MAKE SENSE OF YOUR OMICS DATA

INTEGRATIVE DATA ANALYSIS IN LIFE SCIENCES

WHAT ARE OMICS DATA? ▸ Allow the simultaneous analysis of a great number of measures:

• DNA : Genomic (SNP, DNA rearrangements,…), Epigenomic (methylation, histone modifications,…)

• RNA : Transcriptomic (differential expression, alternative splicing, lncRNA, miRNA,…)

• Proteins : Proteomic (differential expression) ‣ With the aim of:

• Caracterizing new models • Identifying molecular mecanisms/markers of pathology • Following biological ways of interest (oxydative stress, immune

response,…) • Caracterizing the effect of treatments at different doses • Studying the microbiote

Transcriptomic (DNA chip, RNA-Seq)

Proteomic (LC-MS/MS)

Genomic/Epigenomic (DNA chip, NGS)

THE ALTRABIO’S WORKFLOW

What we deliverWhat we need What we do

Implementation of biostatistical and biomathematical methods

Analysis methods & resultsPublication quality images

Oral presentation of the report

Comprehensive report

State-of-the-art methodsCustomized statistical models

Classifier analyses

Generated Omics DataFrom your own providers or from our partners

Biological questionAccess to WikiBioPath

Web interface for visualization and exploration of the results

DATA PREPROCESSING▸ Quality controls are performed at different step:

• Molecular (RNA, cDNA, protein,…) • Technologic (hybridation, reads, mapping, missing

values,…) • Experimental (contaminations, annotation errors,

hidden factors,…) ▸ Adapted data normalization for each technology:

• Background correction • Variance stabilization • Quantile normalization

▸ Treatment of the calcul units • Probe merging/separation related to their behaviour to

optimize modulation detection

Hybridization Quality Control

Data NormalizationProbeset summarization

(proprietary CDFs)6

8

10

12

Sample

log 2(s

igna

l)

DST (667_at)

6

8

10

12

P129

_01_

01S1

6_no

15_J

14.C

EL.g

z

P129

_02_

01S1

6_no

15_J

14.C

EL.g

z

P129

_03_

01S1

6_no

15_J

14.C

EL.g

z

P129

_04_

01S1

6_no

15_J

14.C

EL.g

z

P129

_05_

01S1

6_no

15_J

14.C

EL.g

z

P129

_06_

01S1

6_no

15_J

14.C

EL.g

z

P129

_07_

01S1

6_no

16_J

14.C

EL.g

z

P129

_08_

01S1

6_no

16_J

14.C

EL.g

z

P129

_09_

01S1

6_no

16_J

14.C

EL.g

z

P129

_10_

01S1

6_no

16_J

14.C

EL.g

z

P129

_11_

01S1

6_no

16_J

14.C

EL.g

z

P129

_12_

01S1

6_no

16_J

14.C

EL.g

z

P129

_13_

01S1

6_no

15_J

18.C

EL.g

z

P129

_15_

01S1

6_no

15_J

18.C

EL.g

z

P129

_19_

01S1

6_no

16_J

18.C

EL.g

z

P129

_20_

01S1

6_no

16_J

18.C

EL.g

z

P129

_21_

01S1

6_no

16_J

18.C

EL.g

z

P129

_22_

01S1

6_no

16_J

18.C

EL.g

z

P129

_24_

01S1

6_no

16_J

18.C

EL.g

z

Sample

log 2(s

igna

l)

DST (667_at)

●

●●

●●

●

●●

●●

●

●

●●

●

●

●

●●

●

● ●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●● ●●● ●●●●●●

●●●●

−1

0

1

0 2 4PC1

PC2

group●

●

●

●

●

●

●

●

1

2

3

4

5

6

7

8

●

●●

●●

●

●● ●

●

●

●

●●

●

●

●

●●

●

● ●

●

●

●

●

●

●●

●

●●

●

●

●

●●

●●

●

●

●

●●●●●●● ●●●●● ●●●

●●

−1

0

1

0 2 4PC1

PC2

probeset●

●

667_at_AB_1:19

667_at_AB_20:59

6

8

10

12

Sample

log

2(s

igna

l)

