% Generated by Paperpile. Check out http://paperpile.com for more information.
% BibTeX export options can be customized via Settings -> BibTeX.

@ARTICLE{Oldham2008-vu,
  title    = "Functional organization of the transcriptome in human brain",
  author   = "Oldham, Michael C and Konopka, Genevieve and Iwamoto, Kazuya and
              Langfelder, Peter and Kato, Tadafumi and Horvath, Steve and
              Geschwind, Daniel H",
  abstract = "The enormous complexity of the human brain ultimately derives
              from a finite set of molecular instructions encoded in the human
              genome. These instructions can be directly studied by exploring
              the organization of the brain's transcriptome through systematic
              analysis of gene coexpression relationships. We analyzed gene
              coexpression relationships in microarray data generated from
              specific human brain regions and identified modules of
              coexpressed genes that correspond to neurons, oligodendrocytes,
              astrocytes and microglia. These modules provide an initial
              description of the transcriptional programs that distinguish the
              major cell classes of the human brain and indicate that cell
              type-specific information can be obtained from whole brain tissue
              without isolating homogeneous populations of cells. Other modules
              corresponded to additional cell types, organelles, synaptic
              function, gender differences and the subventricular neurogenic
              niche. We found that subventricular zone astrocytes, which are
              thought to function as neural stem cells in adults, have a
              distinct gene expression pattern relative to protoplasmic
              astrocytes. Our findings provide a new foundation for
              neurogenetic inquiries by revealing a robust and previously
              unrecognized organization to the human brain transcriptome.",
  journal  = "Nat. Neurosci.",
  volume   =  11,
  number   =  11,
  pages    = "1271--1282",
  month    =  nov,
  year     =  2008,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Lyall2018-ua,
  title    = "Association of disrupted circadian rhythmicity with mood
              disorders, subjective wellbeing, and cognitive function: a
              cross-sectional study of 91 105 participants from the {UK}
              Biobank",
  author   = "Lyall, Laura M and Wyse, Cathy A and Graham, Nicholas and
              Ferguson, Amy and Lyall, Donald M and Cullen, Breda and Celis
              Morales, Carlos A and Biello, Stephany M and Mackay, Daniel and
              Ward, Joey and Strawbridge, Rona J and Gill, Jason M R and
              Bailey, Mark E S and Pell, Jill P and Smith, Daniel J",
  abstract = "BACKGROUND: Disruption of sleep and circadian rhythmicity is a
              core feature of mood disorders and might be associated with
              increased susceptibility to such disorders. Previous studies in
              this area have used subjective reports of activity and sleep
              patterns, but the availability of accelerometer-based data from
              UK Biobank participants permits the derivation and analysis of
              new, objectively ascertained circadian rhythmicity parameters. We
              examined associations between objectively assessed circadian
              rhythmicity and mental health and wellbeing phenotypes, including
              lifetime history of mood disorder. METHODS: UK residents aged
              37-73 years were recruited into the UK Biobank general population
              cohort from 2006 to 2010. We used data from a subset of
              participants whose activity levels were recorded by wearing a
              wrist-worn accelerometer for 7 days. From these data, we derived
              a circadian relative amplitude variable, which is a measure of
              the extent to which circadian rhythmicity of rest-activity cycles
              is disrupted. In the same sample, we examined cross-sectional
              associations between low relative amplitude and mood disorder,
              wellbeing, and cognitive variables using a series of regression
              models. Our final model adjusted for age and season at the time
              that accelerometry started, sex, ethnic origin, Townsend
              deprivation score, smoking status, alcohol intake, educational
              attainment, overall mean acceleration recorded by accelerometry,
              body-mass index, and a binary measure of childhood trauma.
              FINDINGS: We included 91 105 participants with accelerometery
              data collected between 2013 and 2015 in our analyses. A
              one-quintile reduction in relative amplitude was associated with
              increased risk of lifetime major depressive disorder (odds ratio
              [OR] 1·06, 95\% CI 1·04-1·08) and lifetime bipolar disorder
              (1·11, 1·03-1·20), as well as with greater mood instability
              (1·02, 1·01-1·04), higher neuroticism scores (incident rate ratio
              1·01, 1·01-1·02), more subjective loneliness (OR 1·09,
              1·07-1·11), lower happiness (0·91, 0·90-0·93), lower health
              satisfaction (0·90, 0·89-0·91), and slower reaction times (linear
              regression coefficient 1·75, 1·05-2·45). These associations were
              independent of demographic, lifestyle, education, and overall
              activity confounders. INTERPRETATION: Circadian disruption is
              reliably associated with various adverse mental health and
              wellbeing outcomes, including major depressive disorder and
              bipolar disorder. Lower relative amplitude might be linked to
              increased susceptibility to mood disorders. FUNDING: Lister
              Institute of Preventive Medicine.",
  journal  = "Lancet Psychiatry",
  volume   =  5,
  number   =  6,
  pages    = "507--514",
  month    =  jun,
  year     =  2018,
  language = "en"
}

@ARTICLE{Hughes2010-st,
  title    = "{JTK\_CYCLE}: an efficient nonparametric algorithm for detecting
              rhythmic components in genome-scale data sets",
  author   = "Hughes, Michael E and Hogenesch, John B and Kornacker, Karl",
  abstract = "Circadian rhythms are oscillations of physiology, behavior, and
              metabolism that have period lengths near 24 hours. In several
              model organisms and humans, circadian clock genes have been
              characterized and found to be transcription factors. Because of
              this, researchers have used microarrays to characterize global
              regulation of gene expression and algorithmic approaches to
              detect cycling. This article presents a new algorithm,
              JTK\_CYCLE, designed to efficiently identify and characterize
              cycling variables in large data sets. Compared with COSOPT and
              the Fisher's G test, two commonly used methods for detecting
              cycling transcripts, JTK\_CYCLE distinguishes between rhythmic
              and nonrhythmic transcripts more reliably and efficiently.
              JTK\_CYCLE's increased resistance to outliers results in
              considerably greater sensitivity and specificity. Moreover,
              JTK\_CYCLE accurately measures the period, phase, and amplitude
              of cycling transcripts, facilitating downstream analyses.
              Finally, JTK\_CYCLE is several orders of magnitude faster than
              COSOPT, making it ideal for large-scale data sets. JTK\_CYCLE was
              used to analyze legacy data sets including NIH3T3 cells, which
              have comparatively low amplitude oscillations. JTK\_CYCLE's
              improved power led to the identification of a novel cluster of
              RNA-interacting genes whose abundance is under clear circadian
              regulation. These data suggest that JTK\_CYCLE is an ideal tool
              for identifying and characterizing oscillations in genome-scale
              data sets.",
  journal  = "J. Biol. Rhythms",
  volume   =  25,
  number   =  5,
  pages    = "372--380",
  month    =  oct,
  year     =  2010,
  language = "en"
}

