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قابل دانلود از يكشنبه, ۲۰ فروردين ۱۴۰۲
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فهرست مطالب: Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vContributors. . . . . . . . . . . . . . . . . . . . . . . . . . ix 1 Unveiling the Links Between Peptide Identification and Differential Analysis FDR Controls by Means of a Practical Introduction to Knockoff Filters . . . . . . . 1 2 A Pipeline for Peptide Detection Using Multiple Decoys . . . . . . . . . . . . . . . . . . . . 25 3 Enhanced Proteomic Data Analysis with MetaMorpheus. . . . . . . . . . . . . . . . . . . . . 35 4 Validation of MS/MS Identifications and Label-Free Quantification Using Proline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5 Integrating Identification and Quantification Uncertainty for Differential Protein Abundance Analysis with Triqler. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 6 Left-Censored Missing Value Imputation Approach for MS-Based Proteomics Data with GSimp. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 7 Towards a More Accurate Differential Analysis of Multiple Imputed Proteomics Data with mi4limma . . . . . . . . . . . . . . . . . . . . . 131 8 Uncertainty-Aware Protein-Level Quantification and Differential Expression Analysis of Proteomics Data with seaMass . . . . . . . . . . . . . . . . . . . . . . . 141 9 Statistical Analysis of Quantitative Peptidomics and Peptide-Level Proteomics Data with Prostar . . . . . . . . . . . . . . . . . . . . 163 10 msmsEDA & msmsTests: Label-Free Differential Expression by Spectral Counts . . . . . . . . . . . . . . . . . . . . . . . . 197 11 Exploring Protein Interactome Data with IPinquiry: Statistical Analysis and Data Visualization by Spectral Counts . . . . . . . . . . . . . . . . . . . . . . . . . 243 12 Statistical Analysis of Post-Translational Modifications Quantified by Label-Free Proteomics Across Multiple Biological Conditions with R: Illustration from SARS-CoV-2 Infected Cells . . . . . . . . . . . . . . . . . . . . . . . 267 13 Fast, Free, and Flexible Peptide and Protein Quantification with FlashLFQ . . . . . . . . . . . . . . . . . . . . . . . . . . 303 14 Robust Prediction and Protein Selection with Adaptive PENSE . . . . . . . . . . . . . . 315 15 Multivariate Analysis with the R Package mixOmics . . . . . . . . . . . . . . . . . . . . . . . . . 333 16 Integrating Multiple Quantitative Proteomic Analyses Using MetaMSD . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . 361 17 Application of WGCNA and PloGO2 in the Analysis of Complex Proteomic Data. . . . . . . . . . .. . . . . . . . . . . . . . . 375 Index . . . . . . . . . . . . . . . . . . 391 مشخصات فایل |
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| عنوان (Title): | Statistical Analysis of Proteomic Data_ Methods and Tools |
| نام فایل (File name): | 904-www.GeneProtocols.ir-Statistical Analysis of Proteomic Data_ Methods and Tools-Humana Press (2022).pdf |
| عنوان فارسی (Title in Persian): | آنالیز آماری داده های پروتئومیک- روشها و ابزارها |
| ایجاد کننده: | Thomas Burger |
| زبان (Language): | انگلیسی English |
| سال انتشار: | 2022 |
| شابک ISBN: | 1071619667, 9781071619667 |
| نوع سند (Doc. type): | کتاب |
| فرمت (File extention): | |
| حجم فایل (File size): | 24.7 مگابایت |
| تعداد صفحات (Book length in pages): | 398 |
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