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Last updated: 2020-12-03

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Knit directory: Proteomics/analysis/

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File	Version	Author	Date	Message
html	b8e0823	Junyan Lu	2020-03-10	Build site.
html	96bcb9e	Junyan Lu	2020-03-10	Build site.
Rmd	4045ee2	Junyan Lu	2020-03-10	update analysis
html	4045ee2	Junyan Lu	2020-03-10	update analysis
Rmd	c7747b2	Junyan Lu	2020-03-10	update analysses
Rmd	b688c41	Junyan Lu	2020-02-27	wflow_git_commit(all = TRUE)
html	b688c41	Junyan Lu	2020-02-27	wflow_git_commit(all = TRUE)
html	46534c2	Junyan Lu	2020-02-27	Build site.
Rmd	2b8852e	Junyan Lu	2020-02-27	wflow_publish(list.files("./", pattern = "Rmd"))
html	cc8c163	Junyan Lu	2020-02-27	Build site.
Rmd	16b2ddd	Junyan Lu	2020-02-27	wflow_git_commit(all = TRUE)
Rmd	aabea73	Junyan Lu	2020-02-27	Start workflowr project.

Figures for the manuscript

Reports for CLL proteomic project

Raw data processing

Quality control

Integrative analysis

Assocation between genomic aberrations and protein expression

Blocking for IGHV and trisomy12 to avoid potential confounding effect
No blocking, only univariate model for testing
Associations in M-CLL samples, without blocking
Associations in U-CLL samples, without blocking
Associations using new timsTOF dataset
Associations using new timsTOF+Hela dataset
Comment: In my opinion, blocking for IGHV and trisomy12 is still the right way to go. Quite a few variations show imbalanced distributions among IGHV and trisomy12 groups. And based on the tests, blocking doesn't really reduce the sensitivity

Other associations

Protein complex analysis

Evaluation of the hypothesis underlying protein complex detection algorithms

Complex analysis using complex detection algorithms

Differential complex regulations related to trisomy12
Differential complex regulations related to IGHV status
(I would not rely on the results from the two analyses above, based on the reasons mentioned in the hypothesis evaluation report)

Protein complex analysis using an alternative approach

Protein complex analysis related to trisomy12
Protein complex analysis related to IGHV status
(I suggest using results from those two analysis above in the manuscript)

Copy number changes and gene dosage effect analysis

Proteomic markers for drug responses

Analysis on 1000CPS dataset
Analysis on IC50 dataset
(I recommend using 1000CPS for the manuscript, as there are more overlapped samples and thus higher statistical power)