AlanFung:LabNotes/2015/2015-7-14

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Revision as of 19:04, 14 July 2015 by >Alan6017518 (→‎Swift vs. Kapa)
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Swift vs. Kapa

  • We are interested in the performance of the Swift Bioscience Methyl-Seq DNA library kit
  • Since we have WGB libraries made using Kapa we can compare swift against it.
  • 2nd Experiment was done by Noi (Kapa Hyper Lib. Prep + Seqcap) on
  • 2nd Data analysis was done by Dinh
  • 3rd Experiment was done by me (Kapa Hyper Lib. Prep + Seqcap-optimized) on AlanFung:LabNotes/2015/2015-1-15
  • 3rd Data analysis was done by Dr. Zhang

Summary

Experiment Person Capture Date Lib Prep Capture Conclusion
1 Noi 141104 Tang SeqCap lower complexity and higher clonal rates due to Tang et assumption the DNA fragment ends
2 Noi 141225 Kapa Hyper SeqCap lower specificity and enrichment due to capture condition
3 Alan 150115 Kapa Hyper SeqCap Mapping rates, library complexity and capture specificity is high
4 Alan 150714 Swift ? ?

Samples

  • We only have 12 reactions from the swift methyl-seq kit and Dana needs to use it for her project so I can work on 4 samples.
  • I am going to pick 1x tumor 2x plasma sample and 1x NC plasma
  • I will pick the ones that have relatively low % trimmed (percentage of adapters being trimmed) and high % mapped rate from 2nd capture.
  • I will pick the ones with high % on target and low % clonal from 3rd capture.
SAMPLE ID Total PE reads Total reads Total reads after trimming Total mapped reads %trimmed %mapped      
6T-2_map 7,489,616 14,979,232 14,638,550 12,820,323 2% 88%      
                   
Sample N_mapped_reads N_non-clonal_reads N_on-target_reads N_non-clonal_on-target_reads N_on-target_haplotypes N_target_coverred Pct_on-target Pct_clonal Enrichment_factor
6P-3 28,124,349 27,174,711 20,126,384 19,455,168 7,299,019 48,605 71.60% 3.40% 254
PCP-3 9,225,527 9,067,481 6,226,370 6,133,490 1,984,048 47,803 67.50% 1.70% 210
NC-30 15,359,075 13,957,906 9,350,399 8,223,219 3,641,546 45,664 60.90% 9.10% 157