3. dimension reduction and trajectory inference
@learningbioinfo https://t.co/DBMTnEJn1k It can also be used for dimensionality reduction and trajectory inference.
scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data https://t.co/zJjDFCNL5r
scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data. https://t.co/f4lLiYROdM
RT @BioDecoded: scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data | Genome Biology ht…
RT @BioDecoded: scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data | Genome Biology ht…
RT @BioDecoded: scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data | Genome Biology ht…
RT @BioDecoded: scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data | Genome Biology ht…
RT @BioDecoded: scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data | Genome Biology ht…
RT @SeqComplete: scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data https://t.co/vIiZU…
scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data https://t.co/vIiZUTHqBc #bioinformatics
scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data | Genome Biology https://t.co/gCFnzvevhV #bioinformatics https://t.co/PgN8cEH9ZY
RT @GenomeBiology: scBFA: a method from Li and @QuonBio for taking into account technical variation in scRNA-seq and scATAC-seq data. It us…
RT @GenomeBiology: scBFA: a method from Li and @QuonBio for taking into account technical variation in scRNA-seq and scATAC-seq data. It us…
RT @GenomeBiology: scBFA: a method from Li and @QuonBio for taking into account technical variation in scRNA-seq and scATAC-seq data. It us…
RT @tangming2005: scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data https://t.co/zJjD…
RT @GenomeBiology: scBFA: a method from Li and @QuonBio for taking into account technical variation in scRNA-seq and scATAC-seq data. It us…
scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data https://t.co/zJjDFCw9GR
RT @GenomeBiology: scBFA: a method from Li and @QuonBio for taking into account technical variation in scRNA-seq and scATAC-seq data. It us…
RT @GenomeBiology: scBFA: a method from Li and @QuonBio for taking into account technical variation in scRNA-seq and scATAC-seq data. It us…
RT @GenomeBiology: scBFA: a method from Li and @QuonBio for taking into account technical variation in scRNA-seq and scATAC-seq data. It us…
RT @GenomeBiology: scBFA: a method from Li and @QuonBio for taking into account technical variation in scRNA-seq and scATAC-seq data. It us…
scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data https://t.co/rO93xMDklz
RT @GenomeBiology: scBFA: a method from Li and @QuonBio for taking into account technical variation in scRNA-seq and scATAC-seq data. It us…
RT @GenomeBiology: scBFA: a method from Li and @QuonBio for taking into account technical variation in scRNA-seq and scATAC-seq data. It us…
scBFA: a method from Li and @QuonBio for taking into account technical variation in scRNA-seq and scATAC-seq data. It uses feature detection patterns rather than feature quantification, and can be used for cell type identification and trajectory inference
scBFA: modeling detection patterns to mitigate technical noise in large-scale single-cell genomics data from Prof. @QuonBio's lab https://t.co/Sia0fMhILY