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====Mapping summary==== *All 16 sequencing libraries were sequenced in a PE150bp MiSeq run: /home/kunzhang/seqStore/131227_MiSeq_GP1 *Pre-processing of sequencing reads: the 6bp UMI in each of the Read 1 is extracted and placed in the read name, then 27bp of the 5'-ends (corresponding to H1&H2) were trimmed off from Read 1 and Read 2. ./[[Media:extract_UMI_PE.txt|extract_UMI_PE.pl]] *The reads were then mapped by [[Media:bisReadMapperPE19.txt|bisReadMapperPE19.pl]], and the bam files were used for haplotype analysis. The 400bp probe set had very poor capture, so the following analysis focus on the data generated with the 150bp probe set (GP1_V4). {| {{table}} | align="center" style="background:#f0f0f0;"|'''Sample''' | align="center" style="background:#f0f0f0;"|'''raw reads''' | align="center" style="background:#f0f0f0;"|'''mapped reads''' | align="center" style="background:#f0f0f0;"|'''on-target reads''' | align="center" style="background:#f0f0f0;"|'''mapping rate''' | align="center" style="background:#f0f0f0;"|'''specificity''' | align="center" style="background:#f0f0f0;"|'''# CpG called''' |- | BE2C_V4||1,386,590||915,834||862,623||62.21%||94.19%||31,853 |- | BE2C_V6||2,933,904||489,918||38,994||1.33%||7.96%||28,819 |- | BXPC3_V4||1,805,276||1,256,196||1,232,955||68.30%||98.15%||36,528 |- | BXPC3_V6||2,753,274||376,020||24,332||0.88%||6.47%||18,885 |- | PANC1_V4||1,264,618||807,262||763,920||60.41%||94.63%||32,712 |- | PANC1_V6||2,522,344||386,410||29,667||1.18%||7.68%||22,154 |- | T98G_V4||1,803,782||1,125,066||1,107,621||61.41%||98.45%||37,906 |- | T98G_V6||3,151,530||478,980||30,172||0.96%||6.30%||27,995 |- | U87MG_V4||1,586,144||1,047,246||1,011,039||63.74%||96.54%||34,562 |- | U87MG_V6||2,856,720||419,040||40,911||1.43%||9.76%||26,848 |- | UCLA-SZ_B1_V4||1,427,496||774,492||713,916||50.01%||92.18%||29,093 |- | UCLA-SZ_B1_V6||2,173,094||374,268||21,959||1.01%||5.87%||21,690 |- | UCLA-SZ_D1_V4||1,409,960||523,588||472,779||33.53%||90.30%||26,859 |- | UCLA-SZ_D1_V6||1,125,166||136,234||5,584||0.50%||4.10%||8,815 |- | UCLA-SZ_H11_V4||1,574,628||643,542||583,033||37.03%||90.60%||29,864 |- | UCLA-SZ_H11_V6||2,165,268||268,476||15,822||0.73%||5.89%||16,206 |- | |} I used our standard pipeline to create a methylation matrix, and did a hierarchical clustering. [[Image:131227_MiSeq_8_sample_V4_clustering.png|300px]] Clearly, all samples cluster as expect (3 blood in one group, two PC (BXPC3, PANC1) lines in the second, and three GBM lines (U87, T98G, BE2_C) in the third.
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