% Encoding: UTF-8

@Article{Key__tutorial_2012,
  author        = {Melissa Key},
  title         = {A tutorial in displaying mass spectrometry-based proteomic data using heat maps},
  journaltitle  = {BMC bioinformatics},
  year          = {2012},
  volume        = {13},
  number        = {16},
  pages         = {1},
  __markedentry = {[Wenhao:4]},
  file          = {:Key_2012.pdf:PDF},
  groups        = {MassSpectrometry},
  journal       = {BMC bioinformatics},
  publisher     = {BioMed Central},
  review        = {One solution is to use a distance metric based on the
correlation between profiles instead of change in location.

The second strategy for handling the variability across
features is to standardize each row (feature) so that it
has a mean of 0 and a standard deviation of 1.},
}

@Article{Larrouy-Maumus__Direct_2016,
  author    = {Gerald Larrouy-Maumus and Abigail Clements and Alain Filloux and Ronan R. McCarthy and Serge Mostowy},
  title     = {Direct detection of lipid A on intact Gram-negative bacteria by {MALDI}-{TOF} mass spectrometry},
  year      = {2016},
  volume    = {120},
  month     = {jan},
  pages     = {68--71},
  doi       = {10.1016/j.mimet.2015.12.004},
  url       = {http://dx.doi.org/10.1016/j.mimet.2015.12.004},
  file      = {:Larrouy-Maumus__Direct_2016 - Direct detection of lipid A on intact Gram-negative bacteria by MALDI-TOF mass spectrometry.pdf:PDF},
  groups    = {MassSpectrometry},
  journal   = {Journal of Microbiological Methods},
  publisher = {Elsevier {BV}},
}

@Article{Larrouy-Maumus__Mycobacterial_2015,
  author    = {G{\'{e}}rald Larrouy-Maumus and Germain Puzo},
  title     = {Mycobacterial envelope lipids fingerprint from direct {MALDI}-{TOF} {MS} analysis of intact bacilli},
  year      = {2015},
  volume    = {95},
  number    = {1},
  month     = {jan},
  pages     = {75--85},
  doi       = {10.1016/j.tube.2014.11.001},
  url       = {http://dx.doi.org/10.1016/j.tube.2014.11.001},
  file      = {:Larrouy-Maumus__Mycobacterial_2015 - Mycobacterial envelope lipids fingerprint from direct MALDI-TOF MS analysis of intact bacilli.pdf:PDF},
  groups    = {MassSpectrometry},
  journal   = {Tuberculosis},
  publisher = {Elsevier {BV}},
}

@Article{Meuleman__Comparison_2008,
  author    = {Wouter Meuleman and Judith Y.M.N. Engwegen and Marie-Christine W. Gast and Jos H. Beijnen and Marcel J.T. Reinders and Lodewyk F.A. Wessels},
  title     = {Comparison of normalisation methods for surface-enhanced laser desorption and ionisation ({SELDI}) time-of-flight ({TOF}) mass spectrometry data},
  journal   = {{BMC} Bioinformatics},
  year      = {2008},
  volume    = {9},
  number    = {1},
  pages     = {88},
  doi       = {10.1186/1471-2105-9-88},
  file      = {:Meuleman__Comparison_2008 - Comparison of normalisation methods for surface-enhanced laser desorption and ionisation (SELDI) time-of-flight (TOF) mass spectrometry data.pdf:PDF},
  groups    = {MassSpectrometry},
  publisher = {Springer Nature},
  review    = {difference between MALDI and SELDI

supervised normalization
},
  url       = {http://dx.doi.org/10.1186/1471-2105-9-88},
}

