Changes in version 1.7.28:
o Modified decomposeVar() to return statistics (but not p-values) for
spike-ins when get.spikes=NA. Added block= argument for
mean/variance calculations within each level of a blocking factor,
followed by reporting of weighted averages (using Fisher's method
for p-values). Automatically record global statistics in the
metadata of the output for use in combineVar(). Switched output to
a DataFrame object for consistency with other functions.
o Fixed testVar() to report a p-value of 1 when both the observed and
null variances are zero.
o Allowed passing of arguments to irlba() in denoisePCA() to assist
convergence. Reported low-rank approximations for all genes,
regardless of whether they were used in the SVD. Deprecated design=
argument in favour of manual external correction of confounding
effects. Supported use of a vector or DataFrame in technical=
instead of a function.
o Allowed passing of arguments to prcomp_irlba() in buildSNNGraph() to
assist convergence. Allowed passing of arguments to get.knn(),
switched default algorithm back to a kd-tree.
o Added the buildKNNGraph() function to construct a simple
k-nearest-neighbours graph.
o Fixed a number of bugs in mnnCorrect(), migrated code to C++ and
parallelized functions. Added variance shift adjustment,
calculation of angles with the biological subspace.
o Modified trend specification arguments in trendVar() for greater
flexibility. Switched from ns() to robustSmoothSpline() to avoid
bugs with unloaded predict.ns(). Added block= argument for
mean/variance calculations within each level of a blocking factor.
o Added option to avoid normalization in the SingleCellExperiment
method for improvedCV2(). Switched from ns() to smooth.spline() or
robustSmoothSpline() to avoid bugs.
o Replaced zoo functions with runmed() for calculating the median
trend in DM().
o Added block= argument to correlatePairs() to calculate correlations
within each level of a blocking factor. Deprecated the use of
residuals=FALSE for one-way layouts in design=. Preserve input
order of paired genes in the gene1/gene2 output when
pairings!=NULL.
o Added block= argument to overlapExprs() to calculate overlaps within
each level of a blocking factor. Deprecated the use of
residuals=FALSE for one-way layouts in design=. Switched to
automatic ranking of genes based on ability to discriminate between
groups. Added rank.type= and direction= arguments to control
ranking of genes.
o Modified combineVar() so that it is aware of the global stats
recorded in decomposeVar(). Absence of global statistics in the
input DataFrames now results in an error. Added option to method=
to use Stouffer's method with residual d.f.-weighted Z-scores.
Added weighted= argument to allow weighting to be turned off for
equal batch representation.
o Modified the behaviour of min.mean= in computeSumFactors() when
clusters!=NULL. Abundance filtering is now performed within each
cluster and for pairs of clusters, rather than globally.
o Switched to pairwise t-tests in findMarkers(), rather than fitting a
global linear model. Added block= argument for within-block
t-tests, the results of which are combined across blocks via
Stouffer's method. Added lfc= argument for testing against a
log-fold change threshold. Added log.p= argument to return
log-transformed p-values/FDRs. Removed empirical Bayes shrinkage as
well as the min.mean= argument.
o Added the makeTechTrend() function for generating a mean-variance
trend under Poisson technical noise.
o Added the multiBlockVar() function for convenient fitting of
multiple mean-variance trends per level of a blocking factor.
o Added the clusterModularity() function for assessing the
cluster-wise modularity after graph-based clustering.
o Added the parallelPCA() function for performing parallel analysis to
choose the number of PCs.
o Modified convertT() to return raw counts and size factors for
CellDataSet output.
o Deprecated exploreData(), selectorPlot() in favour of iSEE().
Changes in version 1.6.0:
o Supported parallelization in buildSNNGraph(), overlapExprs() with
BPPARAM options.
o Forced zero-derived residuals to a constant value in
correlatePairs(), overlapExprs().
o Allowed findMarkers() to return IUT p-values, to identify uniquely
expressed genes in each cluster. Added options to specify the
direction of the log-fold changes, to focus on upregulated genes in
each cluster.
o Fixed bug in correlatePairs() when per.gene=TRUE and no spike-ins
are available. Added block.size argument to control caching.
o Switched all C++ code to use the beachmat API. Modified several
functions to accept ANY matrix-like object, rather than only base
matrix objects.
o quickCluster() with method="igraph" will now merge based on
modularity to satisfy min.size requirements. Added max.size option
to restrict the size of the output clusters.
o Updated the trendVar() interface with parametric, method arguments.