@ARTICLE{Sulli2018-wq,
  title    = "Pharmacological activation of {REV-ERBs} is lethal in cancer and
              oncogene-induced senescence",
  author   = "Sulli, Gabriele and Rommel, Amy and Wang, Xiaojie and Kolar,
              Matthew J and Puca, Francesca and Saghatelian, Alan and Plikus,
              Maksim V and Verma, Inder M and Panda, Satchidananda",
  abstract = "The circadian clock imposes daily rhythms in cell proliferation,
              metabolism, inflammation and DNA damage response. Perturbations
              of these processes are hallmarks of cancer and chronic circadian
              rhythm disruption predisposes individuals to tumour development.
              This raises the hypothesis that pharmacological modulation of the
              circadian machinery may be an effective therapeutic strategy for
              combating cancer. REV-ERBs, the nuclear hormone receptors
              REV-ERB$\alpha$ (also known as NR1D1) and REV-ERB$\beta$ (also
              known as NR1D2), are essential components of the circadian clock.
              Here we show that two agonists of REV-ERBs-SR9009 and SR9011-are
              specifically lethal to cancer cells and oncogene-induced
              senescent cells, including melanocytic naevi, and have no effect
              on the viability of normal cells or tissues. The anticancer
              activity of SR9009 and SR9011 affects a number of oncogenic
              drivers (such as HRAS, BRAF, PIK3CA and others) and persists in
              the absence of p53 and under hypoxic conditions. The regulation
              of autophagy and de novo lipogenesis by SR9009 and SR9011 has a
              critical role in evoking an apoptotic response in malignant
              cells. Notably, the selective anticancer properties of these
              REV-ERB agonists impair glioblastoma growth in vivo and improve
              survival without causing overt toxicity in mice. These results
              indicate that pharmacological modulation of circadian regulators
              is an effective antitumour strategy, identifying a class of
              anticancer agents with a wide therapeutic window. We propose that
              REV-ERB agonists are inhibitors of autophagy and de novo
              lipogenesis, with selective activity towards malignant and benign
              neoplasms.",
  journal  = "Nature",
  volume   =  553,
  number   =  7688,
  pages    = "351--355",
  month    =  jan,
  year     =  2018,
  language = "en"
}

@ARTICLE{Lim2017-cw,
  title    = "Diurnal and seasonal molecular rhythms in human neocortex and
              their relation to Alzheimer's disease",
  author   = "Lim, Andrew S P and Klein, Hans-Ulrich and Yu, Lei and Chibnik,
              Lori B and Ali, Sanam and Xu, Jishu and Bennett, David A and De
              Jager, Philip L",
  abstract = "Circadian and seasonal rhythms are seen in many species, modulate
              several aspects of human physiology, including brain functions
              such as mood and cognition, and influence many neurological and
              psychiatric illnesses. However, there are few data regarding the
              genome-scale molecular correlates underlying these rhythms,
              especially in the human brain. Here, we report widespread,
              site-specific and interrelated diurnal and seasonal rhythms of
              gene expression in the human brain, and show their relationship
              with parallel rhythms of epigenetic modification including
              histone acetylation, and DNA methylation. We also identify
              transcription factor-binding sites that may drive these effects.
              Further, we demonstrate that Alzheimer's disease pathology
              disrupts these rhythms. These data suggest that interrelated
              diurnal and seasonal epigenetic and transcriptional rhythms may
              be an important feature of human brain biology, and perhaps human
              biology more broadly, and that changes in such rhythms may be
              consequences of, or contributors to, diseases such as Alzheimer's
              disease.",
  journal  = "Nat. Commun.",
  volume   =  8,
  pages    = "14931",
  month    =  apr,
  year     =  2017,
  language = "en"
}

@ARTICLE{Yang2010-os,
  title    = "Analyzing circadian expression data by harmonic regression based
              on autoregressive spectral estimation",
  author   = "Yang, Rendong and Su, Zhen",
  abstract = "MOTIVATION: Circadian rhythms are prevalent in most organisms.
              Identification of circadian-regulated genes is a crucial step in
              discovering underlying pathways and processes that are
              clock-controlled. Such genes are largely detected by searching
              periodic patterns in microarray data. However, temporal gene
              expression profiles usually have a short time-series with low
              sampling frequency and high levels of noise. This makes circadian
              rhythmic analysis of temporal microarray data very challenging.
              RESULTS: We propose an algorithm named ARSER, which combines time
              domain and frequency domain analysis for extracting and
              characterizing rhythmic expression profiles from temporal
              microarray data. ARSER employs autoregressive spectral estimation
              to predict an expression profile's periodicity from the frequency
              spectrum and then models the rhythmic patterns by using a
              harmonic regression model to fit the time-series. ARSER describes
              the rhythmic patterns by four parameters: period, phase,
              amplitude and mean level, and measures the multiple testing
              significance by false discovery rate q-value. When tested on well
              defined periodic and non-periodic short time-series data, ARSER
              was superior to two existing and widely-used methods, COSOPT and
              Fisher's G-test, during identification of sinusoidal and
              non-sinusoidal periodic patterns in short, noisy and
              non-stationary time-series. Finally, analysis of Arabidopsis
              microarray data using ARSER led to identification of a novel set
              of previously undetected non-sinusoidal periodic transcripts,
              which may lead to new insights into molecular mechanisms of
              circadian rhythms. AVAILABILITY: ARSER is implemented by Python
              and R. All source codes are available from
              http://bioinformatics.cau.edu.cn/ARSER.",
  journal  = "Bioinformatics",
  volume   =  26,
  number   =  12,
  pages    = "i168--74",
  month    =  jun,
  year     =  2010,
  language = "en"
}

