Computational Systems Biology Methods and Protocols.7z

SCnorm A quantile regression method for accurate and efficientnormalization of scRNA-seqdata. SCnorm uses quantileregression to ...

Table 1(continued)Tool Description Requirements Type Interface Operatingsystem Programinglanguages References Differential expre ...

MAST A logistic regression model is used to test differentialexpression rate betweengroups while a Gaussiangeneralized linear mo ...

Table 1(continued)Tool Description Requirements Type Interface Operatingsystem Programinglanguages References proportion of cell ...

Subpopulation detectionRaceID Uses k-means applied to a similarity matrix of Pearson’scorrelation coefficients for allpairs of c ...

Table 1(continued)Tool Description Requirements Type Interface Operatingsystem Programinglanguages References Destiny Extends di ...

identifying genes that aredifferentially expressedbetween time points or, if dataat multiple time points are notavailable, choos ...

Table 1(continued)Tool Description Requirements Type Interface Operatingsystem Programinglanguages References LEAP Utilizes the ...

TASIC Temporal Assignment of SIngle Cells (TASIC) uses on aprobabilistic graphical modelto integrate expression andtime informat ...

Table 1(continued)Tool Description Requirements Type Interface Operatingsystem Programinglanguages References switchde An R pack ...

Embeddr Laplacian Eigenmaps and principal curves forpseudotemporal ordering andclustering of single-cellRNA-seq data. Embeddrcre ...

Table 1(continued)Tool Description Requirements Type Interface Operatingsystem Programinglanguages References Batch effect remov ...

counts can be collapsed by summing the number of unique bar- codes associated with all reads mapped to a given gene. When perfor ...

obtained directly from the FastQC output. This metric indicates whether there is a problem with the sequencing library generated ...

2.2.1 Normalization of scRNA-seq Data Without UMIs Although the bulk-based normalization strategy has to be used without other c ...

2.2.2 Normalization of scRNA-seq Data with UMIs To correct for amplification bias, the UMIs have been described how molecules ca ...

estimates. This applies to any downstream analysis but is particu- larly important when comparing expression levels between cell ...

methods aiming at inferring the heterogeneity based on sequencing data from bulk samples [133], single-cell transcriptomics prov ...

(Table1), which explicitly take into account all scRNA-seq-specific confounding factors. Unlike the DEG analysis, the identifica ...

computed. This can be done using the extrinsic spike-in molecules as described above—the extent of variability in their expressi ...