Basejump 1.4.0 MacOSX 2.2 MB Basejump is a base64 encoding tool which will help you to manage your css,html… files and the associated images. SimBooster Pro 1.4.0 – System optimizing utility. January 24, 2015 SimBooster Pro is an all-in-one package that includes a variety of system tools to help you clean and protect your Mac.
Major changes
Base Jump 1.4.0 For Macos Free
bcbioRNASeq
S4 class object is now extendingRangedSummarizedExperiment
instead ofSummarizedExperiment
. Consequently, the row annotations are now stored in therowRanges
slot asGRanges
class, instead of in therowData
slot as aDataFrame
. TherowData
accessor still works and returns a data frame of gene/transcript annotations, but these are now coerced from the internally storedGRanges
. TheGRanges
object is acquired automatically from Ensembl usingbasejump::ensembl
. By default,GRanges
are acquired from Ensembl using AnnotationHub and ensembldb. Legacy GRCh37 genome build is supported using the EnsDb.Hsapiens.v75 package.assays
now only slot matrices. We’ve moved the tximport data from the now defunctbcbio
slot to assays. This includes thelengths
matrix from tximport. Additionally, we are optionally slotting DESeq2 variance-stabilized counts (“rlog
”,'vst'
). DESeq2 normalized counts and edgeR TMM counts are calculated on the fly and no longer stored inside thebcbioRNASeq
object.colData
now defaults to returning asdata.frame
instead ofDataFrame
, for easy piping to tidyverse functions.bcbio
slot is now defunct.- FASTA spike-ins (e.g. EGFP, ERCCs) can be defined using the
isSpike
argument during theloadRNASeq
data import step. - Melted counts are now scaled to log2 in the relevant quality control functions rather than using log10. This applies to
plotCountsPerGene
andplotCountDensity
. Note that we are subsetting the nonzero genes as defined by the raw counts here. - Simplified internal
tximport
code to no longer attempt to strip transcript versions. This is required for working with C. elegans transcripts. - Minimal working example dataset is now derived from GSE65267, which is also used in the F1000 paper.
- Added
as(object, 'DESeqDataSet')
coercion method support forbcbioRNASeq
class. This helps us set up the differential expression analysis easily. counts
function now returns DESeq2 normalized counts (normalized = TRUE
) and edgeR TMM counts (normalized = 'tmm'
) on the fly, as suggested by the F1000 reviewers.- Design formula can no longer be slotted into
bcbioRNASeq
object, since we’re not stashing aDESeqDataSet
any more. - Updated Functional Analysis R Markdown template.