@ARTICLE{Glynn2006-rv,
  title    = "Detecting periodic patterns in unevenly spaced gene expression
              time series using {Lomb-Scargle} periodograms",
  author   = "Glynn, Earl F and Chen, Jie and Mushegian, Arcady R",
  abstract = "MOTIVATION: Periodic patterns in time series resulting from
              biological experiments are of great interest. The commonly used
              Fast Fourier Transform (FFT) algorithm is applicable only when
              data are evenly spaced and when no values are missing, which is
              not always the case in high-throughput measurements. The choice
              of statistic to evaluate the significance of the periodic
              patterns for unevenly spaced gene expression time series has not
              been well substantiated. METHODS: The Lomb-Scargle periodogram
              approach is used to search time series of gene expression to
              quantify the periodic behavior of every gene represented on the
              DNA array. The Lomb-Scargle periodogram analysis provides a
              direct method to treat missing values and unevenly spaced time
              points. We propose the combination of a Lomb-Scargle test
              statistic for periodicity and a multiple hypothesis testing
              procedure with controlled false discovery rate to detect
              significant periodic gene expression patterns. RESULTS: We
              analyzed the Plasmodium falciparum gene expression dataset. In
              the Quality Control Dataset of 5080 expression patterns, we found
              4112 periodic probes. In addition, we identified 243 probes with
              periodic expression in the Complete Dataset, which could not be
              examined in the original study by the FFT analysis due to an
              excessive number of missing values. While most periodic genes had
              a period of 48 h, some had a period close to 24 h. Our approach
              should be applicable for detection and quantification of periodic
              patterns in any unevenly spaced gene expression time-series data.",
  journal  = "Bioinformatics",
  volume   =  22,
  number   =  3,
  pages    = "310--316",
  month    =  feb,
  year     =  2006,
  language = "en"
}

@ARTICLE{Robles2014-gh,
  title    = "In-vivo quantitative proteomics reveals a key contribution of
              post-transcriptional mechanisms to the circadian regulation of
              liver metabolism",
  author   = "Robles, Maria S and Cox, J{\"u}rgen and Mann, Matthias",
  abstract = "Circadian clocks are endogenous oscillators that drive the
              rhythmic expression of a broad array of genes, orchestrating
              metabolism and physiology. Recent evidence indicates that
              post-transcriptional and post-translational mechanisms play
              essential roles in modulating temporal gene expression for proper
              circadian function, particularly for the molecular mechanism of
              the clock. Due to technical limitations in large-scale,
              quantitative protein measurements, it remains unresolved to what
              extent the circadian clock regulates metabolism by driving
              rhythms of protein abundance. Therefore, we aimed to identify
              global circadian oscillations of the proteome in the mouse liver
              by applying in vivo SILAC mouse technology in combination with
              state of the art mass spectrometry. Among the 3000 proteins
              accurately quantified across two consecutive cycles, 6\% showed
              circadian oscillations with a defined phase of expression.
              Interestingly, daily rhythms of one fifth of the liver proteins
              were not accompanied by changes at the transcript level. The
              oscillations of almost half of the cycling proteome were delayed
              by more than six hours with respect to the corresponding,
              rhythmic mRNA. Strikingly we observed that the length of the time
              lag between mRNA and protein cycles varies across the day. Our
              analysis revealed a high temporal coordination in the abundance
              of proteins involved in the same metabolic process, such as
              xenobiotic detoxification. Apart from liver specific metabolic
              pathways, we identified many other essential cellular processes
              in which protein levels are under circadian control, for instance
              vesicle trafficking and protein folding. Our large-scale
              proteomic analysis reveals thus that circadian
              post-transcriptional and post-translational mechanisms play a key
              role in the temporal orchestration of liver metabolism and
              physiology.",
  journal  = "PLoS Genet.",
  volume   =  10,
  number   =  1,
  pages    = "e1004047",
  month    =  jan,
  year     =  2014,
  language = "en"
}

@ARTICLE{Hughes2009-pd,
  title    = "Harmonics of circadian gene transcription in mammals",
  author   = "Hughes, Michael E and DiTacchio, Luciano and Hayes, Kevin R and
              Vollmers, Christopher and Pulivarthy, S and Baggs, Julie E and
              Panda, Satchidananda and Hogenesch, John B",
  abstract = "The circadian clock is a molecular and cellular oscillator found
              in most mammalian tissues that regulates rhythmic physiology and
              behavior. Numerous investigations have addressed the contribution
              of circadian rhythmicity to cellular, organ, and organismal
              physiology. We recently developed a method to look at
              transcriptional oscillations with unprecedented precision and
              accuracy using high-density time sampling. Here, we report a
              comparison of oscillating transcription from mouse liver, NIH3T3,
              and U2OS cells. Several surprising observations resulted from
              this study, including a 100-fold difference in the number of
              cycling transcripts in autonomous cellular models of the
              oscillator versus tissues harvested from intact mice. Strikingly,
              we found two clusters of genes that cycle at the second and third
              harmonic of circadian rhythmicity in liver, but not cultured
              cells. Validation experiments show that 12-hour oscillatory
              transcripts occur in several other peripheral tissues as well
              including heart, kidney, and lungs. These harmonics are lost ex
              vivo, as well as under restricted feeding conditions. Taken in
              sum, these studies illustrate the importance of time sampling
              with respect to multiple testing, suggest caution in use of
              autonomous cellular models to study clock output, and demonstrate
              the existence of harmonics of circadian gene expression in the
              mouse.",
  journal  = "PLoS Genet.",
  volume   =  5,
  number   =  4,
  pages    = "e1000442",
  month    =  apr,
  year     =  2009,
  language = "en"
}

@ARTICLE{Roenneberg2016-qv,
  title    = "The Circadian Clock and Human Health",
  author   = "Roenneberg, Till and Merrow, Martha",
  abstract = "Epidemiological studies provided the first evidence suggesting a
              connection between the circadian clock and human health. Mutant
              mice convincingly demonstrate the principle that dysregulation of
              the circadian system leads to a multitude of pathologies.
              Chrono-medicine is one of the most important upcoming themes in
              the field of circadian biology. Although treatments counteracting
              circadian dysregulation are already being applied (e.g.,
              prescribing strong and regular zeitgebers), we need to comprehend
              entrainment throughout the body's entire circadian network before
              understanding the mechanisms that tie circadian dysregulation to
              pathology. Here, we attempt to provide a systematic approach to
              understanding the connection between the circadian clock and
              health. This taxonomy of (mis)alignments on one hand exposes how
              little we know about entrainment within any organism and which
              'eigen-zeitgeber' signals are used for entrainment by the
              different cells and tissues. On the other hand, it provides focus
              for experimental approaches and tools that will logically map out
              how circadian systems contribute to disease as well as how we can
              treat and prevent them.",
  journal  = "Curr. Biol.",
  volume   =  26,
  number   =  10,
  pages    = "R432--43",
  month    =  may,
  year     =  2016,
  language = "en"
}

