GSE40651 Processing Pipeline

Publication

Nature neuroscience (2012) — PMID 23023293

Dataset

Divergent roles of ALS-linked proteins FUS/TLS and TDP-43 intersect in processing long pre-mRNAs (CLIP-Seq)

1. 1

   Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence, then mapped to mm9 or hg18 whole genome using bowtie v0.12.2 with parameters -q -p 4 -e 100 -y -a -m 10 --best --strata

   Bowtie v0.12.2 GitHub

   $ Bash example

   # Install Bowtie (if not already installed)
   # conda install -c bioconda bowtie=0.12.2
   
   # --- Pre-processing Step (described but not part of Bowtie command) ---
   # Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence.
   # This step is assumed to have been completed, producing 'trimmed_masked_reads.fastq'.
   # -------------------------------------------------------------------
   
   # Define input reads and output SAM file
   INPUT_READS="trimmed_masked_reads.fastq"
   OUTPUT_SAM="mapped_reads.sam"
   
   # Define the reference genome to use (choose either mm9 or hg18)
   # For example:
   REFERENCE_GENOME="mm9"
   # REFERENCE_GENOME="hg18"
   
   # Define the base path to the Bowtie index files for the chosen genome.
   # Replace '/path/to/bowtie_indexes/' with the actual directory where your Bowtie indexes are stored.
   # For example, if your mm9 index files are named mm9.1.ebwt, mm9.2.ebwt, etc.,
   # then BOWTIE_INDEX_BASE should be '/path/to/bowtie_indexes/mm9'.
   BOWTIE_INDEX_BASE="/path/to/bowtie_indexes/${REFERENCE_GENOME}"
   
   # Execute Bowtie mapping
   bowtie -q -p 4 -e 100 -y -a -m 10 --best --strata "${BOWTIE_INDEX_BASE}" "${INPUT_READS}" > "${OUTPUT_SAM}"

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