stas$cal(analysis(with( msstats( - dia/swath...

Sta$s$cal analysis with MSstats

Meena Choi

Department of Sta$s$cs

2013.07.18

Agenda

2 SRM course 2013 : Sta$s$cal analysis with MSstats

•  What is MSstats? •  How to analyze using MSstats in Skyline •  Study of poor quality of peaks •  R-‐based plaLorm takes advantage of more op$ons and modifies easily.

R and MSstats

3

1.  Test proteins for differen$al abundance 2.  Quan$fy proteins in biological samples 3.  Design of future experiment

R Package

What we can do :

Label-‐free & label-‐based LC-‐MS & SRM

Label-‐free & label-‐based SRM Label-‐free shotgun MS

SRM course 2013 : Sta$s$cal analysis with MSstats

R is a freely available language and environment for sta$s$cal compu$ng and graphics, easy to develop tools. R packages allow specialized sta$s$cal techniques, graphics with specific func$ons for specific area of study.

Website

•  hWp://www.stat.purdue.edu/~ovitek/SoZware.html •  hWp://msstats.org

–  Workflow for different analysis –  Example dataset with R-‐script

4

Download

Download & website


Agenda



MSstats with Skyline

•  Use as an external tool •  Automa$cally run the func$ons for

–  Data processing : Preprocessing the data, Drawing the profile plots, Quality control plots, Condi$on plots

–  Group Comparison : Comparing between groups, Drawing the plots with results

–  Design Sample Size : Calcula$ng the sample size •  For the beginner of R or other sta$s$cal tools, we can do sta$s$cal

analysis with default op$ons through Skyline easily.

6

In Skyline


Set up MSstats as external tool

•  Need ‘MSstatsExternal.zip’ (will be downloaded through Skyline website or MSstats website)

•  Tools -‐> External tools •  Add… -‐> select MSstatsExternal.zip •  Then start to download and install R and required packages

7

In Skyline


1. Data processing and Quality control plots

Visualiza$on for data –  Show poten$al source of varia$on : Run, Subject, Transi$on, Condi$on –  Find any problema$c observa$on : outliers, missingness, poor quality runs –  Show how the normaliza$on works

8

Profile Plot : individual observa$ons QC Plot : distribu$on per run SRM course 2013 : Sta$s$cal analysis with MSstats

In Skyline

Data processing : Input with the report from Skyline –  Log 2 or 10 transforma$on –  Constant normaliza$on ( same median across runs in reference)

Reference Endogenous

●

●●

●

●●

●●

●●

●

●

●

●●

●

●●

●●

●●

●

●

●

●●

●

●●

●●

●●

●

●

●

●●

●

●●

●●●●

●

●●

●●

●

●●

●●

●●

●

●

●●●

●

●●

●●

●●

●

●

●

●●

●

●●

●●

●●

●

●

●

●●

●

●●

●●

●●

●

● ●

●●

●

●●

●●

●●

●

●

T1−0h T2−6h T3−48h

●●

●

●

●●

●●

●●

●

●

●

●●

●

●●

●●●●●●

●

●●

●

●●

●●●●

●

●●

●●

●

●

●

●

●

●●

●

● ●

●●

●

●●

●●

●●

●

●●

●●

●

●●

●●

●●

●

●

●

●●

●

●●

●●

●●

●

●

●

●●

●

●●

●●

●●

●

●●

●●

●

●

●

●●

●●

●

●

T1−0h T2−6h T3−48h

0

10

20

30

3 6 9 3 6 9MS runs

Log2−i

nten

sitie

s

●

●

●

●

●

●

●

●

●

●

●

●

AQAATAGIDDLRPALIR_3_y12_2





EFPDVAVFSGGR_2_y10_1

EFPDVAVFSGGR_2_y10_2

EFPDVAVFSGGR_2_y7_1

LTTPAEALVTR_2_y8_1

LTTPAEALVTR_2_y8_2

LTTPAEALVTR_2_y9_1

LTTPAEALVTR_2_y9_2

Rv0079_Rv0079 Reference Endogenous

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●●

●

●●●

●

●

●

●●

● ●

●

T1−0h T2−6h T3−48h

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●● ●

●● ●

●

T1−0h T2−6h T3−48h

0

10

20

30

3 6 9 3 6 9MS runs

Log2−i

nten

sitie

s

All proteins

2. Test for differen$al abundance at the protein level

•  Hypothesis : Is there a difference in abundance between condi$on1 and condi$on2?