@ARTICLE{Benjamini1995-uz,
  title    = "Controlling the False Discovery Rate: A Practical and Powerful
              Approach to Multiple Testing",
  author   = "Benjamini, Yoav and Hochberg, Yosef",
  abstract = "SUMMARY The common approach to the multiplicity problem calls for
              controlling the familywise error rate (FWER). This approach,
              though, has faults, and we point out a few. A different approach
              to problems of multiple significance testing is presented. It
              calls for controlling the expected proportion of falsely rejected
              hypotheses ? the false discovery rate. This error rate is
              equivalent to the FWER when all hypotheses are true but is
              smaller otherwise. Therefore, in problems where the control of
              the false discovery rate rather than that of the FWER is desired,
              there is potential for a gain in power. A simple sequential
              Bonferronitype procedure is proved to control the false discovery
              rate for independent test statistics, and a simulation study
              shows that the gain in power is substantial. The use of the new
              procedure and the appropriateness of the criterion are
              illustrated with examples.",
  journal  = "J. R. Stat. Soc. Series B Stat. Methodol.",
  volume   =  57,
  number   =  1,
  pages    = "289--300",
  month    =  jan,
  year     =  1995
}

@ARTICLE{Chang2018-hv,
  title   = "shiny: Web application framework for r, 2015",
  author  = "Chang, Winston and Cheng, Joe and Allaire, J and Xie, Yihui and
             McPherson, Jonathan and {Others}",
  journal = "R package version",
  volume  =  1,
  number  =  0,
  pages   = "14",
  year    =  2018
}

@ARTICLE{Gaggioni2014-il,
  title    = "Neuroimaging, cognition, light and circadian rhythms",
  author   = "Gaggioni, Giulia and Maquet, Pierre and Schmidt, Christina and
              Dijk, Derk-Jan and Vandewalle, Gilles",
  abstract = "In humans, sleep and wakefulness and the associated cognitive
              processes are regulated through interactions between sleep
              homeostasis and the circadian system. Chronic disruption of sleep
              and circadian rhythmicity is common in our society and there is a
              need for a better understanding of the brain mechanisms
              regulating sleep, wakefulness and associated cognitive processes.
              This review summarizes recent investigations which provide first
              neural correlates of the combined influence of sleep homeostasis
              and circadian rhythmicity on cognitive brain activity. Markers of
              interindividual variations in sleep-wake regulation, such as
              chronotype and polymorphisms in sleep and clock genes, are
              associated with changes in cognitive brain responses in
              subcortical and cortical areas in response to manipulations of
              the sleep-wake cycle. This review also includes recent data
              showing that cognitive brain activity is regulated by light,
              which is a powerful modulator of cognition and alertness and also
              directly impacts sleep and circadian rhythmicity. The effect of
              light varied with age, psychiatric status, PERIOD3 genotype and
              changes in sleep homeostasis and circadian phase. These data
              provide new insights into the contribution of demographic
              characteristics, the sleep-wake cycle, circadian rhythmicity and
              light to brain functioning.",
  journal  = "Front. Syst. Neurosci.",
  volume   =  8,
  pages    = "126",
  month    =  jul,
  year     =  2014,
  keywords = "circadian; cognition; fMRI; inter-individual differences in
              sleep-wake regulation; light; non-image-forming; non-visual;
              sleep",
  language = "en"
}

@ARTICLE{Oh2018-gd,
  title    = "Cytosine modifications exhibit circadian oscillations that are
              involved in epigenetic diversity and aging",
  author   = "Oh, Gabriel and Ebrahimi, Sasha and Carlucci, Matthew and Zhang,
              Aiping and Nair, Akhil and Groot, Daniel E and Labrie, Viviane
              and Jia, Peixin and Oh, Edward S and Jeremian, Richie H and
              Susic, Miki and Shrestha, Tenjin C and Ralph, Martin R and
              Gordevi{\v c}ius, Juozas and Koncevi{\v c}ius, Karolis and
              Petronis, Art",
  abstract = "Circadian rhythmicity governs a remarkable array of fundamental
              biological functions and is mediated by cyclical transcriptomic
              and proteomic activities. Epigenetic factors are also involved in
              this circadian machinery; however, despite extensive efforts,
              detection and characterization of circadian cytosine
              modifications at the nucleotide level have remained elusive. In
              this study, we report that a large proportion of epigenetically
              variable cytosines show a circadian pattern in their modification
              status in mice. Importantly, the cytosines with circadian
              epigenetic oscillations significantly overlap with the cytosines
              exhibiting age-related changes in their modification status. Our
              findings suggest that evolutionary advantageous processes such as
              circadian rhythmicity can also contribute to an organism's
              deterioration.",
  journal  = "Nat. Commun.",
  volume   =  9,
  number   =  1,
  pages    = "644",
  month    =  feb,
  year     =  2018,
  language = "en"
}

@ARTICLE{Schibler2005-yt,
  title    = "Cellular oscillators: rhythmic gene expression and metabolism",
  author   = "Schibler, Ueli and Naef, Felix",
  abstract = "Many biological processes are driven by biological clocks that,
              depending on the frequency they generate, are classified into
              ultradian, circadian and infradian oscillators. In virtually all
              light-sensitive organisms from cyanobacteria to humans, a
              circadian timing system adapts cyclic physiology to geophysical
              time. Recent evidence suggests that even in mammals circadian
              oscillators function in a cell-autonomous manner. In yeast, an
              ultradian oscillator regulates cyclic respiratory activity and
              global gene expression. Circadian oscillators and the ultradian
              yeast respiratory clock share at least four properties: they
              follow limit-cycle kinetics, interweave with cellular metabolism,
              are temperature-compensated and influence the cell division
              clock.",
  journal  = "Curr. Opin. Cell Biol.",
  volume   =  17,
  number   =  2,
  pages    = "223--229",
  month    =  apr,
  year     =  2005,
  language = "en"
}

