Table 1 Bioinformatics tools developed to assess tumor purity, compute cell proportions, and identifying specific cell-type subsets

UNDO

Identify cell type-specific marker genes, compute sample-wise cellular proportions, and deconvolute mixed expressions into cell-specific expression profiles

[306]

contamDE

Estimate cell proportions and perform differential gene expression analysis from RNA-seq data considering tumor-infiltrating normal cells as contaminants

[260]

ISOpureR

Cancer cells fraction estimation, and personalized patient-specific mRNA abundance profiling from a mixed tumor profile

[261]

ISOLATE

Primary site of origin prediction, sample heterogeneity effect removal and deconvolution, and determination of differentially expressed genes of tumor purity

[307]

ESTIMATE

Gene set enrichment analysis method that uses expression profile of immune, stromal, and tumor cells signature genes to give tumor purity scores

[259]

DeMix

Maximum likelihood-based statistical approach for computing cell fractions, and differential gene expression analysis of tumor purity

[263]

PurBayes

Bayesian statistics modelling approach that uses RNAseq data to estimate sub-clonality and tumor purity

[265]

DeconRNASeq

Deconvolution of heterogeneous tissues using mRNA-seq data. Estimates proportions of distinct immune cell subsets

[308]

PSEA

Computes cell fractions from marker genes expression profiles

[309]

csSAM

Differential gene expression analysis using microarray data for each cell type in the sample and their relative frequencies of occurrence

[254]

NMF

Computes cell-type-specific expression profiles and their proportions without any a-priori information

[310]

DSA

Probabilistic model-based approach that uses RNA-seq data from heterogeneous samples to estimate cell-type-specific transcript abundances

[311]

MMAD

Simultaneous calculation of cell proportions and cell-specific expression profiles; prior knowledge of cell fractions and reference expression profiles are required

[312]

PERT

Probabilistic gene expression deconvolution strategy that corrects perturbations in reference expression profiles of different cell populations of a heterogeneous sample

[313]

LLSR

Computes different cells proportions from reference microarray expression profiles

[314]

CIBERSORT

Estimates cell proportions from complex tissues using their gene expression profiles

[271]

Nanodissection

Computes gene expression profiles of specific cells/tissues using reference expression profiles as training data for this genome-scale machine-learning based approach

[269]

Dsection

Probabilistic model using reference expression profiles and predicted cell proportions information. Estimate cell proportions and cell-specific expression profiles with better accuracy

[268]

MCP-counter

Estimates abundance of two stromal and eight immune cell types of populations in bulk tissues

[251]

EPIC

Computes absolute fractions of tumor and different immune cell types using transcriptomic data

[315]

xCell

Infers abundance of 64 stromal and immune cell types based on cell-specific gene signatures enrichment

[316]

TIMER

Six immune cell-types infiltration quantification across different cancer types based on RNA-seq data

[317]

MethylCIBERSORT

CIBERSORT-based deconvolution method. Uses DNA methylation data from bulk to infer tumor cell fractions

[318]

DeMixT

Extract component-specific proportions and gene expression profiles for every sample

[252]

MuSiC

Single cell RNA sequencing data derived cell type specific expression profiles are used to define cell compositions from bulk RNA sequencing data in complex tissues

[319]

CPM

Deconvolution algorithm that uses single cell RNA sequencing reference expression profiles to infer cellular heterogeneity in complex tissues from bulk transcriptome data

[320]

CIBERSORTx

Estimates sample-wise cell type frequencies from bulk RNA sequencing data using single cell RNA sequencing or bulk-sorted gene expression reference profiles data, and minimizes platform-specific variations

[249]

quanTIseq

Using bulk RNA sequencing data, this method quantitates proportions of 10 types of immune cells

[321]