@Article{Strittmatter__Characterization_2014,
  author        = {Nicole Strittmatter and Monica Rebec and Emrys A. Jones and Ottmar Golf and Alireza Abdolrasouli and Julia Balog and Volker Behrends and Kirill A. Veselkov and Zoltan Takats},
  title         = {Characterization and Identification of Clinically Relevant Microorganisms Using Rapid Evaporative Ionization Mass Spectrometry},
  year          = {2014},
  volume        = {86},
  number        = {13},
  month         = {jul},
  pages         = {6555--6562},
  doi           = {10.1021/ac501075f},
  url           = {http://dx.doi.org/10.1021/ac501075f},
  __markedentry = {[Wenhao:5]},
  file          = {:Strittmatter__Characterization_2014 - Characterization and Identification of Clinically Relevant Microorganisms Using Rapid Evaporative Ionization Mass Spectrometry.pdf:PDF},
  groups        = {MassSpectrometry},
  journal       = {Analytical Chemistry},
  publisher     = {American Chemical Society ({ACS})},
  review        = {unsupervised PCA hclust},
}

@Article{YASUI__data_2003,
  author        = {Yutaka Yasui},
  title         = {A data-analytic strategy for protein biomarker discovery: profiling of high-dimensional proteomic data for cancer detection},
  journaltitle  = {Biostatistics},
  year          = {2003},
  volume        = {4},
  number        = {3},
  pages         = {449--463},
  __markedentry = {[Wenhao:4]},
  file          = {:YASUI__data_2003.pdf:PDF},
  groups        = {MassSpectrometry},
  journal       = {Biostatistics},
  publisher     = {Biometrika Trust},
  review        = {preprocess SELDI},
}

@Article{Yang__Comparison_2009,
  author    = {Chao Yang and Zengyou He and Weichuan Yu},
  title     = {Comparison of public peak detection algorithms for {MALDI} mass spectrometry data analysis},
  year      = {2009},
  volume    = {10},
  number    = {1},
  pages     = {4},
  doi       = {10.1186/1471-2105-10-4},
  url       = {http://dx.doi.org/10.1186/1471-2105-10-4},
  file      = {:Yang__Comparison_2009 - Comparison of public peak detection algorithms for MALDI mass spectrometry data analysis.pdf:PDF},
  groups    = {MassSpectrometry},
  journal   = {{BMC} Bioinformatics},
  publisher = {Springer Science $\mathplus$ Business Media},
  review    = {Each of MS spectra consists of two large vectors corresponding to mass to charge  ratio (m/z) and intensity value, respectively.},
}

@Article{Hansen__new_2004,
  author        = {Michael Edberg Hansen and J{\o}rn Smedsgaard},
  title         = {A new matching algorithm for high resolution mass spectra},
  year          = {2004},
  volume        = {15},
  number        = {8},
  month         = {aug},
  pages         = {1173--1180},
  doi           = {10.1016/j.jasms.2004.03.008},
  url           = {http://dx.doi.org/10.1016/j.jasms.2004.03.008},
  __markedentry = {[Wenhao:4]},
  file          = {:Hansen__new_2004 - A new matching algorithm for high resolution mass spectra.pdf:PDF},
  groups        = {MassSpectrometry},
  journal       = {J Am Soc Mass Spectrom},
  publisher     = {Springer Science $\mathplus$ Business Media},
  review        = {The most widely used approach is binning, using narrow bins.

In most databases spectra are stored as centroid data thus reduced to mass-intensity pairs.},
}

@Article{GUYON__Gene_2002,
  author    = {Guyon, Isabelle and Weston, Jason and Barnhill, Stephen and Vapnik, Vladimir},
  title     = {Gene Selection for Cancer Classification using Support Vector Machines},
  year      = {2002},
  volume    = {46},
  number    = {1-3},
  pages     = {389--422},
  file      = {:GUYON__Gene_2002.pdf:PDF},
  groups    = {MassSpectrometry},
  journal   = {Machine learning},
  keywords  = {diagnosis, diagnostic tests, drug discovery, RNA expression, genomics, gene selection, DNA micro- array, proteomics, cancer classification, feature selection, support vector machines, recursive feature elimination},
  publisher = {Springer},
  review    = {SVM RFE  feature selection},
}