@ARTICLE{Lim2014-jm,
  title    = "24-hour rhythms of {DNA} methylation and their relation with
              rhythms of {RNA} expression in the human dorsolateral prefrontal
              cortex",
  author   = "Lim, Andrew S P and Srivastava, Gyan P and Yu, Lei and Chibnik,
              Lori B and Xu, Jishu and Buchman, Aron S and Schneider, Julie A
              and Myers, Amanda J and Bennett, David A and De Jager, Philip L",
  abstract = "Circadian rhythms modulate the biology of many human tissues,
              including brain tissues, and are driven by a near 24-hour
              transcriptional feedback loop. These rhythms are paralleled by
              24-hour rhythms of large portions of the transcriptome. The role
              of dynamic DNA methylation in influencing these rhythms is
              uncertain. While recent work in Neurospora suggests that dynamic
              site-specific circadian rhythms of DNA methylation may play a
              role in modulating the fungal molecular clock, such rhythms and
              their relationship to RNA expression have not, to our knowledge,
              been elucidated in mammalian tissues, including human brain
              tissues. We hypothesized that 24-hour rhythms of DNA methylation
              exist in the human brain, and play a role in driving 24-hour
              rhythms of RNA expression. We analyzed DNA methylation levels in
              post-mortem human dorsolateral prefrontal cortex samples from 738
              subjects. We assessed for 24-hour rhythmicity of 420,132 DNA
              methylation sites throughout the genome by considering
              methylation levels as a function of clock time of death and
              parameterizing these data using cosine functions. We determined
              global statistical significance by permutation. We then related
              rhythms of DNA methylation with rhythms of RNA expression
              determined by RNA sequencing. We found evidence of significant
              24-hour rhythmicity of DNA methylation. Regions near
              transcription start sites were enriched for high-amplitude
              rhythmic DNA methylation sites, which were in turn time locked to
              24-hour rhythms of RNA expression of nearby genes, with the nadir
              of methylation preceding peak transcript expression by 1-3 hours.
              Weak ante-mortem rest-activity rhythms were associated with lower
              amplitude DNA methylation rhythms as were older age and the
              presence of Alzheimer's disease. These findings support the
              hypothesis that 24-hour rhythms of DNA methylation, particularly
              near transcription start sites, may play a role in driving
              24-hour rhythms of gene expression in the human dorsolateral
              prefrontal cortex, and may be affected by age and Alzheimer's
              disease.",
  journal  = "PLoS Genet.",
  volume   =  10,
  number   =  11,
  pages    = "e1004792",
  month    =  nov,
  year     =  2014,
  language = "en"
}

@ARTICLE{Wu2016-rd,
  title    = "{MetaCycle}: an integrated {R} package to evaluate periodicity in
              large scale data",
  author   = "Wu, Gang and Anafi, Ron C and Hughes, Michael E and Kornacker,
              Karl and Hogenesch, John B",
  abstract = "Detecting periodicity in large scale data remains a challenge.
              While efforts have been made to identify best of breed
              algorithms, relatively little research has gone into integrating
              these methods in a generalizable method. Here, we present
              MetaCycle, an R package that incorporates ARSER, JTK\_CYCLE and
              Lomb-Scargle to conveniently evaluate periodicity in time-series
              data. MetaCycle has two functions, meta2d and meta3d, designed to
              analyze two-dimensional and three-dimensional time-series
              datasets, respectively. Meta2d implements N-version programming
              concepts using a suite of algorithms and integrating their
              results. AVAILABILITY AND IMPLEMENTATION: MetaCycle package is
              available on the CRAN repository
              (https://cran.r-project.org/web/packages/MetaCycle/index.html)
              and GitHub (https://github.com/gangwug/MetaCycle). CONTACT:
              hogenesch@gmail.comSupplementary information: Supplementary data
              are available at Bioinformatics online.",
  journal  = "Bioinformatics",
  volume   =  32,
  number   =  21,
  pages    = "3351--3353",
  month    =  nov,
  year     =  2016,
  language = "en"
}

@ARTICLE{Zhang2014-ol,
  title    = "A circadian gene expression atlas in mammals: implications for
              biology and medicine",
  author   = "Zhang, Ray and Lahens, Nicholas F and Ballance, Heather I and
              Hughes, Michael E and Hogenesch, John B",
  abstract = "To characterize the role of the circadian clock in mouse
              physiology and behavior, we used RNA-seq and DNA arrays to
              quantify the transcriptomes of 12 mouse organs over time. We
              found 43\% of all protein coding genes showed circadian rhythms
              in transcription somewhere in the body, largely in an
              organ-specific manner. In most organs, we noticed the expression
              of many oscillating genes peaked during transcriptional ``rush
              hours'' preceding dawn and dusk. Looking at the genomic landscape
              of rhythmic genes, we saw that they clustered together, were
              longer, and had more spliceforms than nonoscillating genes.
              Systems-level analysis revealed intricate rhythmic orchestration
              of gene pathways throughout the body. We also found oscillations
              in the expression of more than 1,000 known and novel noncoding
              RNAs (ncRNAs). Supporting their potential role in mediating clock
              function, ncRNAs conserved between mouse and human showed
              rhythmic expression in similar proportions as protein coding
              genes. Importantly, we also found that the majority of
              best-selling drugs and World Health Organization essential
              medicines directly target the products of rhythmic genes. Many of
              these drugs have short half-lives and may benefit from timed
              dosage. In sum, this study highlights critical, systemic, and
              surprising roles of the mammalian circadian clock and provides a
              blueprint for advancement in chronotherapy.",
  journal  = "Proc. Natl. Acad. Sci. U. S. A.",
  volume   =  111,
  number   =  45,
  pages    = "16219--16224",
  month    =  nov,
  year     =  2014,
  keywords = "chronotherapy; circadian; gene networks; genomics; noncoding RNA",
  language = "en"
}


