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Kun:LabNotes/Haplotyping/2011-9-7
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==Haplotyping data analysis== *Rui&Matt lysed GM12878 cells, and made dilution to ~8 chrosomes per aliquot, then performed tagmentation followed by PCR with indexing primers. Rui prepared 24 libraries (one failed) and Matt prepared 12 libraries (one failed). Each mixture of 12 libraries was sequenced in two lanes (HL101, 60bp+index): [[Rui_Liu#Haplotyping_samples|Lab notes]]. ===Mapping=== *I processed 12 data sets in a batch. less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx1.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx1.txt.gz > s12_Indx1.fq less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx2.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx2.txt.gz > s12_Indx2.fq less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx3.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx3.txt.gz > s12_Indx3.fq less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx4.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx4.txt.gz > s12_Indx4.fq less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx5.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx5.txt.gz > s12_Indx5.fq less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx6.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx6.txt.gz > s12_Indx6.fq less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx7.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx7.txt.gz > s12_Indx7.fq less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx8.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx8.txt.gz > s12_Indx8.fq less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx9.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx9.txt.gz > s12_Indx9.fq less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx10.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx10.txt.gz > s12_Indx10.fq less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx11.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx11.txt.gz > s12_Indx11.fq less /home/kunzhang/SeqStore/110902_HL101/s_1_Indx12.txt.gz /home/kunzhang/SeqStore/110902_HL101/s_2_Indx12.txt.gz > s12_Indx12.fq fastq2variants.pl s12_Indx1.fq 60 > s_12_Indx1.log fastq2variants.pl s12_Indx2.fq 60 > s_12_Indx2.log fastq2variants.pl s12_Indx3.fq 60 > s_12_Indx3.log fastq2variants.pl s12_Indx4.fq 60 > s_12_Indx4.log fastq2variants.pl s12_Indx5.fq 60 > s_12_Indx5.log fastq2variants.pl s12_Indx6.fq 60 > s_12_Indx6.log fastq2variants.pl s12_Indx7.fq 60 > s_12_Indx7.log fastq2variants.pl s12_Indx8.fq 60 > s_12_Indx8.log fastq2variants.pl s12_Indx9.fq 60 > s_12_Indx9.log fastq2variants.pl s12_Indx10.fq 60 > s_12_Indx10.log fastq2variants.pl s12_Indx11.fq 60 > s_12_Indx11.log fastq2variants.pl s12_Indx12.fq 60 > s_12_Indx12.log *Then I used samtools to get the read counts for each data set: /home/kunzhang/softwares/samtools-0.1.12a/samtools view -c s12_Indx1.fq.bowtie.sorted.bam /home/kunzhang/softwares/samtools-0.1.12a/samtools view -c s12_Indx1.fq.bowtie.sorted.unique.bam [[Image:Haplotyping_HL101_library_complexity.png]] **We got an average of 3.5 millions reads (median 3.5M) per library, and the average unique reads per library is ~250k (median 117k). This is roughly twice as high as the 12 libraries Rui did in June, which could be due to the use of protease digestion after tagmentation. **With the combination of 34 libraries (equivalent to 6 cells), we have 8.5 millions of unique 60bp reads, which cover 500Mb (or 1/6) of the human genome. **If we obtain PE100bp reads, we would cover roughly half of the human genome with the same set of libraries. **To obtain 1X coverage of the genome, we need PE100bp reads on ~80 of such libraries. ===Variant calling and visualization of haplotypes=== *Compare the alleles called from each file with the GM12878 reference haplotype using [[Media:pileupVsRefHap.txt|pileupVsRefHap.pl]]: [[Media:idioGraphic_batch_commands.txt|batch commands]]. *Visualize the parental alleles with [http://www.ncrna.org/idiographica Idiographica]. [[Image:RuiA_Indx1_idioGraph.png|600px]][[Image:RuiA_Indx2_idioGraph.png|600px]] [[Image:RuiA_Indx3_idioGraph.png|600px]][[Image:RuiA_Indx4_idioGraph.png|600px]] [[Image:RuiA_Indx5_idioGraph.png|600px]][[Image:RuiA_Indx6_idioGraph.png|600px]] [[Image:RuiA_Indx7_idioGraph.png|600px]][[Image:RuiA_Indx8_idioGraph.png|600px]] [[Image:RuiA_Indx9_idioGraph.png|600px]][[Image:RuiA_Indx10_idioGraph.png|600px]] [[Image:RuiA_Indx11_idioGraph.png|600px]][[Image:RuiA_Indx12_idioGraph.png|600px]] [[Image:RuiB_Indx1_idioGraph.png|600px]][[Image:RuiB_Indx2_idioGraph.png|600px]] [[Image:RuiB_Indx3_idioGraph.png|600px]][[Image:RuiB_Indx4_idioGraph.png|600px]] [[Image:RuiB_Indx5_idioGraph.png|600px]][[Image:RuiB_Indx6_idioGraph.png|600px]] [[Image:RuiB_Indx7_idioGraph.png|600px]][[Image:RuiB_Indx8_idioGraph.png|600px]] [[Image:RuiB_Indx10_idioGraph.png|600px]] [[Image:RuiB_Indx11_idioGraph.png|600px]][[Image:RuiB_Indx12_idioGraph.png|600px]] [[Image:Matt_Indx1_idioGraph.png|600px]][[Image:Matt_Indx2_idioGraph.png|600px]] [[Image:Matt_Indx3_idioGraph.png|600px]][[Image:Matt_Indx4_idioGraph.png|600px]] [[Image:Matt_Indx5_idioGraph.png|600px]][[Image:Matt_Indx6_idioGraph.png|600px]] [[Image:Matt_Indx8_idioGraph.png|600px]] [[Image:Matt_Indx9_idioGraph.png|600px]][[Image:Matt_Indx10_idioGraph.png|600px]] [[Image:Matt_Indx11_idioGraph.png|600px]][[Image:Matt_Indx12_idioGraph.png|600px]] *Some really promising ones include RuiA: Indx5, 6, 8; RuiB: Indx4, 8; Matt: Indx3, 4, 5, 7. *The question is how to call haplotypes on samples without references. ===How to further improve?=== #Pre-amplification using a single primer targeting the transposon recognition sequence, so that all A-A, A-B, B-B fragments can be captured. #Use metaphase-blocked cells to increase the average fragment size of DNA molecules. #Develop a QPCR assay to estimate the complexity of the libraries without Illumina sequencing. The key is to establish a reference library of known quantity, dilute the library to different levels (250k molecules, 500k molecules, 1M molecules, 2M molecules), and include these diluted libraries as the standards for the post-tagmentation PCR.
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