder (one folder per sample).