@ARTICLE{Wu2014-mo,
  title    = "Evaluation of five methods for genome-wide circadian gene
              identification",
  author   = "Wu, Gang and Zhu, Jiang and Yu, Jun and Zhou, Lan and Huang,
              Jianhua Z and Zhang, Zhang",
  abstract = "Identification of circadian-regulated genes based on temporal
              transcriptome data is important for studying the regulation
              mechanism of the circadian system. However, various computational
              methods adopting different strategies for the identification of
              cycling transcripts usually yield inconsistent results even for
              the same dataset, making it challenging to choose the optimal
              method for a specific circadian study. To address this challenge,
              we evaluate 5 popular methods, including ARSER (ARS), COSOPT
              (COS), Fisher's G test (FIS), HAYSTACK (HAY), and JTK\_CYCLE
              (JTK), based on both simulated and empirical datasets. Our
              results show that increasing the number of total samples (through
              improving sampling frequency or lengthening the sampling time
              window) is beneficial for computational methods to accurately
              identify circadian transcripts and measure circadian phase. For a
              given number of total samples, higher sampling frequency is more
              important for HAY and JTK, and the longer sampling time window is
              more crucial for ARS and COS, as testified on simulated and
              empirical datasets from which circadian signals are
              computationally identified. In addition, the preference of higher
              sampling frequency or the longer sampling time window is also
              obvious for JTK, ARS, and COS in estimating circadian phases of
              simulated periodic profiles. Our results also indicate that
              attention should be paid to the significance threshold that is
              used for each method in selecting circadian genes, especially
              when analyzing the same empirical dataset with 2 or more methods.
              To summarize, for any study involving genome-wide identification
              of circadian genes from transcriptome data, our evaluation
              results provide suggestions for the selection of an optimal
              method based on specific goal and experimental design.",
  journal  = "J. Biol. Rhythms",
  volume   =  29,
  number   =  4,
  pages    = "231--242",
  month    =  aug,
  year     =  2014,
  keywords = "ARSER; COSOPT; Fisher's G test; HAYSTACK; JTK\_CYCLE; circadian
              gene; circadian rhythms; comparison",
  language = "en"
}


@ARTICLE{Gentleman2004-sk,
  title    = "Bioconductor: open software development for computational biology
              and bioinformatics",
  author   = "Gentleman, Robert C and Carey, Vincent J and Bates, Douglas M and
              Bolstad, Ben and Dettling, Marcel and Dudoit, Sandrine and Ellis,
              Byron and Gautier, Laurent and Ge, Yongchao and Gentry, Jeff and
              Hornik, Kurt and Hothorn, Torsten and Huber, Wolfgang and Iacus,
              Stefano and Irizarry, Rafael and Leisch, Friedrich and Li, Cheng
              and Maechler, Martin and Rossini, Anthony J and Sawitzki, Gunther
              and Smith, Colin and Smyth, Gordon and Tierney, Luke and Yang,
              Jean Y H and Zhang, Jianhua",
  abstract = "The Bioconductor project is an initiative for the collaborative
              creation of extensible software for computational biology and
              bioinformatics. The goals of the project include: fostering
              collaborative development and widespread use of innovative
              software, reducing barriers to entry into interdisciplinary
              scientific research, and promoting the achievement of remote
              reproducibility of research results. We describe details of our
              aims and methods, identify current challenges, compare
              Bioconductor to other open bioinformatics projects, and provide
              working examples.",
  journal  = "Genome Biol.",
  volume   =  5,
  number   =  10,
  pages    = "R80",
  month    =  sep,
  year     =  2004,
  language = "en"
}

@ARTICLE{Levi2007-vg,
  title    = "Circadian rhythms: mechanisms and therapeutic implications",
  author   = "Levi, Francis and Schibler, Ueli",
  abstract = "The mammalian circadian system is organized in a hierarchical
              manner in that a central pacemaker in the suprachiasmatic nucleus
              (SCN) of the brain's hypothalamus synchronizes cellular circadian
              oscillators in most peripheral body cells. Fasting-feeding cycles
              accompanying rest-activity rhythms are the major timing cues in
              the synchronization of many, if not most, peripheral clocks,
              suggesting that the temporal coordination of metabolism and
              proliferation is a major task of the mammalian timing system. The
              inactivation of noxious food components by hepatic, intestinal,
              and renal detoxification systems is among the metabolic processes
              regulated in a circadian manner, with the understanding of the
              involved clock output pathways emerging. The rhythmic control of
              xenobiotic detoxification provides the molecular basis for the
              dosing time-dependence of drug toxicities and efficacy. This
              knowledge can in turn be used in improving or designing
              chronotherapeutics for the patients who suffer from many of the
              major human diseases.",
  journal  = "Annu. Rev. Pharmacol. Toxicol.",
  volume   =  47,
  pages    = "593--628",
  year     =  2007,
  language = "en"
}

@BOOK{Numata2014-ww,
  title     = "Annual, Lunar, and Tidal Clocks: Patterns and Mechanisms of
               Nature's Enigmatic Rhythms",
  editor    = "Numata, Hideharu and Helm, Barbara",
  publisher = "Springer, Tokyo",
  year      =  2014
}

@ARTICLE{Cornelissen2014-sa,
  title    = "Cosinor-based rhythmometry",
  author   = "Cornelissen, Germaine",
  abstract = "A brief overview is provided of cosinor-based techniques for the
              analysis of time series in chronobiology. Conceived as a
              regression problem, the method is applicable to non-equidistant
              data, a major advantage. Another dividend is the feasibility of
              deriving confidence intervals for parameters of rhythmic
              components of known periods, readily drawn from the least squares
              procedure, stressing the importance of prior (external)
              information. Originally developed for the analysis of short and
              sparse data series, the extended cosinor has been further
              developed for the analysis of long time series, focusing both on
              rhythm detection and parameter estimation. Attention is given to
              the assumptions underlying the use of the cosinor and ways to
              determine whether they are satisfied. In particular, ways of
              dealing with non-stationary data are presented. Examples
              illustrate the use of the different cosinor-based methods,
              extending their application from the study of circadian rhythms
              to the mapping of broad time structures (chronomes).",
  journal  = "Theor. Biol. Med. Model.",
  volume   =  11,
  pages    = "16",
  month    =  apr,
  year     =  2014,
  language = "en"
}

@ARTICLE{Bell-Pedersen2005-kb,
  title    = "Circadian rhythms from multiple oscillators: lessons from diverse
              organisms",
  author   = "Bell-Pedersen, Deborah and Cassone, Vincent M and Earnest, David
              J and Golden, Susan S and Hardin, Paul E and Thomas, Terry L and
              Zoran, Mark J",
  abstract = "The organization of biological activities into daily cycles is
              universal in organisms as diverse as cyanobacteria, fungi, algae,
              plants, flies, birds and man. Comparisons of circadian clocks in
              unicellular and multicellular organisms using molecular genetics
              and genomics have provided new insights into the mechanisms and
              complexity of clock systems. Whereas unicellular organisms
              require stand-alone clocks that can generate 24-hour rhythms for
              diverse processes, organisms with differentiated tissues can
              partition clock function to generate and coordinate different
              rhythms. In both cases, the temporal coordination of a
              multi-oscillator system is essential for producing robust
              circadian rhythms of gene expression and biological activity.",
  journal  = "Nat. Rev. Genet.",
  volume   =  6,
  number   =  7,
  pages    = "544--556",
  month    =  jul,
  year     =  2005,
  language = "en"
}