@Book{Wu__STATISTICAL_2006,
  author        = {Yuping Wu},
  title         = {Statistical Methods for the Analysis of Mass Spectrometry Data},
  year          = {2006},
  publisher     = {ProQuest},
  __markedentry = {[Wenhao:4]},
  file          = {:Wu__STATISTICAL_2006.pdf:PDF},
  groups        = {MassSpectrometry},
  institution   = {University of South Carolina},
  review        = {p6 where B(mi) is the baseline level of the instrument, which usually is a decreasing function of m},
  type          = {phdthesis},
}

@Book{G.Casella__Introduction_,
  author    = {Gareth James,Daniela Witten,Trevor Hastie and Robert Tibshirani},
  title     = {An Introduction to Statistical Learning},
  year      = {2015},
  publisher = {Springer},
  file      = {:Editors__Springer_ - Springer Texts in Statistics.pdf:PDF},
  groups    = {MassSpectrometry},
}

@Article{Shao__Use_2012,
  author   = {Changli Shao and Yaping Tian},
  title    = {The Use of Principal Component Analysis in MALDI-TOF MS: a Powerful Tool for Establishing a Mini-optimized Proteomic Profile},
  year     = {2012},
  abstract = {Background—Recently, matrix-assisted laser desorption/ionization time-of-flight mass
spectrometry (MALDI-TOF MS) technology has been applied to the exploration of biomarkers for
early cancer diagnosis, but more effort is required to identify a single sensitive and specific
biomarker. For early diagnosis, a proteomic profile is the gold standard, but inconvenient for
clinical use since the profile peaks are quantitative. It would therefore be helpful to find a
minimized profile, comprising fewer peaks than the original using an existing algorithm and
compare it with other traditional statistical methods.},
  file     = {:Shao__Use_2012.pdf:PDF},
  groups   = {MassSpectrometry},
  keywords = {MALDI-TOF MS; mini-profile; PCA; proteomics},
  review   = {The part of the spectrum with m/z
values less than 1,000 was not used for analysis because signals generally interfered with
peak detection in this area.},
}

@Book{Bishop__pattern_2006,
  author    = {Christopher M. Bishop},
  title     = {pattern recognition and machine learning},
  year      = {2006},
  publisher = {Springer},
  pages     = {738},
  file      = {:PRML.pdf:PDF},
  groups    = {MassSpectrometry},
  journal   = {Machine Learning},
}

@Article{Tong__simpler_2011,
  author    = {Dong L Tong},
  title     = {A simpler method of preprocessing MALDI-TOF MS data for differential biomarker analysis: stem cell and melanoma cancer studies},
  year      = {2011},
  volume    = {8},
  number    = {1},
  pages     = {1},
  file      = {:Tong__simpler_2011.pdf:PDF},
  groups    = {MassSpectrometry},
  journal   = {Clinical proteomics},
  keywords  = {MALDI-TOF, MS profiling, raw data, data preprocessing, stem cell, melanoma},
  publisher = {BioMed Central},
}

@Article{Bruyne__Bacterial_2011,
  author        = {Katrien De Bruyne and Bram Slabbinck and Willem Waegeman and Paul Vauterin and Bernard De Baets and Peter Vandamme},
  title         = {Bacterial species identification from {MALDI}-{TOF} mass spectra through data analysis and machine learning},
  journal       = {Systematic and Applied Microbiology},
  year          = {2011},
  volume        = {34},
  number        = {1},
  pages         = {20--29},
  month         = {feb},
  __markedentry = {[Wenhao:1]},
  abstract      = {T2D machine learning mass spectrum},
  doi           = {10.1016/j.syapm.2010.11.003},
  file          = {:Bruyne__Bacterial_2011 - Bacterial species identification from MALDI-TOF mass spectra through data analysis and machine learning.pdf:PDF},
  groups        = {MassSpectrometry},
  publisher     = {Elsevier {BV}},
  url           = {http://dx.doi.org/10.1016/j.syapm.2010.11.003},
}