DST (667_at)

6

8

10

12

P129_01_01S

16_no15_J14.C

EL.g

z

P129_02_01S

16_no15_J14.C

EL.g

z

P129_03_01S

16_no15_J14.C

EL.g

z

P129_04_01S

16_no15_J14.C

EL.g

z

P129_05_01S

16_no15_J14.C

EL.g

z

P129_06_01S

16_no15_J14.C

EL.g

z

P129_07_01S

16_no16_J14.C

EL.g

z

P129_08_01S

16_no16_J14.C

EL.g

z

P129_09_01S

16_no16_J14.C

EL.g

z

P129_10_01S

16_no16_J14.C

EL.g

z

P129_11_01S

16_no16_J14.C

EL.g

z

P129_12_01S

16_no16_J14.C

EL.g

z

P129_13_01S

16_no15_J18.C

EL.g

z

P129_15_01S

16_no15_J18.C

EL.g

z

P129_19_01S

16_no16_J18.C

EL.g

z

P129_20_01S

16_no16_J18.C

EL.g

z

P129_21_01S

16_no16_J18.C

EL.g

z

P129_22_01S

16_no16_J18.C

EL.g

z

P129_24_01S

16_no16_J18.C

EL.g

z

Sample

log

2(s

ign

al)

DST (667_at)