Deprecated the trend="semiloess" option in favour of
parametric=TRUE and method="loess". Modified the NLS equation to
guarantee non-negative coefficients of the parametric trend.
Slightly modified the estimation of NLS starting parameters. Second
d.f. of the fitted F-distribution is now reported as df2 in the
output.
o Modified decomposeVar() to automatically use the second d.f. when
test="f".
o Added option in denoisePCA() to return the number of components or
the low-rank approximation. The proportion of variance explained is
also stored as an attribute in all return values.
o Fixed a variety of bugs in mnnCorrect().
Changes in version 1.4.0:
o Switched default BPPARAM to SerialParam() in all functions.
o Added run argument to selectorPlot(). Bug fix to avoid adding an
empty list.
o Added exploreData() function for visualization of scRNA-seq data.
o Minor bug fix to DM() when extrapolation is required.
o Added check for centred size factors in trendVar(), decomposeVar()
methods. Refactored trendVar() to include automatic start point
estimation, location rescaling and df2 estimation.
o Moved spike-in specification to the scater package.
o Deprecated isSpike<- to avoid confusion over input/output types.
o Generalized sandbag(), cyclone() to work for other classification
problems.
o Added test="f" option in testVar() to account for additional
scatter.
o Added per.gene=FALSE option in correlatePairs(), expanded accepted
value types for subset.row. Fixed an integer overflow in
correlatePairs(). Also added information on whether the permutation
p-value reaches its lower bound.
o Added the combineVar() function to combine results from separate
decomposeVar() calls.
o Added protection against all-zero rows in technicalCV2().
o Added the improvedCV2() function as a more stable alternative to
technicalCV2().
o Added the denoisePCA() function to remove technical noise via
selection of early principal components.
o Removed warning requiring at least twice the max size in
computeSumFactors(). Elaborated on the circumstances surrounding
negative size factors. Increased the default number of window sizes
to be examined. Refactored C++ code for increased speed.
o Allowed quickCluster() to return a matrix of ranks for use in other
clustering methods. Added method="igraph" option to perform
graph-based clustering for large numbers of cells.
o Added the findMarkers() function to automatically identify potential
markers for cell clusters.
o Added the overlapExprs() function to compute the overlap in
expression distributions between groups.
o Added the buildSNNGraph() function to build a SNN graph for cells
from their expression profiles.
o Added the correctMNN() function to perform batch correction based on
mutual nearest neighbors.
o Streamlined examples when mocking up data sets.
Changes in version 1.2.0:
o Transformed correlations to a metric distance in quickCluster().
o Removed normalize() in favour of scater's normalize().
o Switched isSpike()<- to accept a character vector rather than a
logical vector, to enforce naming of spike-in sets. Also added
warning code when the specified spike-in sets overlap.
o Allowed compute*Factors() functions to directly return the size
factors.
o Added selectorPlot() function for interactive plotting.
o Switched to a group-based weighted correlation for one-way layouts
in correlatePairs() and correlateNull(), and to a correlation of
residuals for more complex design matrices.
o Added phase assignments to the cyclone() output.
o Implemented Brennecke et al.'s method in the technicalCV2()
function.
o Updated convertTo() to store spike-in-specific size factors as
offsets.
o Moved code and subsetting into C++ to improve memory efficiency.
o Switched to loess-based trend fitting as the default in trendVar(),
replaced polynomial with semi-loess fitting.
o Added significance statistics to output of decomposeVar(), with only
the p-values replaced by NAs for spike-ins.
o Updated documentation and tests.
Changes in version 1.0.0:
o New package scran, for low-level analyses of single-cell RNA
sequencing data.