@ARTICLE{Hughes2017-ik,
  title    = "Guidelines for {Genome-Scale} Analysis of Biological Rhythms",
  author   = "Hughes, Michael E and Abruzzi, Katherine C and Allada, Ravi and
              Anafi, Ron and Arpat, Alaaddin Bulak and Asher, Gad and Baldi,
              Pierre and de Bekker, Charissa and Bell-Pedersen, Deborah and
              Blau, Justin and Brown, Steve and Ceriani, M Fernanda and Chen,
              Zheng and Chiu, Joanna C and Cox, Juergen and Crowell, Alexander
              M and DeBruyne, Jason P and Dijk, Derk-Jan and DiTacchio, Luciano
              and Doyle, Francis J and Duffield, Giles E and Dunlap, Jay C and
              Eckel-Mahan, Kristin and Esser, Karyn A and FitzGerald, Garret A
              and Forger, Daniel B and Francey, Lauren J and Fu, Ying-Hui and
              Gachon, Fr{\'e}d{\'e}ric and Gatfield, David and de Goede, Paul
              and Golden, Susan S and Green, Carla and Harer, John and Harmer,
              Stacey and Haspel, Jeff and Hastings, Michael H and Herzel,
              Hanspeter and Herzog, Erik D and Hoffmann, Christy and Hong,
              Christian and Hughey, Jacob J and Hurley, Jennifer M and de la
              Iglesia, Horacio O and Johnson, Carl and Kay, Steve A and Koike,
              Nobuya and Kornacker, Karl and Kramer, Achim and Lamia, Katja and
              Leise, Tanya and Lewis, Scott A and Li, Jiajia and Li, Xiaodong
              and Liu, Andrew C and Loros, Jennifer J and Martino, Tami A and
              Menet, Jerome S and Merrow, Martha and Millar, Andrew J and
              Mockler, Todd and Naef, Felix and Nagoshi, Emi and Nitabach,
              Michael N and Olmedo, Maria and Nusinow, Dmitri A and Pt{\'a}{\v
              c}ek, Louis J and Rand, David and Reddy, Akhilesh B and Robles,
              Maria S and Roenneberg, Till and Rosbash, Michael and Ruben, Marc
              D and Rund, Samuel S C and Sancar, Aziz and Sassone-Corsi, Paolo
              and Sehgal, Amita and Sherrill-Mix, Scott and Skene, Debra J and
              Storch, Kai-Florian and Takahashi, Joseph S and Ueda, Hiroki R
              and Wang, Han and Weitz, Charles and Westermark, P{\aa}l O and
              Wijnen, Herman and Xu, Ying and Wu, Gang and Yoo, Seung-Hee and
              Young, Michael and Zhang, Eric Erquan and Zielinski, Tomasz and
              Hogenesch, John B",
  abstract = "Genome biology approaches have made enormous contributions to our
              understanding of biological rhythms, particularly in identifying
              outputs of the clock, including RNAs, proteins, and metabolites,
              whose abundance oscillates throughout the day. These methods hold
              significant promise for future discovery, particularly when
              combined with computational modeling. However, genome-scale
              experiments are costly and laborious, yielding ``big data'' that
              are conceptually and statistically difficult to analyze. There is
              no obvious consensus regarding design or analysis. Here we
              discuss the relevant technical considerations to generate
              reproducible, statistically sound, and broadly useful
              genome-scale data. Rather than suggest a set of rigid rules, we
              aim to codify principles by which investigators, reviewers, and
              readers of the primary literature can evaluate the suitability of
              different experimental designs for measuring different aspects of
              biological rhythms. We introduce CircaInSilico, a web-based
              application for generating synthetic genome biology data to
              benchmark statistical methods for studying biological rhythms.
              Finally, we discuss several unmet analytical needs, including
              applications to clinical medicine, and suggest productive avenues
              to address them.",
  journal  = "J. Biol. Rhythms",
  volume   =  32,
  number   =  5,
  pages    = "380--393",
  month    =  oct,
  year     =  2017,
  keywords = "ChIP-seq; RNA-seq; biostatistics; circadian rhythms;
              computational biology; diurnal rhythms; functional genomics;
              guidelines; metabolomics; proteomics; systems biology",
  language = "en"
}

@MISC{Campbell2019-vm,
  title   = "Shiny {R} Dashboards",
  author  = "Campbell, Matthew",
  journal = "Learn RStudio IDE",
  pages   = "99--112",
  year    =  2019
}

@ARTICLE{Bingham1982-ct,
  title    = "Inferential statistical methods for estimating and comparing
              cosinor parameters",
  author   = "Bingham, C and Arbogast, B and Guillaume, G C and Lee, J K and
              Halberg, F",
  journal  = "Chronobiologia",
  volume   =  9,
  number   =  4,
  pages    = "397--439",
  month    =  oct,
  year     =  1982,
  language = "en"
}

@ARTICLE{Deckard2013-pm,
  title    = "Design and analysis of large-scale biological rhythm studies: a
              comparison of algorithms for detecting periodic signals in
              biological data",
  author   = "Deckard, Anastasia and Anafi, Ron C and Hogenesch, John B and
              Haase, Steven B and Harer, John",
  abstract = "MOTIVATION: To discover and study periodic processes in
              biological systems, we sought to identify periodic patterns in
              their gene expression data. We surveyed a large number of
              available methods for identifying periodicity in time series data
              and chose representatives of different mathematical perspectives
              that performed well on both synthetic data and biological data.
              Synthetic data were used to evaluate how each algorithm responds
              to different curve shapes, periods, phase shifts, noise levels
              and sampling rates. The biological datasets we tested represent a
              variety of periodic processes from different organisms, including
              the cell cycle and metabolic cycle in Saccharomyces cerevisiae,
              circadian rhythms in Mus musculus and the root clock in
              Arabidopsis thaliana. RESULTS: From these results, we discovered
              that each algorithm had different strengths. Based on our
              findings, we make recommendations for selecting and applying
              these methods depending on the nature of the data and the
              periodic patterns of interest. Additionally, these results can
              also be used to inform the design of large-scale biological
              rhythm experiments so that the resulting data can be used with
              these algorithms to detect periodic signals more effectively.",
  journal  = "Bioinformatics",
  volume   =  29,
  number   =  24,
  pages    = "3174--3180",
  month    =  dec,
  year     =  2013,
  language = "en"
}