●

●●

●●

●

●●

●●

●

●

●●

●

●

●

●●

●

● ●

●

●

●

●

●

●●

●

●●

●

●

●

●

●

●●

●

●

●

●●

●● ●●● ●●●●●●

●●●●

−1

0

1

0 2 4PC1

PC

2

group●

●

●

●

●

●

●

●

1

2

3

4

5

6

7

8

●

●●

●●

●

●● ●

●

●

●

●●

●

●

●

●●

●

● ●

●

●

●

●

●

●●

●

●●

●

●

●

●●

●●

●

●

●

●●●●●●● ●●●●● ●●●

●●

−1

0

1

0 2 4PC1

PC

2

probeset●

●

667_at_AB_1:19

667_at_AB_20:59

●

●

●

●

●

●

●

●

●

−4 −2 0 2

−4−2

02

PC1

PC2

GSM733816GSM733817

GSM733818

GSM733819GSM733820

GSM733821

GSM733822

GSM733823

GSM733824

GSM733825

GSM733826GSM733827

GSM733828

GSM733829

GSM733830

GSM733831GSM733832

GSM733833

GSM733834GSM733835

GSM733836

GSM733837

GSM733838GSM733839

GSM733840

GSM733841

GSM733842

●

●

●

●

●

●

●

●

●

−4 −2 0 2

−4−2

02

PC3

PC2

GSM733816GSM733817

GSM733818

GSM733819GSM733820

GSM733821

GSM733822

GSM733823

GSM733824

GSM733825GSM733826GSM733827

GSM733828

GSM733829

GSM733830 GSM733831

GSM733832

GSM733833

GSM733834GSM733835 GSM733836

GSM733837

GSM733838 GSM733839

GSM733840

GSM733841

GSM733842

PC1

PC2

−1.0 −0.5 0.0 0.5

−1.0

−0.5

0.0

0.5

1.0●

●

●

●

●

●

●●

●

●

XIST

HLA−DQA1

HLA−DQB1

HLA−DQB1

FAM118A

GSTT1

LDHCLOC654433

RPS23RPS23

% v

aria

nce

010

2030

4050

●

Patient 12 16 18 21 23 29 32 35 39

Time D0 D3 D7

●

●

●

●

●

●

●

●

●

−4 −2 0 2

−4−2

02

PC1

PC2

GSM733816GSM733817

GSM733818

GSM733819GSM733820

GSM733821

GSM733822

GSM733823

GSM733824

GSM733825

GSM733826GSM733827

GSM733828

GSM733829

GSM733830

GSM733831GSM733832

GSM733833

GSM733834GSM733835

GSM733836

GSM733837

GSM733838GSM733839

GSM733840

GSM733841

GSM733842

●

●

●

●

●

●

●

●

●

−4 −2 0 2

−4−2

02

PC3

PC2

GSM733816GSM733817

GSM733818

GSM733819GSM733820

GSM733821

GSM733822

GSM733823

GSM733824

GSM733825GSM733826GSM733827

GSM733828

GSM733829

GSM733830 GSM733831

GSM733832

GSM733833

GSM733834GSM733835 GSM733836

GSM733837

GSM733838 GSM733839

GSM733840

GSM733841

GSM733842

PC1

PC2

−1.0 −0.5 0.0 0.5

−1.0

−0.5

0.0

0.5

1.0●

●

●

●

●

●

●●

●

●

XIST

HLA−DQA1

HLA−DQB1

HLA−DQB1

FAM118A

GSTT1

LDHCLOC654433

RPS23RPS23

% v

aria

nce

010

2030

4050

●

Patient 12 16 18 21 23 29 32 35 39

Time D0 D3 D7

Popu

latio

n st

ruct

urin

g ge

nes XIST

HLA-DQA1

Annotation Quality Control

PCA Hierarchical clustering

P129_03_01S16_no15_J14

P129_04_01S16_no15_J14

P129_05_01S16_no15_J14

P129_06_01S16_no15_J14

P129_01_01S16_no15_J14

P129_02_01S16_no15_J14

P129_13_01S16_no15_J18

P129_15_01S16_no15_J18

P129_21_01S16_no16_J18

P129_20_01S16_no16_J18

P129_19_01S16_no16_J18

P129_22_01S16_no16_J18

P129_09_01S16_no16_J14

P129_10_01S16_no16_J14

P129_11_01S16_no16_J14

P129_07_01S16_no16_J14

P129_08_01S16_no16_J14

P129_12_01S16_no16_J14

P129_24_01S16_no16_J18

ZoneTimePointDonor

Donorno15no16

TimePointJ14J18

ZoneZone−Zone+

100 10097 100100 100

100 100100 99

9971

1007986

87

87●●

●

●

● ●

