Last updated: 2021-02-15

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Knit directory: Mouse_AAV_PGR_RNAseq_bulk/

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Introduction

Following sequencing and obtaining .fastq.gz file, the first step is to perform trimming and mapping of the sequencing data to generate bam files. All these steps were performed using bash code.

Bam files were then used for read counts to generate a count matrix.

Mouse AAV-PGR bulk RNA-seq were performed using paiered end sequencing method and below are the scripts for trimming and mapping paired end sequencing read.

Used libraries and functions

  • skewer/0.2.2
  • star/2.5.3a
  • samtools/1.8
  • parallel
  • subread/1.5.0

Trimming of sequencing read

#!/bin/bash

# function to run skewer quality trimming
runskew(){
FQZ1=$1
FQZ2=`echo $FQZ1 | sed 's/_R1.fastq.gz/_R2.fastq.gz/'`
skewer -t 8 -q 20 $FQZ1 $FQZ2
}
export -f runskew

# actually run skewer
parallel -j3 runskew ::: *_R1.fastq.gz

Mapping of Skewer trimmed .fastq to mouse reference genome

It will generate the following 4 outputs for individual .fastq.gz file:

  1. .STAR.bam
  2. .STAR.bam.bai
  3. .STAR.bam.stats
  4. _starlog.txt

#!/bin/bash

DIR=/group/card2/Evangelyn_Sim/Sequencing_ATAC_RNA/refgenome/star
GTF=/group/card2/Evangelyn_Sim/Sequencing_ATAC_RNA/refgenome/Mus_musculus.GRCm38.96.gtf

for FQ1 in `ls *1.fastq-trimmed-pair1.fastq` ; do
    FQ2=`echo $FQ1 | sed 's/1.fastq-trimmed-pair1.fastq/1.fastq-trimmed-pair2.fastq/'`
    BASE=`echo $FQ1 | sed 's/_1.fastq-trimmed-pair1.fastq//'`

STAR --genomeLoad NoSharedMemory --genomeDir $DIR --readFilesIn $FQ1 $FQ2 --runThreadN 30 \
--sjdbGTFfile $GTF --outSAMattributes NH HI NM MD

rm $FQ1 $FQ2
mv Aligned.out.sam ${BASE}.STAR.sam
mv Log.final.out ${BASE}_starlog.txt

( samtools view -uSh ${BASE}.STAR.sam | samtools sort -o ${BASE}.STAR.bam
rm ${BASE}.STAR.sam
samtools index ${BASE}.STAR.bam
samtools flagstat ${BASE}.STAR.bam > ${BASE}.STAR.bam.stats ) &

done

STAR genomeLoad Remove --genomeDir $DIR
wait
ls: cannot access *1.fastq-trimmed-pair1.fastq: No such file or directory
bash: line 24: STAR: command not found

Merge bam files

Make a directory called “merged” and ln all .bam files to the folder and perform the following.

#!/bin/bash

samtools view -H `ls *bam | head -1` > header.sam
for BASE in `ls *bam | cut -d '_' -f2 | sort -u ` ; do
  rm $BASE.mg.bam
  samtools merge -h header.sam $BASE.mg.bam *${BASE}*bam &
done
wait
ls: cannot access *bam: No such file or directory
bash: line 2: samtools: command not found
ls: cannot access *bam: No such file or directory

Counting reads from bam files across mouse reference genome


#!/bin/bash

SAF=/group/card2/Evangelyn_Sim/Sequencing_ATAC_RNA/refgenome/Mus_musculus.GRCm38.96.fulllength.saf
OUT=mrna_fulllen_pe_strrev_q30.mx