H0 : log fold change = 0 vs. Ha : log fold change ≠ 0

•  Automa$cally detect the proper$es of the experimental design •  Case-‐control (matching : before-‐aZer) study •  Time-‐course study

•  Can choose the model •  with the desired scope of conclusion

•  Scope of biological replica$on •  fixed (“restricted”) / random (“expanded”)

•  Scope of technical MS run replica$on : •  fixed (“restricted”) / random (“expanded”)

•  Interference •  contain interference transi$ons, need addi$onal model interac$on


In Skyline

● ●

●

●

●

●● ●

●

● Rv0079_Rv0079 Rv1738_Rv1738

Rv1812c_Rv1812c

Rv1996_Rv1996

Rv2027c_dosT

Rv2031c_hspXRv2623_TB31.7 Rv2626c_hrp1

Rv3132c_devS

Rv3133c_devR

0

10

20

30

−5.0 −2.5 0.0 2.5 5.0

−Log

2 (a

djus

ted

p−va

lue)

Log2 fold change●�No regulation�●�Down−regulated�●�Up−regulated

Adj p−value cutoff(0.05)

T2−T1

2. Visualiza$on for tes$ng results : Volcano plot


In Skyline

More significant

Less significant

Prac$cal significance

Sta$s$cal significance

Volcano plot : •  Per comparison •  All proteins •  Adjusted p-‐value and log fold change

2. Visualiza$on for tes$ng results

11

Heatmap: •  With all comparisons •  All proteins •  Adjusted p-‐value and cut-‐off log

fold change

Comparison plot: •  With all comparisons •  Per protein •  log fold change and CI


In Skyline

T2−T1

T3−T1

Rv1812c_Rv1812c

Rv2027c_dosT

Rv3132c_devS

Rv1996_Rv1996

Rv3133c_devR

Rv2626c_hrp1

Rv2623_TB31.7

Rv2031c_hspX

Rv0079_Rv0079

Rv1738_Rv1738

●

●

4

5

6

7

8

T2−T1 T3−T1ComparisonLo

g2−F

old

Cha

nge

Rv2031c_hspX

Color Key

(sign) Adjusted p−value1 0.001 1e−10��1e−10 ��0.001

3. Design of future experiment

•  Use the current dataset for variance es$ma$on : with fixed Subject or random Subject

•  Also calculate •  The number of pep$de per protein •  The number of transi$on per pep$de


In Skyline

05

1015

2025

1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5

0.001 0.003 0.005 0.009 0.018Coefficient of variaWLRQ, CV

Desired fold change

Min

imal

num

ber o

f bio

logi

cal r

eplic

ates Number of peptides is 3

Number of transitions is 4FDR is 0.05Statistical power is 0.8

Prac$ce 1. Set up ‘Annota$ons’

•  Seqngs è Annota$ons.. è Edit List è Add –  Type ‘BioReplicate’ in Name -‐> select ‘Replicates’ in Applies to –  Type ‘Run’ in Name -‐> select ‘Replicates’ in Applies to –  Type ‘Condi$on’ in Name -‐>select ‘Value List’ in Type -‐> Type values(Condi$on

values) -‐> select ‘Replicates’ in Applies to –  Click OK

•  Check ‘BioReplicate’, ‘Run’, ‘Condi$on’ in Annota0on Se2ngs, then click Ok.