●●

−20 −10 0 10 20

−30

−20

−10

010

20

PC1

PC2

01

02

03

0405

0607

08

09

10

11 12

13 15

19

20

21

22 24

●●

●

●

●●

● ●

−30 −20 −10 0 10 20

−30

−20

−10

010

20

PC3

PC2

01

02

03

0405

0607

08

09

10

1112

1315

19

20

21

22 24

−1.0 −0.5 0.0 0.5 1.0

−1.0

−0.5

0.0

0.5

1.0

PC1

PC2

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

●

CD24

LRRC17

SPON2

DDX17

POSTN

SPINK5

CHI3L1

SERPINA3

ADH1B

ALDH1A3KRT23

SFN

APOD

IGFBP3

ITGB6

IVL

KRT5

KRT6AKRT6B

KRT15

KRT16

KRT17

KRT19

KRTDAP

LAMA3

LAMB3

LCN2

TACSTD2CEACAM6

PI3

SERPINB5

FXYD3KLK7

S100A14

RARRES1

S100A2

S100A8

S100A9

S100P

CCL11

C19orf33

ERAP2

MIR205HG

SLPI

SPRR1A

SPRR1B

SPRR2A

VCAM1

GPRC5A

FGFBP1

% v

aria

nce

05

1015

2025

●

TimePoint J14 J18

Zone Zone− Zone+

Donor no15 no16

PBS

APB

S A

PBS

APB

S A

PBS

APB

S B

PBS

BPB

S B

PBS

BPB

S B

Non

e B

Non

e B

Non

e B

Non

e B

Non

e B

Non

e B

T1 A

T1 A

T1 A

T1 A

T1 A

T1 A

T1 B

T1 B

T1 B

T1 B

T1 B

T1 B

T2 A

T2 A

T2 A

T2 A

T2 A

T2 B

T2 B

T2 B

T2 B

T2 B

T2 B

T3 A

T3 A

T3 A

T3 A

T3 A

T3 B

T3 B

T3 B

T3 B

T3 B

T3 B

− SERPINB4− CASP14− CRNN− KRT77− INHBB− SLC40A1− TPX2− PTGS1− TNNC1− SERPINB12− HSD11B1− C1orf105− FAM83D− RARRES1− CA6− ACPP− GAN− SLC45A4− TMEM99− SLC16A10− ALOX12− SLC1A6− SLC46A2− C15orf59− TYRP1− NUAK1− HMGB2− HOXC6− MKNK2− ZNF395− SLC6A8− CLCA4− PTTG1− PFKP− NDUFA4L2− IGFBP3− ALDOC− FOS− DDIT4− EGLN3− CA9− P4HA1− IER3− LRMP− PGF− PPFIA4− PFKFB4− MT1X− SERPINE1− FUT11− NDRG1− ANKRD37− PFKFB3− C7orf68− ANGPTL4− PPP1R3C− ADM− KCTD11− TCN1− S100A7A− ANKRD30BL− SLC7A5− PHLDA1− CH25H− S100P− STC2− ECM2− PHGDH− EIF4EBP1− NUPR1− ASS1− RCN1− PSAT1− MOCOS− SHMT2− CBS− CADM1− BCHE− SERPINE2− SLC7A11− PSPH− TUBE1− CHAC1− HERPUD1− MARS− TARS− XBP1− AARS− ASNS− PCK2− YARS− PRSS23− IFI6− IFI27− IFITM3− ISG15− HLA−B− DDX60− IFITM1− IFI44− XAF1− MX1− IFIH1− IFIT1− IFIT3− IGFL1− SPINK6− PI3− SPRR4− SYNM− CHST2− KRT9− FABP4− EPRS− LOC100131261− TOP1− M6PR− USO1− HIST1H4C− TAOK1− MALAT1− SMC3− PVRL4− SFRS18− ANKRD11− SECISBP2− DNAJC1− LEPROT− TSPAN5− TAF1D− CCAR1− S100A7− S100A12− MMP10− MMP3− TCHH− SPRR3− C14orf34− DHRS9− HMGCS2− RPTN− ODC1− KRT17− SPRR2A− SPRR2G− C4orf19− LCN2− UPP1− RNASE7− KRT75

Heat-MapDATA ANALYSIS▸ Use of unsupervised approaches to identify the

variabilty sources: • Principal component analysis (PCA) • Hierarchical clustering • Heat-Maps • Segregating genesets

▸ Ad-hoc statisical analysis at the gene and genesets level taking into account the variability sources: • Donor effect • Batch effect • Experimental conditions effect

0.003120.002960.002880.002880.002880.002800.002800.002760.002560.002560.002560.002400.002000.002000.001760.001720.001680.001320.001280.001240.001240.001240.001040.001000.000800.000760.000680.000560.000480.000440.000440.000440.000440.000400.000240.000120.00012< 4e−05< 4e−05< 4e−05< 4e−05< 4e−05< 4e−05< 4e−05< 4e−05< 4e−05< 4e−05< 4e−05< 4e−05< 4e−05

