Mo More Challenges Data and Tools Oliver Kohlbacher Da - PowerPoint PPT Presentation

Mo More ¡ ¡Challenges Data ¡and ¡Tools Oliver ¡Kohlbacher

Da Data 2

Big ¡Data ¡Scare

Gr Growth ¡ ¡of ¡ ¡Omics ¡ ¡Data ¡ ¡(EBI)

Mu Multi-­‑ -­‑Om Omic ics

Proteome Transcriptome Metabolome *ome

Integration Metabolomics 5-­‑Oxoproline Glutamate Cysteine Proteomics GCL GGT Glycine Glutamate-­‑cysteine ¡ligase γ-­‑Glutamyltransferase GSSH GSH Cys-­‑Gly Transcriptomics Nrf2 ¡and ATF4 ¡activation (oxidative ¡stress)

Interoperability 10

Complex ¡experiments ¡imply ¡complex ¡analyses ID pipeline based on accurate mass search ID pipeline based on accurate mass search Some Analytics (on preprocessed/normalized input) Some Analytics (on preprocessed/normalized input) Reporting (note the Data to Report nodes) Reporting (note the Data to Report nodes) Java Snippet Java Snippet Joiner Joiner Row Filter Row Filter Column to Grid Column to Grid Data to Report Data to Report FileConverter FileConverter AccurateMassSearch SmallMoleculeMzTabReader AccurateMassSearch SmallMoleculeMzTabReader Molecule Type Cast Molecule Type Cast Column Filter Column Filter Joiner Joiner Transpose Transpose String Manipulation String Manipulation Cross Validation Cross Validation Interactive Table Interactive Table Node 79 Node 79 Node 81 Node 81 Node 82 Node 82 structure grid structure grid Node 99 Node 99 Node 100 Node 100 Node 104 Node 104 Node 80 Node 80 Node 75 Node 75 Node 101 Node 101 Data to Report Data to Report Node 32 Node 32 Node 68 Node 68 Random Forest Random Forest Node 71 Node 71 Tree Ensemble Tree Ensemble Learner Learner Sorter Sorter Row Filter Row Filter Boxplot of group-wise Boxplot of group-wise TableRow To TableRow To intensities for a single intensities for a single top x di fg erentiators top x di fg erentiators Joiner Joiner Variable Loop Start Variable Loop Start di fg erential compound di fg erential compound Table R-View Table R-View Image To Table Image To Table String Manipulation String Manipulation Loop End Loop End Data to Report Data to Report Random forest on Random forest on sort by quality sort by quality top 10 top 10 all experiments all experiments join with centroid.MZ join with centroid.MZ Node 83 Node 83 Node 66 Node 66 Node 84 Node 84 Node 86 Node 86 Node 85 Node 85 box plots box plots Data Acquisition from mzML Data Acquisition from mzML Data Preparation (missing values, column rename, etc) Data Preparation (missing values, column rename, etc) Statistical Analysis Statistical Analysis Handle Missings Handle Missings load mzML input files load mzML input files Mass trace extraction Mass trace extraction retention time correction and linking retention time correction and linking Input Files Input Files ZipLoopStart ZipLoopStart FeatureFinderMetabo FeatureFinderMetabo ZipLoopEnd ZipLoopEnd MapAlignerPoseClustering MapAlignerPoseClustering FeatureLinkerUnlabeledQT FeatureLinkerUnlabeledQT TextExporter TextExporter ConsensusTextReader ConsensusTextReader Column Filter Column Filter Column Rename Column Rename 0.0 -> ? 0.0 -> ? String Manipulation RowID String Manipulation RowID Splitter Splitter Intensity normalization Intensity normalization Hypothesis testing (t-test) Hypothesis testing (t-test) Multiple hypothesis testing Multiple hypothesis testing rm rows with missings rm rows with missings (Benjamini/Hochberg correction) (Benjamini/Hochberg correction) (or allow at most one) (or allow at most one) Splitter Splitter Joiner Joiner R Snippet R Snippet R Snippet R Snippet R Snippet R Snippet Column Filter Column Filter Node 58 Node 58 Node 97 Node 97 Node 12 Node 12 Node 13 Node 13 Node 29 Node 29 Node 6 Node 6 Node 98 Node 98 Node 96 Node 96 Node 103 Node 103 Node 102 Node 102 Node 91 Node 91 Node 92 Node 92 centroid.* centroid.* and and Node 105 Node 105 c/t_BATxy c/t_BATxy control control bioconductor bioconductor bioconductor bioconductor bioconductor bioconductor rm t/p-stats rm t/p-stats Handle Missings Handle Missings and and Signal Count Signal Count test test Intensity distributions before Intensity distributions before Intensity distributions after normalization Intensity distributions after normalization QQ-Plot of test scores QQ-Plot of test scores normalization normalization rm rows with missings rm rows with missings (or allow at most one) (or allow at most one) LOG Normalization LOG Normalization Box Plot Box Plot LOG Normalization LOG Normalization Box Plot Box Plot Table R-View Table R-View Add #mass traces Add #mass traces as variable as variable Node 61 Node 61 Node 45 Node 45 Node 62 Node 62 Node 46 Node 46 Node 64 Node 64 Interactive Table Interactive Table Node 93 Node 93

Re Reproducibility 13

Usability 15

Ta Tailor-­‑ -­‑made ¡ ¡solutions ¡ ¡dominate ¡ ¡bioinformatics cs Chang, ¡Nature, ¡2015, ¡520:151