In Skyline

Prac$ce 2. Fill in ‘Results Grid’

•  View è Results Grid –  Type in columns,‘BioReplicate’ and ‘Run’ –  Choose one of value in column ‘Condi$on’ for each replicate


In Skyline

Prac$ce 3. MSstats as an external tool

–  Tools è MSstats •  Data processing •  Group Comparison •  Design Sample Size

–  All results and plots will be saved under current directory.


In Skyline

Let’s try!

Agenda



Data : Rat-‐plasma for Risk of heart disease

17

Each Protein

High salt (Disease) Low salt (Healthy)

Sub1 … Sub7 Sub8 … Sub14 T1 T2 T3 T1 T2 T3 T1 T2 T3 T1 T2 T3

Pep*Tran1 X X X … X X X X X X … X X X



•  Label-‐free SRM experiment •  High salt (7) vs. Low salt (7) •  3 Technical replicates •  Total 42 injec$ons (Runs) •  48 proteins •  Comparison : High Salt – Low Salt (Disease-‐Healthy)

Rat Plasma : label-‐free SRM


Examples of inconsistent (poor quality?) pep$des

18


Profile plot show the problemaBc pepBdes or transiBons. We need to check what happen in this pepBde.


Endogenous

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●●

●

●

●●●

●

●

●

●

●●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●●●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●●●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●●●

●

●

●●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●●

●

●●

●

●

●

●

●●●

●

●

●

●

●●

●

●

●

●●●

●●

●

●●

●

●●

●

●●

●

●●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s

# peptide: 2 ● ●CSSLLWAGAAWLR_2 NLGVVVAPHALR_2

NP_001007697

NLGVVVAPHALR

19



Endogenous

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●●

●

●

●●●

●

●

●

●

●●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●●●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●●●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●●●

●

●

●●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●●

●

●●

●

●

●

●

●●●

●

●

●

●

●●

●

●

●

●●●

●●

●

●●

●

●●

●

●●

●

●●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s


NP_001007697

CSSLLWAGAAWLR

20



Endogenous

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●●

●

●

●●●

●

●

●

●

●●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●●●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●●●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●●●

●

●

●●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●●

●

●●

●

●

●

●

●●●

●

●

●

●

●●

●

●

●

●●●

●●

●

●●

●

●●

●

●●

●

●●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s


NP_001007697

Log2 FC and varia$on are different between before and aZer removing pep$des

21

All features Only NLGV (red lines) Only CSSL (black lines)

log2FC SE Adj p-‐value log2FC SE Adj p-‐value log2FC SE Adj p-‐value

Fixed Subject -‐2.6721 0.1439 <0.0001 0.8750 0.0260 <0.0001 -‐6.2272 0.2868 <0.0001

Random Subject -‐2.6701 0.2214 <0.0001 0.8750 0.2399 0.0066 -‐6.2187 0.4152 <0.0001



Endogenous

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●●

●

●

●●●

●

●

●

●

●●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●●●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●●●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●●●

