JMP Genomics protocols

View JMP Genomics computational protocol

JMP Genomics statistics

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JMP Genomics specifications


Unique identifier OMICS_01129
Name JMP Genomics
Software type Toolkit/Suite
Interface Graphical user interface
Restrictions to use License purchase required
Operating system Unix/Linux, Windows
Computer skills Medium
Version 13.2.1
Stability Stable
Free trial Yes
Maintained Yes


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  • person_outline JMP Genomics Team <>

Additional information

JMP Genomics in pipelines

PMCID: 5930841
PMID: 29743953
DOI: 10.1186/s13068-018-1116-x

[…] the reads were trimmed for nucleotides with quality score less than 30 before rna-seq analysis to get the rpkm values of protein-coding genes and rrna genes. the rpkm values were then imported into jmp genomics ( and log2-transformed before statistical analysis similar to microarray-based transcriptomic analysis was performed [, , ]., for data normalization […]

PMCID: 5387067
PMID: 28443071
DOI: 10.3389/fmicb.2017.00553

[…] 1.36 × 10-5, adjusted by the bonferroni correction for multiple testing, treating each orf as an independent test. lta positive strains were compared with lta negative strains in a pairwise fashion. jmp genomics (statistical analysis software, cary, nc, usa) was used to construct two-way hierarchical clustering heat maps with centered rows under the fast-ward algorithm using the log2 transformed […]

PMCID: 5387399
PMID: 28397857
DOI: 10.1038/srep46138

[…] count files from the rnaseq reads, the data were primarily filtered to remove transcripts with low counts (sum of counts less than 100 across samples). filtered samples were kdmm normalized using jmp genomics 7.0 (sas, cary nc) and further filtered by removing rows with 40% zero counts. however, kdmm normalization could not normalize the outliers present in the experiment. so, to avoid bias […]

PMCID: 5481029
PMID: 28640866
DOI: 10.1371/journal.pone.0179879

[…] were adjusted for false discovery rate using the benjamini-hochberg method []. pairwise analysis and hierarchical clustering of samples was performed using bioconductor edger version 3.2.3 and jmp genomics respectively. raw sequencing files from abi solid sage analyses have been deposited in ncbi’s gene expression omnibus (geo; with the accession number […]

PMCID: 5513560
PMID: 28715485
DOI: 10.1371/journal.pone.0181265

[…] using tophat 2 (v2.0.13), [] and read counts were obtained using ht-seq (v0.6.1), []. differential expression of genes was determined using jmp genomics software (v7.1, sas institute inc., cary, nc usa) with the basic rna-seq workflow. a mixed model was used for analysis of variance with the fixed effects being genotype, treatment […]

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JMP Genomics in publications

PMCID: 5947867
PMID: 29642003
DOI: 10.1016/j.celrep.2018.03.067

[…] suite (). the statistical significance of each bioprocess was calculated using a negative logarithm (−log10) of the p value. the heatmap was constructed on differentially expressed genes using jmp genomics 6.0., nih 3t3 and normal human lung fibroblast ccl-210 (atcc) cells were cultured as described previously (). plasmid and small interfering rna (sirna) transfections were performed using […]

PMCID: 5887222
PMID: 29632556
DOI: 10.1186/s13068-018-1095-y

[…] very-sensitive preset option expect the number of mismatches was set to 1 [, ], and reads were counted with htseq []. principle component analysis (pca) was used to check for sample variation using jmp genomics 8 (sas institute, cary, nc, usa). differential expression analysis was performed with deseq 2 []. genes were considered significantly differential expressed when their adjusted p values […]

PMCID: 5878102
PMID: 29610666
DOI: 10.1002/prp2.392

[…] agilent technologies). array slides were xdr‐scanned and analyzed with feature extraction software version (agilent technologies). statistical analysis and visualization was performed with jmp genomics 7.0 (sas institute, boeblingen, germany). full gene array data were submitted to the gene expression omnibus., reverse transcription was performed with taqman reverse transcription […]

PMCID: 5907600
PMID: 29574459
DOI: 10.1161/JAHA.117.008315

[…] coefficients without definition of an arbitrary reference group., next, we constructed a partial regression diagram including multivariable‐adjusted changes in lv phenotype and serum insulin using jmp genomics 6.0. this approach fits covariance selection models, estimating the correlation between pairs of variables adjusted for their correlations with all other variables in the network (ie, […]

PMCID: 5859397
PMID: 29554878
DOI: 10.1186/s12864-018-4584-2

[…] ; 2.5) using r version 3.2.0 []. transcriptional effects were analyzed between samples from animals fed l, m, and h diets. relative changes of transcript abundance were analyzed using a linear model (jmp genomics 7.0), including the effects of diet, sire, sex, tissue, and interactions (vijkl = μ + dieti + sirej + sexk + tissuel + dieti*tissuel + errorijkl). p-values were converted to a set of q-va […]

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