p−values

− Broad:GINESTIER_BREAST_CANCER_20Q13_AMPLIFICATION− Broad:REACTOME_RNA_POLYMERASE_II_TRANSCRIPTION− neuron differentiation (GO:0030182)− regulation of endocytosis (GO:0030100)− vesicle organization (GO:0016050)− Broad:REACTOME_TRANSCRIPTION_OF_THE_HIV_GENOME− Broad:ACTAYRNNNCCCR_UNKNOWN− Broad:ATGGYGGA_UNKNOWN− positive regulation of erythrocyte differentiation (GO:0045648)− Broad:MULLIGHAN_NPM1_MUTATED_SIGNATURE_1− L2L:hsa−miR−10a− Broad:GGCAGTG,MIR−324−3P− GeneSigDB:Hypothalamic_Mansuy10_1270genes− Broad:V$PAX5_02− negative regulation of cell cycle process (GO:0010948)− cell projection organization (GO:0030030)− neuron development (GO:0048666)− GeneSigDB:Lung_Olaussen09_174genes− GeneSigDB:Lung_not_cancer_Golpon04_84genes− protein localization in membrane (GO:0072657)− Broad:V$CREB_Q3− Broad:DISTECHE_ESCAPED_FROM_X_INACTIVATION− cell projection assembly (GO:0030031)− L2L:mmu−miR−298− Broad:MULLIGHAN_NPM1_SIGNATURE_3− nucleotide−excision repair (GO:0006289)− GeneSigDB:Leukemia_Haslinger04_126genes− RNA splicing, via transesterification reactions (GO:0000375)− L2L:3ab_gamma− RNA splicing, via transesterification reactions with bulged adenosine as nucleophile (GO:0000377; ...− SMD:paxtube1_sw− GeneSigDB:Leukemia_Lindvall04_30genes_HigherExpression− Broad:ATAGGAA,MIR−202− Broad:TCCCRNNRTGC_UNKNOWN− cell development (GO:0048468)− Broad:REACTOME_ELONGATION_AND_PROCESSING_OF_CAPPED_TRANSCRIPTS− Broad:CASORELLI_ACUTE_PROMYELOCYTIC_LEUKEMIA− mRNA processing (GO:0006397)− GeneSigDB:Embryo_Heim07_327genes− AB:sex− CHR:Y− RNA splicing (GO:0008380)− RNA processing (GO:0006396)− SMD:male_sw− GeneSigDB:Viral_Craft08_969genes− GeneSigDB:StemCell_Komor05_56genes− Broad:RUNNE_GENDER_EFFECT− Broad:PYEON_CANCER_HEAD_AND_NECK_VS_CERVICAL− Broad:GINESTIER_BREAST_CANCER_ZNF217_AMPLIFIED− AB:celtype_mel