@Article{Gibb__MALDIquant_2012,
  author        = {S. Gibb and K. Strimmer},
  title         = {{MALDIquant}: a versatile R package for the analysis of mass spectrometry data},
  journaltitle  = {Bioinformatics},
  year          = {2012},
  volume        = {28},
  number        = {17},
  month         = {jul},
  pages         = {2270--2271},
  __markedentry = {[Wenhao:5]},
  file          = {:Gibb__MALDIquant_2012 - MALDIquant_ a versatile R package for the analysis of mass spectrometry data.pdf:PDF},
  groups        = {MassSpectrometry},
  journal       = {Bioinformatics},
  publisher     = {Oxford University Press ({OUP})},
}

@Article{Tibshirani__Sample_2004,
  author    = {R. Tibshirani and T. Hastie and B. Narasimhan and S. Soltys and G. Shi and A. Koong and Q.-T. Le},
  title     = {Sample classification from protein mass spectrometry, by {\textquotesingle}peak probability contrasts{\textquotesingle}},
  year      = {2004},
  volume    = {20},
  number    = {17},
  month     = {jun},
  pages     = {3034--3044},
  doi       = {10.1093/bioinformatics/bth357},
  url       = {http://dx.doi.org/10.1093/bioinformatics/bth357},
  file      = {:Tibshirani__Sample_2004 - Sample classification from protein mass spectrometry, by _textquotesinglepeak probability contrasts_textquotesingle.pdf:PDF},
  groups    = {MassSpectrometry},
  journal   = {Bioinformatics},
  publisher = {Oxford University Press ({OUP})},
}

@Article{He__Self_2011,
  author    = {He and Jin Wang and James A. Mobley and Joshua Richman and Grizzle},
  title     = {Self-Calibrated Warping for Mass Spectra Alignment},
  year      = {2011},
  month     = {mar},
  pages     = {65},
  doi       = {10.4137/cin.s6358},
  url       = {https://doi.org/10.4137%2Fcin.s6358},
  file      = {:He__Self_2011 - Self-Calibrated Warping for Mass Spectra Alignment.pdf:PDF},
  groups    = {MassSpectrometry},
  journal   = {Cancer Informatics},
  publisher = {Libertas Academica, Ltd.},
}

@Article{Dillies__comprehensive_2013,
  author    = {Dillies, Marie-Agn{\`e}s and Rau, Andrea and Aubert, Julie and Hennequet-Antier, Christelle and Jeanmougin, Marine and Servant, Nicolas and Keime, C{\'e}line and Marot, Guillemette and Castel, David and Estelle, Jordi and others},
  title     = {A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis},
  journal   = {Briefings in bioinformatics},
  year      = {2013},
  volume    = {14},
  number    = {6},
  pages     = {671--683},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis.pdf:PDF},
  groups    = {scRNAseq},
  publisher = {Oxford Univ Press},
  review    = {comprehensive evaluation of normalization methods},
}

@Article{zappia2017splatter,
  author    = {Zappia, Luke and Phipson, Belinda and Oshlack, Alicia},
  title     = {Splatter: Simulation Of Single-Cell RNA Sequencing Data},
  year      = {2017},
  pages     = {133173},
  doi       = {10.1101/133173},
  groups    = {scRNAseq},
  journal   = {bioRxiv},
  publisher = {Cold Spring Harbor Labs Journals},
}

@Article{brennecke2013accounting,
  author    = {Brennecke, Philip and Anders, Simon and Kim, Jong Kyoung and Ko{\l}odziejczyk, Aleksandra A and Zhang, Xiuwei and Proserpio, Valentina and Baying, Bianka and Benes, Vladimir and Teichmann, Sarah A and Marioni, John C and others},
  title     = {Accounting for technical noise in single-cell RNA-seq experiments},
  journal   = {Nature methods},
  year      = {2013},
  volume    = {10},
  number    = {11},
  pages     = {1093--1095},
  doi       = {10.1038/nmeth.2645},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\Accounting for technical noise in single-cell RNA -seq experiments\\Accounting for technical noise in single-cell RNA-seq experiments.pdf:PDF},
  groups    = {scRNAseq},
  publisher = {Nature Research},
}

