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== Performing filters == === Filter for high quality probes === * High quality probes has fewer CGs on capture arms AND map uniquely to the target region. (Ignore alignments to multiple chromosomes and > 10 kbp apart). * First, since some of the batches were ran using maxCG = 6, we need to filter out the ones with more than 2 CGs on both arms. 857,865 probes generated 856,510 probes with maxCG=2 on both arms (107,321 / 147,016 = 73% of target coverage) * Next, generate the cg info for each probe: /home/ddiep/scripts/probesCGinfo.pl < all_probes_filtered > all_probes_cg_info * Next, make h1.fa and h2.fa for each probe & map using bowtie /home/ddiep/scripts/probes2PairedFA.pl < all_probes_cg_info This will make: ProbeSeqL.fa ProbeSeqR.fa * Next, copy the .fa file to tscc and map with bowtie2 to the reference genome with this master script (getPairs.sh) <nowiki>bowtie2="/home/ddiep/softwares/bowtie2-2.1.0/bowtie2" ref_dir="/oasis/tscc/scratch/ddiep/bisHg19" cur_dir="/oasis/tscc/scratch/ddiep/Working/Map2" email="diep.hue.dinh@gmail.com" split -l 10000 ProbeSeqL.fa sub_ProbeSeqL_ split -l 10000 ProbeSeqR.fa sub_ProbeSeqR_ for f in sub_ProbeSeqL_* do g=`echo $f | sed 's/L/R/g'` echo "#!/bin/csh" > $f.job echo "#PBS -q small" >> $f.job echo "#PBS -l nodes=1:ppn=4" >> $f.job echo "#PBS -l walltime=4:00:00" >> $f.job echo "#PBS -o $f.log" >> $f.job echo "#PBS -e $f.err" >> $f.job echo "#PBS -V" >> $f.job echo "#PBS -M $email" >> $f.job echo "#PBS -m abe" >> $f.job echo "#PBS -A k4zhang-group" >> $f.job echo "cd /state/partition1/\$USER/\$PBS_JOBID" >> $f.job echo "$bowtie2 -p 4 -f --very-sensitive-local -k 1000 -x $ref_dir/hg19.bis.GA.bowtie -1 $cur_dir/$f -2 $cur_dir/$g -S $f.outRev.sam" >> $f.job echo "$bowtie2 -p 4 -f --very-sensitive-local -k 1000 -x $ref_dir/hg19.bis.CT.bowtie -1 $cur_dir/$f -2 $cur_dir/$g -S $f.outFwd.sam" >> $f.job echo "cp *sam $cur_dir/" >> $f.job #getpaired echo "less $cur_dir/$f.outFwd.sam $cur_dir/$f.outRev.sam | /home/ddiep/scripts/probesCheck.pl > $f.paired.txt" >> $f.job echo "cp $f.paired.txt $cur_dir/" >> $f.job qsub -q hotel $f.job done </nowiki> * From the *.paired.txt outputs, generate keep.pairs.txt: cat *paired.txt | awk '{if($5 < 10000 && $5 > -10000) print $0}' > keep.pairs.txt * Copy keep.pairs.txt back to genome miner, tabulate the accepted hits, and generate a unique.pairs.txt file: cut -f 1 keep.pairs.txt | /home/ddiep/scripts/tabulateList.pl > count.pairs.txt awk '{if($2==1) print $0}' count.pairs.txt | sed 's/|/\t/g' | cut -f 5 > unique.pairs.txt * unique.pairs.txt contains the uniquely aligned probes id and can be used to extract the unique probes records: /home/ddiep/scripts/extractBowtieKeepPairs.pl unique.pairs.txt < all_probes_cg_info > all_probes_cg_info_unique_pairs: 749,801 all_probes_cg_info_unique_pairs * separate out probes with cg(s) in 1 arm and cgs in 2 arms. awk '{if($7 !~ /C/ || $9 !~ /C/) print $0}' all_probes_cg_info_unique_pairs > probes_max1arm_cg_info awk '{if($7 ~ /C/ && $9 ~ /C/) print $0}' all_probes_cg_info_unique_pairs > probes_2arms_cg_info * Number of probes in each file: 2,355 probes_2arms_cg_info 747,446 probes_max1arm_cg_info (104,211 / 147,016 = 71% of target coverage) === Obtain informative probes === * Informative probes has at least 3 CpGs in the target region (~300bp long) AND minimum CV of 0.2 (before we used 0.40, but since we have fewer probes from this iteration, I used a less stringent requirement). * Informative probes cover all RefSeq genes (try to get >99%). * First, filtered informative probes using min 3 CGs and min 0.2 CV requirement. 375,011 probes ( 85,625 / 147,016 = 58% of target coverage) * Since we have a lot of freed up space, try to get 100% coverage of transcript TSS region (TSS200 or TSS1500) 22,895 gene probes added 15,000 high CV probes from TFBS/DHS/SE overlapping regions.
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