LAIV

01

D0

LAIV

01

D3

LAIV

01

D7

LAIV

05

D0

LAIV

05

D3

LAIV

05

D7

LAIV

06

D0

LAIV

06

D3

LAIV

06

D7

LAIV

14

D0

LAIV

14

D3

LAIV

14

D7

LAIV

22

D0

LAIV

22

D3

LAIV

22

D7

LAIV

24

D0

LAIV

24

D3

LAIV

24

D7

LAIV

25

D0

LAIV

25

D3

LAIV

25

D7

LAIV

26

D0

LAIV

26

D3

LAIV

26

D7

LAIV

33

D0

LAIV

33

D3

LAIV

33

D7

LAIV

40

D0

LAIV

40

D3

LAIV

40

D7

LAIV

41

D0

LAIV

41

D3

LAIV

41

D7

LAIV

45

D0

LAIV

45

D3

LAIV

49

D0

LAIV

49

D3

LAIV

49

D7

LAIV

50

D0

LAIV

50

D3

LAIV

50

D7

LAIV

52

D0

LAIV

52

D3

LAIV

52

D7

LAIV

55

D0

LAIV

55

D3

LAIV

55

D7

LAIV

56

D0

LAIV

56

D3

LAIV

56

D7

LAIV

59

D0

LAIV

59

D3

LAIV

59

D7

LAIV

60

D0

LAIV

60

D3

LAIV

60

D7

LAIV

61

D0

LAIV

61

D3

LAIV

61

D7

LAIV

62

D0

LAIV

62

D3

LAIV

62

D7

LAIV

66

D0

LAIV

66

D3

LAIV

66

D7

LAIV

71

D0

LAIV

71

D3

LAIV

71

D7

LAIV

76

D0

LAIV

76

D3

LAIV

76

D7

LAIV

77

D0

LAIV

77

D3

LAIV

77

D7

LAIV

79

D0

LAIV

79

D3

LAIV

79

D7

LAIV

81

D0

LAIV

81

D3

LAIV

81

D7

LAIV

82

D0

LAIV

82

D3

LAIV

82

D7

TIV

02 D

0TI

V 02

D7

TIV

03 D

0TI

V 03

D3

TIV

03 D

7TI

V 04

D0

TIV

04 D

3TI

V 16

D0

TIV

16 D

3TI

V 16

D7

TIV

29 D

0TI

V 29

D3

TIV

29 D

7TI

V 32

D0

TIV

32 D

3TI

V 32

D7

TIV

35 D

0TI

V 35

D3

TIV

35 D

7TI

V 38

D0

TIV

38 D

3TI

V 38

D7

TIV

39 D

0TI

V 39

D3

TIV

39 D

7TI

V 42

D0

TIV

42 D

3TI

V 42

D7

TIV

43 D

0TI

V 43

D3

TIV

43 D

7TI

V 44

D0

TIV

44 D

3TI

V 44

D7

TIV

46 D

0TI

V 46

D3

TIV

46 D

7TI

V 47

D0

TIV

47 D

3TI

V 47

D7

TIV

48 D

0TI

V 48

D3

TIV

48 D

7TI

V 51

D0

TIV

51 D

3TI

V 53

D0

TIV

53 D

3TI

V 53

D7

TIV

63 D

0TI

V 63

D3

TIV

63 D

7TI

V 65

D0

TIV

65 D

3TI

V 65

D7

TIV

68 D

0TI

V 68

D3

TIV

68 D

7TI

V 70

D0

TIV

70 D

7TI

V 72

D0

TIV

72 D

3TI

V 72

D7

TIV

73 D

0TI

V 73

D3

TIV

73 D

7TI

V 74

D0

TIV

74 D

3TI

V 74

D7

TIV

78 D

0TI

V 78

D3

TIV

78 D

7TI

V 80

D0

TIV

80 D

3TI

V 80

D7

TIV

83 D

0TI

V 83

D3

TIV

83 D

7TI

V 85

D0

TIV

85 D

3TI

V 85

D7

Segregating genesets

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CXCL8

NAMPTP1

G0S2CXCL8

CX3CR1

FCGR3B

ZNF331

CXCR2

PDE4B

MAFF

NAMPT

NR4A2

CREM

S100P

OAS1

BCL2A1

PTGS2

CMTM2

HBEGF GPR183

RGCC

PLAUR

MS4A6A

IDI1

PFKFB3LOC284454

SLC25A37

SLC2A3

HBM

IL1B

CXCL2

GIMAP4

HBD

OSM

CCR2

IDH1RAB10

KCTD12

B3GNT5

TNFSF10

BASP1

IL1R2

ZBTB21

RGS1

EEF1D

SMCO4

CD83

MXD1

MGAM

LITAF

TNFAIP3

AQP9

SAMSN1

CXCR4

MS4A6A

FGD2ALAS2

VCAN

AATBC

COPB2

ABCA1

BRE−AS1

IFI27TLR8

SFPQATF3

TNFAIP8L2

TMEM176B

FOSGOLGA8A

CD69

SON

ZFP36

FFAR2

CA1

RNF103

CDKN1CKLRF1

GPRASP1

GZMH

IFITM2

ALDH1A1

FGFBP2

JUN

NSUN5P1

CLU

LINC00936

POU2AF1

IGHM

/1.2

/1.5

x1.2

x1.5

/1.2/1.5/2 x1.2 x1.5LAIV:(D3 / D0)

TIV:

(D3

/ D0)

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Non−significant (adjusted p−value>0.05)

Significant in LAIV:(D3 / D0)

Significant in TIV:(D3 / D0)