@Article{Gruen__Validation_2014,
  author    = {Gr{\"u}n, Dominic and Kester, Lennart and Van Oudenaarden, Alexander},
  title     = {Validation of noise models for single-cell transcriptomics},
  journal   = {Nature methods},
  year      = {2014},
  volume    = {11},
  number    = {6},
  pages     = {637--640},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\Validation of noise models for single-cell transcriptomics\\Validation of noise.pdf:PDF},
  groups    = {scRNAseq},
  publisher = {Nature Research},
}

@Article{lun2016step,
  author    = {Lun, Aaron TL and McCarthy, Davis J and Marioni, John C},
  title     = {A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor},
  year      = {2016},
  volume    = {5},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\Aaron\\A step by step scRNAseq\\f1000research-5-10712.pdf:PDF},
  groups    = {Aaron, scRNAseq},
  journal   = {F1000Research},
  publisher = {Faculty of 1000 Ltd},
}

@Article{stegle2015computational,
  author    = {Stegle, Oliver and Teichmann, Sarah A and Marioni, John C},
  title     = {Computational and analytical challenges in single-cell transcriptomics},
  year      = {2015},
  volume    = {16},
  number    = {3},
  pages     = {133--145},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\Computational and analytical.pdf:PDF},
  groups    = {scRNAseq},
  journal   = {Nature Reviews Genetics},
  publisher = {Nature Research},
}

@Article{kolodziejczyk2015technology,
  author    = {Kolodziejczyk, Aleksandra A and Kim, Jong Kyoung and Svensson, Valentine and Marioni, John C and Teichmann, Sarah A},
  title     = {The technology and biology of single-cell RNA sequencing},
  year      = {2015},
  volume    = {58},
  number    = {4},
  pages     = {610--620},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\The Technology and Biology of scRNAseq.pdf:PDF},
  groups    = {scRNAseq},
  journal   = {Molecular cell},
  publisher = {Elsevier},
}

@Article{mccarthy2012differential,
  author    = {McCarthy, Davis J and Chen, Yunshun and Smyth, Gordon K},
  title     = {Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation},
  year      = {2012},
  volume    = {40},
  number    = {10},
  pages     = {4288--4297},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\RNAseq_Rpackage_relatedPaper\\Bulk RNAseq packages\\edgeR\\Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation.pdf:PDF},
  groups    = {scRNAseq},
  journal   = {Nucleic acids research},
  publisher = {Oxford University Press},
}

@Article{conrad2017sparse,
  author        = {Conrad, Tim OF and Genzel, Martin and Cvetkovic, Nada and Wulkow, Niklas and Leichtle, Alexander and Vybiral, Jan and Kutyniok, Gitta and Sch{\"u}tte, Christof},
  title         = {Sparse Proteomics Analysis--a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data},
  year          = {2017},
  volume        = {18},
  number        = {1},
  pages         = {160},
  __markedentry = {[Wenhao:4]},
  file          = {:SPA_Sparse Proteomics Analysis.pdf:PDF},
  groups        = {MassSpectrometry},
  journal       = {BMC bioinformatics},
  publisher     = {BioMed Central},
}

@Article{gibb2015differential,
  author        = {Gibb, Sebastian and Strimmer, Korbinian},
  title         = {Differential protein expression and peak selection in mass spectrometry data by binary discriminant analysis},
  journal       = {Bioinformatics},
  year          = {2015},
  volume        = {31},
  number        = {19},
  pages         = {3156--3162},
  __markedentry = {[Wenhao:5]},
  file          = {:MALDIquant_binary discriminant.pdf:PDF},
  groups        = {MassSpectrometry},
  publisher     = {Oxford University Press},
  review        = {BinDA},
}

@Article{wang2006feature,
  author        = {Wang, Xuena and Zhu, Wei and Pradhan, Kith and Ji, Chen and Ma, Yeming and Semmes, Oliver John and Glimm, James and Mitchell, Joseph},
  title         = {Feature extraction in the analysis of proteomic mass spectra},
  journal       = {Proteomics},
  year          = {2006},
  volume        = {6},
  number        = {7},
  pages         = {2095--2100},
  __markedentry = {[Wenhao:3]},
  file          = {:Wang_et_al-2006-PROTEOMICS.pdf:PDF},
  groups        = {MassSpectrometry},
  publisher     = {Wiley Online Library},
}

