Last updated: 2019-11-21
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Knit directory: Comparative_APA/analysis/
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File | Version | Author | Date | Message |
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Rmd | 9fbd1fe | brimittleman | 2019-11-21 | figure out sample swap |
html | 40db68c | brimittleman | 2019-11-20 | Build site. |
Rmd | 7c206f8 | brimittleman | 2019-11-20 | add extra QC anaylsis |
I have two samples that are not making a lot of sense. They cluster in the raw data by speices but in the normalized data they switch sides. Also removing these samples greatly improves the DE analysis. I want to make sure these are not switched samples. To test this I will map 4973 to the human genome and 18498 to the chimp genome. I can run verify bam id to see if 4973 maps well to a human.
mkdir ../data/TwoBadSampleAnalysis
sbatch MapBadSamples.sh
sbatch SortIndexBadSamples.sh
sbatch verifyBam4973inHuman.sh
4973 verifies as 18498….
Look at rate of mismatch per base.
18498: human: 0.87% chimp: 0.14%
4973: human: 0.16% chimp:0.84%
This is a sample swap. FIX AND RERUN!
sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.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
loaded via a namespace (and not attached):
[1] workflowr_1.5.0 Rcpp_1.0.2 digest_0.6.18 later_0.7.5
[5] rprojroot_1.3-2 R6_2.3.0 backports_1.1.2 git2r_0.26.1
[9] magrittr_1.5 evaluate_0.12 stringi_1.2.4 fs_1.3.1
[13] promises_1.0.1 whisker_0.3-2 rmarkdown_1.10 tools_3.5.1
[17] stringr_1.3.1 glue_1.3.0 httpuv_1.4.5 yaml_2.2.0
[21] compiler_3.5.1 htmltools_0.3.6 knitr_1.20