Skip to content

Commit

Permalink
update
Browse files Browse the repository at this point in the history
  • Loading branch information
Jakob Russel committed Mar 26, 2018
1 parent 321412d commit ee4f83b
Showing 1 changed file with 32 additions and 60 deletions.
92 changes: 32 additions & 60 deletions README.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -77,58 +77,33 @@ higher effectSize or with a pruned dataset (see `preDA`)

summary(test)

## Method AUC FPR FDR Spike.detect.rate Score
## MgSeq Feature (msf) 1.000 0.000 0.000 1.0 1.000
## RAIDA (rai) 1.000 0.000 0.000 1.0 1.000
## LIMMA voom (vli) 1.000 0.035 0.031 1.0 0.969
## DESeq2 (ds2x) 1.000 0.035 0.062 1.0 0.938
## DESeq2 man. geoMeans (ds2) 1.000 0.035 0.062 1.0 0.938
## EdgeR exact - TMM (ere) 1.000 0.043 0.062 1.0 0.938
## EdgeR exact - RLE (ere2) 1.000 0.049 0.118 1.0 0.882
## EdgeR qll - TMM (erq) 1.000 0.049 0.118 1.0 0.882
## SAMseq (sam) 1.000 NA 0.118 1.0 0.882
## EdgeR qll - RLE (erq2) 1.000 0.054 0.167 1.0 0.833
## MgSeq ZIG (zig) 0.980 0.127 0.434 0.9 0.457
## ALDEx2 wilcox (adx) 1.000 0.097 0.545 1.0 0.455
## ALDEx2 t-test (adx) 1.000 0.124 0.583 1.0 0.417
## Log t-test (ltt) 1.000 0.670 0.901 1.0 0.099
## Log LIMMA (lli) 1.000 0.689 0.906 1.0 0.094
## Log t-test2 (ltt2) 1.000 0.968 0.924 1.0 0.076
## Quasi-Poisson GLM (qpo) 1.000 0.970 0.924 1.0 0.076
## Log LIMMA 2 (lli2) 1.000 0.989 0.925 1.0 0.075
## Negbinom GLM (neb) 1.000 0.989 0.925 1.0 0.075
## Poisson GLM (poi) 1.000 1.000 0.925 1.0 0.075
## t-test (ttt) 0.986 0.968 0.924 1.0 0.075
## Wilcox (wil) 0.884 0.957 0.924 1.0 0.067
## Permutation (per) 0.595 0.962 0.924 1.0 0.045
## ZI-NegBin GLM (znb) 0.500 0.000 0.000 0.0 0.000
## ZI-Poisson GLM (zpo) 0.500 0.000 0.000 0.0 0.000
## Score.5% Score.95%
## 1.000 1.000
## 0.577 1.000
## 0.536 1.000
## 0.556 1.000
## 0.556 1.000
## 0.536 1.000
## 0.536 1.000
## 0.536 1.000
## 0.500 0.938
## 0.500 1.000
## 0.000 0.652
## 0.214 0.556
## 0.183 0.455
## 0.081 0.109
## 0.081 0.101
## 0.075 0.079
## 0.073 0.079
## 0.075 0.079
## 0.075 0.079
## 0.075 0.076
## 0.069 0.078
## 0.065 0.071
## 0.042 0.047
## 0.000 0.000
## 0.000 0.000
## Method AUC FPR FDR Spike.detect.rate Score Score.5% Score.95%
## MgSeq Feature (msf) 1.000 0.000 0.000 1.0 1.000 1.000 1.000
## RAIDA (rai) 1.000 0.000 0.000 1.0 1.000 0.577 1.000
## LIMMA voom (vli) 1.000 0.035 0.031 1.0 0.969 0.536 1.000
## DESeq2 (ds2x) 1.000 0.035 0.062 1.0 0.938 0.556 1.000
## DESeq2 man. geoMeans (ds2) 1.000 0.035 0.062 1.0 0.938 0.556 1.000
## EdgeR exact - TMM (ere) 1.000 0.043 0.062 1.0 0.938 0.536 1.000
## EdgeR exact - RLE (ere2) 1.000 0.049 0.118 1.0 0.882 0.536 1.000
## EdgeR qll - TMM (erq) 1.000 0.049 0.118 1.0 0.882 0.536 1.000
## SAMseq (sam) 1.000 NA 0.118 1.0 0.882 0.500 0.938
## EdgeR qll - RLE (erq2) 1.000 0.054 0.167 1.0 0.833 0.500 1.000
## MgSeq ZIG (zig) 0.980 0.127 0.434 0.9 0.457 0.000 0.652
## ALDEx2 wilcox (adx) 1.000 0.097 0.545 1.0 0.455 0.214 0.556
## ALDEx2 t-test (adx) 1.000 0.124 0.583 1.0 0.417 0.183 0.455
## Log t-test (ltt) 1.000 0.670 0.901 1.0 0.099 0.081 0.109
## Log LIMMA (lli) 1.000 0.689 0.906 1.0 0.094 0.081 0.101
## Log t-test2 (ltt2) 1.000 0.968 0.924 1.0 0.076 0.075 0.079
## Quasi-Poisson GLM (qpo) 1.000 0.970 0.924 1.0 0.076 0.073 0.079
## Log LIMMA 2 (lli2) 1.000 0.989 0.925 1.0 0.075 0.075 0.079
## Negbinom GLM (neb) 1.000 0.989 0.925 1.0 0.075 0.075 0.079
## Poisson GLM (poi) 1.000 1.000 0.925 1.0 0.075 0.075 0.076
## t-test (ttt) 0.986 0.968 0.924 1.0 0.075 0.069 0.078
## Wilcox (wil) 0.884 0.957 0.924 1.0 0.067 0.065 0.071
## Permutation (per) 0.595 0.962 0.924 1.0 0.045 0.042 0.047
## ZI-NegBin GLM (znb) 0.500 0.000 0.000 0.0 0.000 0.000 0.000
## ZI-Poisson GLM (zpo) 0.500 0.000 0.000 0.0 0.000 0.000 0.000
##

# MetagenomeSeq Featue model appears to be the best
res1 <- DA.msf(df, predictor = vec)
Expand All @@ -152,14 +127,11 @@ higher effectSize or with a pruned dataset (see `preDA`)

**Things to consider:**

[Do you have a paired or blocked experimental
design](#if-you-have-a-paired-or-blocked-experimental-design) [Do you
have covariates?](#if-you-have-covariates) [Does your predictor have
more than two
classes?](#if-your-predictor-is-categorical-with-more-than-two-levels)
[Is your data normalized externally or is it absolute
abundances?](#if-data-is-normalized-externally-or-represent-absolute-abundances)
[Do you have a Phyloseq object?](#if-you-have-a-phyloseq-object)
- [Do you have a paired or blocked experimental design](#if-you-have-a-paired-or-blocked-experimental-design)
- [Do you have covariates?](#if-you-have-covariates)
- [Does your predictor have more than two classes?](#if-your-predictor-is-categorical-with-more-than-two-levels)
- [Is your data normalized externally or is it absolute abundances?](#if-data-is-normalized-externally-or-represent-absolute-abundances)
- [Do you have a Phyloseq object?](#if-you-have-a-phyloseq-object)

#### Main functions:

Expand Down

0 comments on commit ee4f83b

Please sign in to comment.