●●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●●●

●

●

●●●

●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●●

●

●●

●

●

●

●

●●●

●

●

●

●

●●

●

●

●

●●●

●●

●

●●

●

●●

●

●●

●

●●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s


NP_001007697

Endogenous

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●

●●

●

●

●

●

●

●●●

●

●

●

●

●●

●

●

●●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●●●

●

●

●

●●●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●●●

●●

●

●

●●

●

●

●

●●●

●

●

●

●●●

●

●

●

●

●

●

●

● ●

●

●●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●

●●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s

# peptide: 1 ● CSSLLWAGAAWLR_2

NP_001007697

Endogenous

●

●●

●

●

●

●

●●

●

●

●●

●●

●

●

●●

●●

●

●

●

●

●●

●

●●

●

●●

●

●

●●

●●●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●●

●

●

●●

●●

●

●

●

●

●●

●

●

●

●

●●

●

●

●●

●●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●●

●

●

●●

●●

●

●

●●

●●

●

●

● ●

●●

●

●

●●

●●●

●

●

●

●●

●

●

●

●

●●

●

●

● ●

●●

●

●●

●

●●

●

●●

●

●●

●

●

●●

●●

●

●

● ●

●●

●

●

●●

●●

●

●

●

●●●

●

●

●

●

●●

●

●

● ●

●●

●

●

●

●

●●

●

●●

●

●●●

●

●●

●●●

●●

●

●●

●

●●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s

# peptide: 1 ● NLGVVVAPHALR_2

NP_001007697

22

Examples of inconsistent pep$des



Profile plot show inconsistent paKern per pepBdes. We need to check that is there any measurement problem.

Endogenous

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●●

●

●

●

●

●

●

●

●

●

●

● ●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s# peptide: 3 ● ● ●AIAYLNTGYQR_2 DLTGFPQGADQR_2 TVEHPFSVEEFVLPK_2

NP_036620

DLTGFPQGADQR

23



Endogenous

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●●

●

●

●

●

●

●

●

●

●

●

● ●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s

# peptide: 3 ● ● ●AIAYLNTGYQR_2 DLTGFPQGADQR_2 TVEHPFSVEEFVLPK_2

NP_036620

AIAYLNTGYQR

24



Endogenous

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●●

●

●

●

●

●

●

●

●

●

●

● ●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s


NP_036620

25

Log2 FC and varia$on are quite different depending on pep$des.

All features Only DLTG and TVEH Only AIAY

log2FC SE Adj p-‐value log2FC SE Adj p-‐value log2FC SE Adj p-‐value

Fixed Subject 2.0642 0.0951 <0.0001 0.6167 0.0414 <0.0001 5.0812 0.0591 <0.0001

Random Subject 2.0642 0.2966 <0.0001 0.6167 0.1137 0.0005 5.0812 0.7390 <0.0001



Endogenous

●●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●●

●●

●●

●

●

●●

●●

●●

●●

●

●

●●

●●

●●

●●

●●

●●

●●

●●

●●

●●

●

●

●

●

●

●

●●

●●

●

●

●

●

●●

●●

●●

●

●

●●

●

●

●

●

●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●●

●●

●●

●●

●

●

●

●

●●

●

●

●●

●

●●●

●

● ●●

●●

●

●

●

●

●

●

●

● ●

●

●

●

●●

●

●

●●

●●

●

●

●

●

●

●

●

●

●●●

●

●●

●

●

●●

●

●

●

●●●

●

●

●●

●

●

●

●

●

●

●●

●

●

●●

●

●●

●

●

●

●

●

●●

●●

●●

●

●

●

●●

●

●●

●●

●●

●●

●●

●●

●

●

●●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●●

●●●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s

# peptide: 1 ● AIAYLNTGYQR_2

NP_036620

Endogenous

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●●

●

●

●

●

●

●

●

●

●

●

● ●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s


NP_036620

Endogenous

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

Disease Healthy

0

10

20

30

21 42MS runs

Log2−i

nten

sitie

s

# peptide: 2 ● ●DLTGFPQGADQR_2 TVEHPFSVEEFVLPK_2

NP_036620

Summary of poor quality pep$des

•  Profile plot show inconsistent paWern per pep$des. We need to check that is there any measurement problem.

•  Less certainty that you look at the correct pep$de, –  Due to different reasons such as any phosphoryla$on and modifica$on

in pep$de level. –  sugges$on : re-‐measure in label-‐based way.

•  Need to inves$gate further a subset of pep$des that we find interes$ng for some reason.

26



Agenda



MSstats in R

•  Use R-‐based plaLorm if you want the detailed op$ons for all func$ons such as, –  Customized normaliza$on – Detailed op$ons for all plots – Quan$fica$on for sample

•  With R-‐based plaLorm, we can take advantage of op$ons and modify the data easily.