@Article{robinson2010scaling,
  author    = {Robinson, Mark D and Oshlack, Alicia},
  title     = {A scaling normalization method for differential expression analysis of RNA-seq data},
  year      = {2010},
  volume    = {11},
  number    = {3},
  pages     = {R25},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\RNAseq_Rpackage_relatedPaper\\Bulk RNAseq packages\\TMM\\TMM.pdf:PDF},
  groups    = {scRNAseq},
  journal   = {Genome biology},
  publisher = {BioMed Central},
  review    = {TMM method},
}

@Article{vallejos2017normalizing,
  author    = {Vallejos, Catalina A and Risso, Davide and Scialdone, Antonio and Dudoit, Sandrine and Marioni, John C},
  title     = {Normalizing single-cell RNA sequencing data: challenges and opportunities},
  journal   = {Nature methods},
  year      = {2017},
  volume    = {14},
  number    = {6},
  pages     = {565},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\Classical paper\\Normalizing single-cell RNA sequencing data Challenges and opportunities.pdf:PDF},
  groups    = {scRNAseq},
  publisher = {Europe PMC Funders},
}

@Article{robinson2007moderated,
  author    = {Robinson, Mark D and Smyth, Gordon K},
  title     = {Moderated statistical tests for assessing differences in tag abundance},
  year      = {2007},
  volume    = {23},
  number    = {21},
  pages     = {2881--2887},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\RNAseq_Rpackage_relatedPaper\\Bulk RNAseq packages\\edgeR\\edgeR_tagwise_dispersion.pdf:PDF},
  groups    = {scRNAseq},
  journal   = {Bioinformatics},
  publisher = {Oxford University Press},
  review    = {edgeR},
}

@Article{love2014moderated,
  author    = {Love, Michael I and Huber, Wolfgang and Anders, Simon},
  title     = {Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2},
  journal   = {Genome Biol.},
  year      = {2014},
  volume    = {15},
  number    = {12},
  pages     = {550},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\RNAseq_Rpackage_relatedPaper\\Bulk RNAseq packages\\DESeq2\\DESeq2_2.pdf:PDF},
  groups    = {scRNAseq},
  publisher = {BioMed Central},
  review    = {DEseq2},
}

@Article{leek2012sva,
  author    = {Leek, Jeffrey T and Johnson, W Evan and Parker, Hilary S and Jaffe, Andrew E and Storey, John D},
  title     = {The sva package for removing batch effects and other unwanted variation in high-throughput experiments},
  year      = {2012},
  volume    = {28},
  number    = {6},
  pages     = {882--883},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\RNAseq_Rpackage_relatedPaper\\Microarray\\ComBat_sva\\ComBat.pdf:PDF},
  groups    = {scRNAseq},
  journal   = {Bioinformatics},
  publisher = {Oxford University Press},
  review    = {Combat},
}

@Article{smyth2005use,
  author    = {Smyth, Gordon K and Michaud, Jo{\"e}lle and Scott, Hamish S},
  title     = {Use of within-array replicate spots for assessing differential expression in microarray experiments},
  year      = {2005},
  volume    = {21},
  number    = {9},
  pages     = {2067--2075},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\RNAseq_Rpackage_relatedPaper\\Microarray\\Limma\\batch.pdf:PDF},
  groups    = {scRNAseq},
  journal   = {Bioinformatics},
  publisher = {Oxford University Press},
  review    = {limma},
}

@Article{risso2014normalization,
  author    = {Risso, Davide and Ngai, John and Speed, Terence P and Dudoit, Sandrine},
  title     = {Normalization of RNA-seq data using factor analysis of control genes or samples},
  year      = {2014},
  volume    = {32},
  number    = {9},
  pages     = {896--902},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\RNAseq_Rpackage_relatedPaper\\RUV\\RUV normalization.pdf:PDF},
  groups    = {scRNAseq},
  journal   = {Nature biotechnology},
  publisher = {Nature Research},
  review    = {RUV},
}