Significant in both

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CXCL8

G0S2

NAMPTP1

NAMPT

PTGS2

FCGR3B

CXCL8

NR4A2

RGS1

CX3CR1

CLC

ZNF331

PDE4B

BRE−AS1

S100P

PFKFB3

EGR2

CXCL2

HBEGF

PLAURMAFF

NR4A3

CXCR2

BCL2A1

NFIL3

IL1B

AREG

SLC2A3

OSM

CREM

ACSL1

EEF1D

GPR183

B3GNT5

BASP1

SLC25A37

GIMAP4

AQP9

CMTM2

MS4A6A

IDI1

HBM

CD83

RGS2

MXD1

SGK1

PROK2

CSRNP1

ZBTB21

HBD

OAS1

CCR2

IDH1CXCL1

TREM1

C5AR1

IL1R2

DENND2D

KCTD12

EGR3

SAMSN1

TNFRSF10C

LITAF

RAB10

ATG2A

ATF3

THBS1

PELI1

MGAM

ZNF267

ALAS2

JUN

HSD17B4

LTF

IRS2

RAB20

SELENOK

MS4A7

VCAN

MS4A6A

CLEC12A

ISCA1

MNDA

RNASE6

TP53INP2

RGCC

SGK223

FAM53C

MIR22HGGAPT

METTL7A

TRG−AS1

CD36USP15

SOD2

GIMAP1

TRIB1

TRIM58

SLC35A1

MPEG1

MRPS31

SMCO4

FKBP5

YTHDF3

IL7R

GNA13

VCAN

DUSP2

CLEC2B

SLC25A39

RTN1

STK38

LRRC8D

ELP3

IFIT2

RB1CC1

TES

EGR1

FOSB

CUL4A

PROSC

MYOF

LYZ

IFI27

RAB18

FAM208A

SLU7

AK2

HERC5

GLG1

SELENOH

ARHGEF6

MRFAP1

1

0.01

10−4

10−6

/1.2/1.5/2 x1.2 x1.5LAIV:(D7 / D0)

adju

sted

p−v

alue

● ●Non−significant (adjusted p−value>0.05) Significant in LAIV:(D7 / D0)Volcano-plot Pairwise comparison

Geneset enrichment

DATA INTERPRETATION THANKS TO WIKIBIOPATH▸ Interactive visualization tool for experimental results allows you

to: • Quickly identify significant biological entities/entity sets of

interest and relevant to the experimental findings • Contextualize the experimental observations to a specific

biological context by applying a filter to the knowledge graph and enriching the graph for the information of interest

‣ WikiBioPath assists you in biological interpretation and enables you to: • Better understand your experimental results in their context • Obtain key insights and formulate new hypotheses for the

mechanism of action • Underlying the experimental observations

INTEGRATIVE ANALYSIS▸ Analysis strategy adaptation to each issues ▸ Data Preprocessing of each data sources individually and then

globally thanks to the AltraBio’s multidisciplinary skills ▸ Use of unsupervised approaches to identify the variabilty

sources and correlated variables: • Principal component analysis (PCA) • Hierarchical clustering • Heat-Maps

‣ Use of statistical and predictive power evaluation approaches: • Random forest • Decision tree • Lasso

Decision tree

Heat-Map ROC curve

Sorted features importance

Distribution of importance

WHY CHOOSE ALTRABIO?▸ 12 years of expertise in the implementation and development of bioinformatic

tools for:• life science data analysis/mining in immunology, oncology, dermo-

cosmetology, …• biological interpretation of results• databases generation

▸ A multidisciplinary team (bioinformaticians/mathematicians and biologists/physicians)

▸ A step-by-step approach with unsupervised and supervised analysis to adapt the analysis process to your problem

▸ Hundreds analyses performed in immunology, oncology and dermo-cosmetology

▸ WikiBioPath, a proprietary tool allowing you to interact with your results

▸ Our disponibility and flexibility

We already worked with industrial, hospital and university partners

HOW CAN WE WORK TOGETHER?

Depending on your needs…

▸ Partner in a collaborative project related to:• innovative biological products (Clinical R&D,

Diagnostic and patient monitoring)• innovative data-analysis, data-mining & data

management tools (fundamental research in bio-knowledge)

• services for disruptive technologies

▸ Subcontractor:• application of services for R&D projects

http://www.altrabio.com 30 rue Pré-Gaudry, 69007 Lyon, France

+33 (0)4 26 84 69 63 julien.nourikyan@altrabio.com

Do not hesitate to contact us