#featureCounts -p -Q 30 -T 20 -s 2 -a $SAF -F SAF -o $OUT *bam

Tidy counted matrix


#!/bin/bash

for MX in `ls *mx` ; do
   sed 1d $MX | sed 's/.mg.bam//g' > $MX.all
   sed 1d $MX | cut -f1-6 | sed 's/.mg.bam//g' > $MX.chr
   sed 1d $MX | cut -f1,7- | sed 's/.mg.bam//g' > $MX.PR.fix


done
wait
ls: cannot access *mx: No such file or directory

Filter out low counts genes from matrix

Filtering out low counts genes by running the following filter.sh as

bash filter.sh hrna_dev_mf_fulllen_se_strrev_q30.mx.all.fix

filter.sh

head -1 $1 > ${1}_filt
awk '{
  min = max = sum = $2;       # Initialize to the first value (2nd field)
  sum2 = $2 * $2              # Running sum of squares
  for (n=3; n <= NF; n++) {   # Process each value on the line
    if ($n < min) min = $n    # Current minimum
    if ($n > max) max = $n    # Current maximum
    sum += $n;                # Running sum of values
    sum2 += $n * $n           # Running sum of squares
  }
  print sum/(NF-1) ;
}' $1 > avg
paste avg $1 | awk '$1 >= 10' | cut -f2- | tr ' ' '\t' >> ${1}_filt
rm avg

Mapping of Skewer trimmed .fastq to human reference genome

To confirm the expression of AAV-PGR (human isoform), Skewer trimmed reads also mapped to human reference genome and later counted.

#!/bin/bash
DIR=/group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/refgenome/star
GTF=/group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/refgenome/star/Homo_sapiens.GRCh38.96.gtf

for FQ1 in `ls *1.fastq-trimmed-pair1.fastq` ; do
    FQ2=`echo $FQ1 | sed 's/1.fastq-trimmed-pair1.fastq/1.fastq-trimmed-pair2.fastq/'`
    BASE=`echo $FQ1 | sed 's/_1.fastq-trimmed-pair1.fastq//'`

STAR --genomeLoad NoSharedMemory --genomeDir $DIR --readFilesIn $FQ1 $FQ2 --runThreadN 30 \
--sjdbGTFfile $GTF --outSAMattributes NH HI NM MD

rm $FQ1 $FQ2
mv Aligned.out.sam ${BASE}.STAR.sam
mv Log.final.out ${BASE}_starlog.txt

( samtools view -uSh ${BASE}.STAR.sam | samtools sort -o ${BASE}.STAR.bam
rm ${BASE}.STAR.sam
samtools index ${BASE}.STAR.bam
samtools flagstat ${BASE}.STAR.bam > ${BASE}.STAR.bam.stats ) &

done

STAR genomeLoad Remove --genomeDir $DIR
wait
ls: cannot access *1.fastq-trimmed-pair1.fastq: No such file or directory
bash: line 22: STAR: command not found

Counting reads from bam files across human reference genome


#!/bin/bash

SAF=/group/card2/Evangelyn_Sim/Transcriptome_chromatin_human/Sequencing_ATAC_RNA/refgenome/Homo_sapiens.GRCh38.96.fulllength.saf
OUT=mrna_fulllen_pe_strrev_q30_map2human.mx

#featureCounts -p -Q 30 -T 20 -s 2 -a $SAF -F SAF -o $OUT *bam

sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)

Matrix products: default
BLAS:   /hpc/software/installed/R/3.6.1/lib64/R/lib/libRblas.so
LAPACK: /hpc/software/installed/R/3.6.1/lib64/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.5       rstudioapi_0.11  whisker_0.4      knitr_1.30      
 [5] magrittr_1.5     R6_2.5.0         rlang_0.4.7      stringr_1.4.0   
 [9] tools_3.6.1      xfun_0.18        git2r_0.27.1     htmltools_0.5.0 
[13] ellipsis_0.3.1   rprojroot_1.3-2  yaml_2.2.1       digest_0.6.27   
[17] tibble_3.0.3     lifecycle_0.2.0  crayon_1.3.4     later_1.1.0.1   
[21] vctrs_0.3.2      promises_1.1.1   fs_1.5.0         glue_1.4.2      
[25] evaluate_0.14    rmarkdown_2.5    stringi_1.5.3    compiler_3.6.1  
[29] pillar_1.4.6     backports_1.1.10 httpuv_1.5.4     pkgconfig_2.0.3