@ARTICLE{Hurley2018-hg,
  title    = "Circadian Proteomic Analysis Uncovers Mechanisms of
              {Post-Transcriptional} Regulation in Metabolic Pathways",
  author   = "Hurley, Jennifer M and Jankowski, Meaghan S and De Los Santos,
              Hannah and Crowell, Alexander M and Fordyce, Samuel B and Zucker,
              Jeremy D and Kumar, Neeraj and Purvine, Samuel O and Robinson,
              Errol W and Shukla, Anil and Zink, Erika and Cannon, William R
              and Baker, Scott E and Loros, Jennifer J and Dunlap, Jay C",
  abstract = "Transcriptional and translational feedback loops in fungi and
              animals drive circadian rhythms in transcript levels that provide
              output from the clock, but post-transcriptional mechanisms also
              contribute. To determine the extent and underlying source of this
              regulation, we applied newly developed analytical tools to a
              long-duration, deeply sampled, circadian proteomics time course
              comprising half of the proteome. We found a quarter of expressed
              proteins are clock regulated, but >40\% of these do not arise
              from clock-regulated transcripts, and our analysis predicts that
              these protein rhythms arise from oscillations in translational
              rates. Our data highlighted the impact of the clock on metabolic
              regulation, with central carbon metabolism reflecting both
              transcriptional and post-transcriptional control and opposing
              metabolic pathways showing peak activities at different times of
              day. The transcription factor CSP-1 plays a role in this
              metabolic regulation, contributing to the rhythmicity and phase
              of clock-regulated proteins.",
  journal  = "Cell Syst",
  volume   =  7,
  number   =  6,
  pages    = "613--626.e5",
  month    =  dec,
  year     =  2018,
  keywords = "CSP-1; Neurospora; circadian; metabolism; post-transcriptional
              regulation; proteome; tandem mass tag mass spectrometry;
              translational elongation",
  language = "en"
}


% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@ARTICLE{Krishnaiah2017-lm,
  title    = "Clock Regulation of Metabolites Reveals Coupling between
              Transcription and Metabolism",
  author   = "Krishnaiah, Saikumari Y and Wu, Gang and Altman, Brian J and
              Growe, Jacqueline and Rhoades, Seth D and Coldren, Faith and
              Venkataraman, Anand and Olarerin-George, Anthony O and Francey,
              Lauren J and Mukherjee, Sarmistha and Girish, Saiveda and Selby,
              Christopher P and Cal, Sibel and Er, Ubeydullah and Sianati,
              Bahareh and Sengupta, Arjun and Anafi, Ron C and Kavakli, I Halil
              and Sancar, Aziz and Baur, Joseph A and Dang, Chi V and
              Hogenesch, John B and Weljie, Aalim M",
  abstract = "The intricate connection between the circadian clock and
              metabolism remains poorly understood. We used high temporal
              resolution metabolite profiling to explore clock regulation of
              mouse liver and cell-autonomous metabolism. In liver, ∼50\% of
              metabolites were circadian, with enrichment of nucleotide, amino
              acid, and methylation pathways. In U2 OS cells, 28\% were
              circadian, including amino acids and NAD biosynthesis
              metabolites. Eighteen metabolites oscillated in both systems and
              a subset of these in primary hepatocytes. These 18 metabolites
              were enriched in methylation and amino acid pathways. To assess
              clock dependence of these rhythms, we used genetic perturbation.
              BMAL1 knockdown diminished metabolite rhythms, while CRY1 or CRY2
              perturbation generally shortened or lengthened rhythms,
              respectively. Surprisingly, CRY1 knockdown induced 8 hr rhythms
              in amino acid, methylation, and vitamin metabolites, decoupling
              metabolite from transcriptional rhythms, with potential impact on
              nutrient sensing in vivo. These results provide the first
              comprehensive views of circadian liver and cell-autonomous
              metabolism.",
  journal  = "Cell Metab.",
  volume   =  25,
  number   =  4,
  pages    = "961--974.e4",
  month    =  apr,
  year     =  2017,
  keywords = "LCMS; chronometabolism; chronopharmacology; circadian clock;
              circadian metabolism; mass spectrometry; metabolomics;
              translational transcription feedback loop",
  language = "en"
}


@ARTICLE{Singer2019-lq,
  title    = "Simphony: simulating large-scale, rhythmic data",
  author   = "Singer, Jordan M and Fu, Darwin Y and Hughey, Jacob J",
  abstract = "Simulated data are invaluable for assessing a computational
              method's ability to distinguish signal from noise. Although many
              biological systems show rhythmicity, there is no general-purpose
              tool to simulate large-scale, rhythmic data. Here we present
              Simphony, an R package for simulating data from experiments in
              which the abundances of rhythmic and non-rhythmic features (e.g.,
              genes) are measured at multiple time points in multiple
              conditions. Simphony has parameters for specifying experimental
              design and each feature's rhythmic properties (e.g., amplitude
              and phase). In addition, Simphony can sample measurements from
              Gaussian and negative binomial distributions, the latter of which
              approximates read counts from RNA-seq data. We show an example of
              using Simphony to evaluate the accuracy of rhythm detection. Our
              results suggest that Simphony will aid experimental design and
              computational method development. Simphony is thoroughly
              documented and freely available at
              https://github.com/hugheylab/simphony.",
  journal  = "PeerJ",
  volume   =  7,
  pages    = "e6985",
  month    =  may,
  year     =  2019,
  keywords = "Circadian; Gene expression; Rhythms; Simulation; Transcriptome",
  language = "en"
}

@article {Hutchison118547,
	author = {Hutchison, Alan L. and Dinner, Aaron R.},
	title = {Correcting for Dependent P-values in Rhythm Detection},
	elocation-id = {118547},
	year = {2017},
	doi = {10.1101/118547},
	publisher = {Cold Spring Harbor Laboratory},
	abstract = {There is much interest in using genome-wide expression time series to identify circadian genes. Several methods have been developed to test for rhythmicity in sparsely sampled time series typical of such measurements. Because these methods are statistical in nature, they rely on estimating the probabilities that patterns arise by chance (i.e., p-values). Here we show that leading methods implicitly make inappropriate assumptions of independence when estimating p-values. We show how to correct for the dependence to obtain accurate estimates for statistical significance during rhythm detection.},
	URL = {https://www.biorxiv.org/content/early/2017/03/20/118547},
	eprint = {https://www.biorxiv.org/content/early/2017/03/20/118547.full.pdf},
	journal = {bioRxiv}
}