Ocular Microbiome Project Scripts

Author: Daniela Puiu
Date: 2024/07/23
OS: Linux

Purpose: align sequence samples to 2 different human reference 
      genomes and remove the aligned reads, leaving only the 
      unmapped ones

Config

# get server name
cat /etc/hostname

# check generic init file
cat init.sh
  export REF1=path/Ref/T2T-chm13v2.0
  export REF2=path/Ref/hs38DH
  export KRAKENDB=path/krakendb-2023-08-08-MICROBIAL/
  export BRAKENDB=path/krakenuniq_db_MICROBIAL_20230808/
  export P=8

# set server name(Ex: pathology/sciserver/salz)
SERVER=pathology

# edit/init environment
nano init.$SERVER.sh
. ./init.$SERVER.sh  

Align reads to the human reference genome

# input:   REF1,REF2 FASTA indexed
# input:   sample FASTA/FASTQ[.gz] file(s)
# output:  sample unmapped FASTA.gz file

Single sample using minimap2

# unmated
ls $QRY_SEQ_FILE
minimap2.sh $SAMPLE_ID $QRY_SEQ_FILE  $OUT_PREFIX
ls $OUT_PREFIX.*

#mated
ls $QRY_SEQ_FILE1 $QRY_SEQ_FILE2
minimap2.sh $SAMPLE_ID $QRY_SEQ_FILE1 $QRY_SEQ_FILE2 $OUT_PREFIX
ls $OUT_PREFIX.*

Single sample using bowtie2

# unmated vs mated
bowtie2.sh $SAMPLE_ID $QRY_SEQ_FILE  $OUT_PREFIX
bowtie2.sh $SAMPLE_ID $QRY_SEQ_FILE1 $QRY_SEQ_FILE2 $OUT_PREFIX

Multiple samples using minimap2

# input: METADATA file; sample names must be in 1st column
META=metadata.{tab,csv,tsv}  
head $META  

# input:   FASTA/FASTQ[.gz] file(s)
ls fastq/

# run minimap2
minimap2.all.sh $META

# output:  unmapped FASTA.gz and count file
ls minimap2/