28

In R


1. Set up ‘Annota$ons’


In Skyline

•  Seqngs è Annota$ons.. è Edit List è Add –  Type ‘BioReplicate’ in Name -‐> select ‘Replicates’ in Applies to –  Type ‘Run’ in Name -‐> select ‘Replicates’ in Applies to –  Type ‘Condi$on’ in Name -‐>select ‘Value List’ in Type -‐> Type values(Condi$on

values) -‐> select ‘Replicates’ in Applies to –  Click OK

•  Check ‘BioReplicate’, ‘Run’, ‘Condi$on’ in Annota0on Se2ngs, then click Ok.

2. Fill in ‘Results Grid’

•  View è Results Grid –  Type in columns,‘BioReplicate’ and ‘Run’ –  Choose one of value in column ‘Condi$on’ for each replicate


In Skyline

3. Generate report from Skyline

•  Export the report using MSstats report format (Msstats_report.skyr) –  File è Export è Report.. è Import.. –  select MSstats_report.skyr –  Select MSstats in Export Reportè Export


In Skyline

Let’s try!

How to start MSstats •  Download and install R 3.0.1 (hWp://cran.r-‐project.org/) •  Required package

–  gplots, lme4, ggplot2, limma, marray –  Need to install the required package once. Then they will be loaded automa$cally

with MSstats. •  Installa$on

–  Select ‘packages’ in toolbar and then ‘Install package(s)’ in dropdown op$on. –  Or use ‘install. packages’ func$on. (see R script example)

32

In R

R screen R studio screen SRM course 2013 : Sta$s$cal analysis with MSstats

4. Data processing

•  Input : report from Skyline or excel spreadsheet, output from signal process tool

Then, we need

–  Log 2 or 10 transforma$on –  Constant normaliza$on –  Show the summary of data structure

In R : use R script


> quantData<-dataProcess(raw, logTrans=2, normalization=TRUE)

5. Data processing : Quality control •  Show poten$al source of varia$on : Run, Subject, Transi$on, Condi$on •  Find any problema$c observa$on : outliers, missingness, poor quality runs •  Show how the normaliza$on works •  Input : processed data

34

Profile Plot : individual observa$ons QC Plot : distribu$on per run SRM course 2013 : Sta$s$cal analysis with MSstats

Let’s try!

> dataProcessPlots(data=quantData,type="ProfilePlot”)


●

●

●

●

●

●

●

●●●

●

●●

●

●

●

●

●

●

●●●

●

● ●

●

●

●

●

●

●

●●●

●

● ●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●●

●

●

● ●

●

●

●

●

●

●

●●

●

●

●●

●

●

●

●

●

●

●●●

●

●

●

●

●

●

●

●

●●

●

●

●

T1−0h T2−6h T3−48h

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●●

●

●

T1−0h T2−6h T3−48h

0

10

20

30

3 6 9 3 6 9MS runs

Log2−i

nten

sitie

s

●

●

●

●

●

●

●

●

●

●

●

●

AIVHTAAELVDAR_3_y4_1




GVLGALIEEPKPIR_3_y11_2




SAIFDLHAGPSR_3_y10_2

SAIFDLHAGPSR_3_y5_1

SAIFDLHAGPSR_3_y8_1

SAIFDLHAGPSR_3_y9_2

Rv2027c_dosT

Missingness


●

●

●

●

●

●●

●

●●

●

●

●

●

●

●●

●

●●●

●

●

●

●●

●●

●

T1−0h T2−6h T3−48h

●

●

●

●

●

●

●

●

●

●

●

●

● ●

●

●●

●●

●

●●

●●

T1−0h T2−6h T3−48h

0

10

20

30

3 6 9 3 6 9MS runs

Log2−i

nten

sitie

s

All proteinsReference Endogenous

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●●

●

●●●

●

●

●

●●

● ●

●

T1−0h T2−6h T3−48h

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●● ●

●● ●

●

T1−0h T2−6h T3−48h

0

10

20

30

3 6 9 3 6 9MS runs

Log2−i

nten

sitie

s

All proteins

In R : use R script

6. Test for differen$al abundance at the protein level


•  Input –  Processed data –  Assigned comparison matrix

How to assign the comparison matrix???