@Article{mccarthy2017scater,
  author    = {McCarthy, Davis J and Campbell, Kieran R and Lun, Aaron TL and Wills, Quin F},
  title     = {Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R},
  year      = {2017},
  volume    = {33},
  number    = {8},
  pages     = {1179--1186},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\RNAseq_Rpackage_relatedPaper\\scRNA_package\\scater\\scaterpre-processing, quality control, normalisation and visualisation of single-cell RNA-seq data in R.pdf:PDF},
  groups    = {scRNAseq},
  journal   = {Bioinformatics},
  publisher = {Oxford University Press},
  review    = {scater},
}

@Article{Bacher__SCnorm_2016,
  author    = {Bacher, Rhonda and Chu, Li-Fang and Leng, Ning and Gasch, Audrey P and Thomson, James A and Stewart, Ron M and Newton, Michael and Kendziorski, Christina},
  title     = {SCnorm: A quantile-regression based approach for robust normalization of single-cell RNA-seq data},
  journal   = {bioRxiv},
  year      = {2016},
  pages     = {090167},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\RNAseq_Rpackage_relatedPaper\\scRNA_package\\SCnorm\\bacher2017.pdf:PDF},
  groups    = {scRNAseq},
  publisher = {Cold Spring Harbor Labs Journals},
  review    = {SCnorm},
}

@Article{vallejos2015basics,
  author    = {Vallejos, Catalina A and Marioni, John C and Richardson, Sylvia},
  title     = {BASiCS: Bayesian analysis of single-cell sequencing data},
  year      = {2015},
  volume    = {11},
  number    = {6},
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  groups    = {scRNAseq},
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  publisher = {Public Library of Science},
  review    = {BASiCS},
}

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  groups    = {scRNAseq},
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}

@Article{rostom2017computational,
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@Article{Argyropoulos__Modeling_2017,
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  year    = {2017},
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@Article{Lun__Pooling_2016,
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UMI},
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@Book{Carlin__Bayesian_2008,
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@Article{Tracy__Precision_2008,
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@PhdThesis{Stanford__Statistical_2015,
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@Article{Soneson__Bias_2017,
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  year      = {2017},
  pages     = {143289},
  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\Bias, robustness and scalability in differential expression analysis of single-cell RNA-seq data.pdf:PDF},
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@Article{Buttner__Assessment_2017,
  author    = {Buttner, Maren and Miao, Zhichao and Wolf, Alexander and Teichmann, Sarah A and Theis, Fabian J},
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  journal   = {bioRxiv},
  year      = {2017},
  pages     = {200345},
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@Article{Blasi__cgCorrect:_2017,
  author    = {Blasi, Thomas and Buettner, Florian and Strasser, Michael K and Marr, Carsten and Theis, Fabian J},
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  file      = {:E\:\\RNAseqProject\\NEWPROJECT_PAPERS\\cgCorrect\\Blasi_2017_Phys._Biol._14_036001.pdf:PDF},
  groups    = {scRNAseq},
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  publisher = {IOP Publishing},
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@Article{haque2017practical,
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@Article{li2017comparison,
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  publisher = {Public Library of Science},
  review    = {A comparison of per sample global scaling and per gene normalization methods for differential expression analysis of RNA-seq data},
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@Article{kim2015characterizing,
  author    = {Kim, Jong Kyoung and Kolodziejczyk, Aleksandra A and Ilicic, Tomislav and Teichmann, Sarah A and Marioni, John C},
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  publisher = {Nature Publishing Group},
  review    = {batch effect data used from Klein (UMI)},
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@Article{kivioja2012counting,
  author    = {Kivioja, Teemu and V{\"a}h{\"a}rautio, Anna and Karlsson, Kasper and Bonke, Martin and Enge, Martin and Linnarsson, Sten and Taipale, Jussi},
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