-L/usr/lib/
in Makevarsinherits()
for conditionals with class()snn
argument in buildGraph()
due to the parameter snn.k.self
getDifferentialGenes()
based on warnings from sccore::plapply()
fail.on.error=TRUE
in some plapplysgetGeneExpression()
methods for Seurat (lost in merge 552408f)parseCellGroups()
, check if clustering existsscaledMatricesSeurat()
, scaledMatricesSeuratV3()
sccore::plapply()
in updatePairs()
getOdGenesUniformly
and con$correctGenes
collapseCellsByType
and colSumByFactor
are moved to sccorep2app4conos()
for rendering Conos to pagoda2 applicationgetGeneExpression()
for Seurat v2 and v3 (January 2021)raster.dpi
in con$plotEmbedding()
to replace raster.height
and raster.width
, given these parameters are defunct with rewrite of ggrastr
(v0.2.0)[https://github.com/VPetukhov/ggrastr/releases/tag/v0.2.0]plotDEheatmap
functionbalancing.factor.per.sample
in buildGraph
std::cout
to Rcpp::Rcout
(July 2020)saveConosForScanPy()
(July 2020)ht_opt$message = FALSE
for ComplexHeatmap (July 2020)getPerCellTypeDE()
for errors, removing NAs (July 2020)ht_opt$message = FALSE
for ComplexHeatmap (July 2020)getCorrectionVector()
and getPerCellTypeDECorrected
(2 July 2020)neighborhood.average
(4 July 2020)raster.height
and raster.width
from con$plotEmbedding()
, given these parameters are defunct with rewrite of ggrastr
(v0.2.0)[https://github.com/VPetukhov/ggrastr/releases/tag/v0.2.0]sccore
buildGraph
k.same.factor
and balancing.factor.per.sample
to buildGraph
.
It can be used to improve alignment between different conditions: with same.factor.downweight
it gives the system similar to k.self
and k.self.weight
convertToPagoda2
to create Pagoda 2 from Conos. Helpful for PagodaWebApp.getDifferentialGenes
getDifferentialGenes
uses first clustering by defaultcollapseCellsByType
. Note: probably will affect DE results.n_sgd_threads
from uwot
to n.cores
by default. It gives much better parallelization, but kills reproducibility.
Use n.sgd.cores=1
to get reproducible embeddings.target.dims
in UMAP embeddingcor.based
with alingnment.strength == 0
. It removes edges with negative correlation and reduce down-weight of inter-sample edges, which can change results of the alignment.fixed.initial.labels
in propagateLabels
from FALSE
to TRUE
. Presumably, FALSE
should never be used.saveConosForScanPy
getDifferentialGenes
(parameters append.specifisity.metrics
and append.auc
)findSubcommunities
to increase resolution for specific clusterssubgroups
to embeddingPlot
. It allows to plot only cells, belonging to the specified subgroupskeep.limits
to embeddingPlot
getDifferentialGenes
(parameters append.specifisity.metrics
and append.auc
)velocityInfoConos
function for RNA velocity analysis on samples integrated with conos (together with supplementary functions prepareVelocity
and pcaFromConos
)velocityInfoConos
function)getJointCountMatrix
to conos obectsaveConosForScanPy
parseCellGroups
to parse properly cell groupings depending on user settingsestimteWeightEntropyPerCell
to visualize alignment quality per cellbuildGraph
now use PCA space as the defaultcluster.sep.chr
in DE functions is changed from '+' to '<!!>',
as it shouldn't be normally present in cluster namesplotClusterStability
stable.tree.clusters
, get.cluster.graph
and scan.k.modularity
get.cluster.graph
and get_nearest_neighbors
embedding
is stored with samples by rows now (i.e. not transposed anymore)Add the following code to your website.
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