CondiBon1 CondiBon2 CondiBon3 … CondiBon J example

T2-‐T1 -‐1 1 0 … 0 Disease-‐Control

T1-‐T2 1 -‐1 Control-‐Disease

T3-‐T1 -‐1 0 1 … 0

T3-‐T2 0 -‐1 1 … 0

(T2+T3)/2-‐T1 -‐1 0.5 0.5 0 (Cancer+Benign)-‐Control

>resultMultiComparisons<-groupComparison(contrast.matrix=comparison,data=quantData, labeled=TRUE, scopeOfBioReplication="restricted", scopeOfTechReplication="expanded", interference=TRUE)

In R : use R script

Comparison matrix


T1-0h T2-6h T3-48hT2-T1 -1 1 0>groupComparison(contrast.matrix=comparison,data=quantData)

T1-0h T2-6h T3-48hT1-T2 1 -1 0>groupComparison(contrast.matrix=comparison,data=quantData)

Sign of log2FC is changed. However, others including conclusion are the same.

In R : use R script

Residual plot

37

−2

−1

0

1

2

10 15 20

Predicted Abundance

Res

idua

ls

FEATURE

ADLLAAAAPR_2_y3_1ADLLAAAAPR_2_y4_1ADLLAAAAPR_2_y6_1ADLLAAAAPR_2_y7_1VIGVPAMFAAGDVAAAR_2_y13_2VIGVPAMFAAGDVAAAR_2_y5_1VIGVPAMFAAGDVAAAR_2_y8_1VIGVPAMFAAGDVAAAR_2_y9_1VIGVPAMFAAGDVAAAR_3_y4_1

VIGVPAMFAAGDVAAAR_3_y5_1VIGVPAMFAAGDVAAAR_3_y7_1VIGVPAMFAAGDVAAAR_3_y8_1VIGVPAMFAAGDVAAAR_3_y9_1VTTSTGASYSYDR_2_y10_1VTTSTGASYSYDR_2_y11_1VTTSTGASYSYDR_2_y6_1VTTSTGASYSYDR_2_y8_1VTTSTGASYSYDR_2_y9_1


Rv1812c_Rv1812c

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●●

●

●

●

●●●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●●●

●

●

●

●●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●

●

●●

●

●

●

●

●

●

●

●

●●

●

●●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●●

●

●

−3 −2 −1 0 1 2 3

−0.2

−0.1

0.0

0.1

0.2

Normal Q−Q Plot ( Rv1812c_Rv1812c )

Theoretical Quantiles

Sam

ple

Qua

ntile

s

•  Perform model-‐based quality control •  Check equal variance assump$on among features

Close to zero, no paKerns Close to diagonal line

In R : use R script


7. Visualiza$on for tes$ng results


•  Input : result of group comparison

>groupComparisonPlots(data=resultmultiComparison,type="VolcanoPlot”,FCcutoff=1.5)

Let’s try!

Color Key

(sign) Adjusted p−value1 0.001 1e−10��1e−10 ��0.001

● ●

●

●

●

●● ●

●

● Rv0079_Rv0079 Rv1738_Rv1738

Rv1812c_Rv1812c

Rv1996_Rv1996

Rv2027c_dosT

Rv2031c_hspXRv2623_TB31.7 Rv2626c_hrp1

Rv3132c_devS

Rv3133c_devR

0

10

20

30

−5.0 −2.5 0.0 2.5 5.0

−Log

2 (a

djus

ted

p−va

lue)

Log2 fold change●�No regulation�●�Down−regulated�●�Up−regulated

Adj p−value cutoff(0.05) Fold change cutoff(1.5)

T2−T1

T2−T1

T3−T1

Rv1812c_Rv1812c

Rv2027c_dosT

Rv3133c_devR

Rv1996_Rv1996

Rv3132c_devS

Rv2626c_hrp1

Rv2623_TB31.7

Rv2031c_hspX

Rv0079_Rv0079

Rv1738_Rv1738

In R : use R script

Different scope of conclusion

39

Less SensiBve More Specific

More SensiBve Less Specific

Fixed Run Random Subject

Random Run Random Subject

Fixed Run Fixed Subject

Random Run Fixed Subject

•  The choice of the model should depend on the desired scope of biological conclusions, and not on the sensi$vity/specificity.

● ●● ●

●

●● ●●● Rv0079_Rv0079 Rv1738_Rv1738Rv1812c_Rv1812c Rv1996_Rv1996

Rv2027c_dosT

Rv2031c_hspXRv2623_TB31.7Rv2626c_hrp1Rv3132c_devSRv3133c_devR

0

10

20

30

−5 0 5

Log2 fold change

−Log

2 (a

djus

ted

p−va

lue)

● ● ●No regulation Down−regulated Up−regulated


T3−T1

●

●

●

●

●

●

●

●

●

●

Rv0079_Rv0079

Rv1738_Rv1738

Rv1812c_Rv1812c

Rv1996_Rv1996

Rv2027c_dosT

Rv2031c_hspX

Rv2623_TB31.7

Rv2626c_hrp1

Rv3132c_devS

Rv3133c_devR

0

5

10

15

−5 0 5

Log2 fold change

−Log

2 (a

djus

ted

p−va

lue)



T3−T1

●

●

●

●

●

●

●

●

●

●

Rv0079_Rv0079Rv1738_Rv1738

Rv1812c_Rv1812c

Rv1996_Rv1996

Rv2027c_dosT

Rv2031c_hspX

Rv2623_TB31.7

Rv2626c_hrp1

Rv3132c_devS

Rv3133c_devR

0

5

10

15

−5 0 5

Log2 fold change

−Log

2 (a

djus

ted

p−va

lue)



T3−T1

In R


8. Design of future experiment


•  Input : processed data

>designSampleSize(data=quantData,numSample=TRUE,numPep=3,numTran=3,desiredFC=c(1.1,1.5),FDR=0.05,power=0.8)

05

1015

2025

1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5

0.001 0.003 0.005 0.009 0.018Coefficient of variaWLRQ, CV

Desired fold change

Min

imal

num

ber o

f bio

logi

cal r

eplic


Number of transitions is 4FDR is 0.05Statistical power is 0.8

In R : use R script

•  Can consider –  Scope of subject : restricted or expanded –  Interference or not

Design of future experiment : Power


Let’s try!

0.0

0.2

0.4

0.6

0.8

1.0

1.1 1.2 1.3 1.4 1.5 1.6 1.7

Desired fold change

Powe

rNumber of replicates is 3Number of peptides is 3Number of transitions is 3FDR is 0.05

•  Input : processed data

>designSampleSize(data=quantData,numSample=3,numPep=3,numTran=3,desiredFC=c(1.1,1.7),FDR=0.05,power=TRUE)

In R : use R script

Different sample size calcula$on for different conclusion and experiments

42

1020

3040

5060

70

1.1 1.15 1.2 1.25 1.3 1.35 1.4 1.45 1.5

Desired fold change

Min

imal

num

ber o

f bio

logi

cal r

eplic


Number of transitions is 3FDR is 0.05Statistical power is 0.8Labeled SRM, Fixed SubjectLabeled SRM, Random Subject

Need more number of biological replicate with random subject for model

In R


Future plan

•  Several sta$s$cal analysis in prototype stage will merge different workflow in MSstats –  sparseStats : with subset of reference pep$des –  Feature selec$on : select a subset of informa$ve fragments

–  Biomarker study : classifica$on study, find best candidates as biomarker, clustering, measure the performance

•  Improve UI and expand more op$ons for MSstats in Skyline

43

MSstats


stas$cal(analysis(with( msstats( - dia/swath...

Documents