Comments (3)
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Hi @cafferychen777 ,
Thank you so much for your support.
I have another question regarding the choice of using a statistical model.
I state that the prediction of the pathways was calculated starting from the biom file normalized in CSS and the abundances were transformed into relative abundances (compositional data).
PICRUSt2 returned me the following table:
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pathway | IBD_10 | IBD_17 | IBD_18 | IBD_19 | IBD_2 |
---|---|---|---|---|---|
1CMET2-PWY | 0.5465172882153324 | 0.3377042200619037 | 0.3480050708737901 | 0.37868503235301076 | 0.5083044705245738 |
ALL-CHORISMATE-PWY | 0.04787401491196773 | 0.0 | 0.16109123022225882 | 0.0674150650166517 | 0.0 |
ANAEROFRUCAT-PWY | 0.5434450173880835 | 0.2113320353615017 | 0.5184411936816795 | 0.3951961385198568 | 0.5823554962659186 |
ANAGLYCOLYSIS-PWY | 0.7538277178508417 | 0.47010082509198325 | 0.4990015807337455 | 0.5348488909894545 | 0.6612861296934521 |
ARG+POLYAMINE-SYN | 0.09654822975725606 | 0.0 | 0.18278652325147193 | 0.1118830385053522 | 0.032285184934744145 |
ARGDEG-PWY | 0.02698526039802911 | 0.0 | 0.13125028626535068 | 0.042193467093528 | 0.0 |
ARGORNPROST-PWY | 0.057156353830507094 | 0.015941504629641053 | 0.18942165025741362 | 0.149949814982684 | 0.18162227360883218 |
ARGSYN-PWY | 0.5956135158560697 | 0.3071337208305732 | 0.24849882084202063 | 0.33723439410332456 | 0.4386114736779196 |
ARGSYNBSUB-PWY | 0.6672876975133343 | 0.3635510647118449 | 0.24907095286223332 | 0.3706586620950412 | 0.4176076103169751 |
ARO-PWY | 0.7732196274665936 | 0.47486507817115475 | 0.3871948003949325 | 0.4765944125060461 | 0.6649511011599307 |
ASPASN-PWY | 0.5099864226673008 | 0.3313803219988792 | 0.23833688894023294 | 0.31962705700866617 | 0.3857929734198072 |
AST-PWY | 0.023076923076923075 | 0.0 | 0.11538461538461538 | 0.03461538461538461 | 0.0 |
BIOTIN-BIOSYNTHESIS-PWY | 0.051862186985359576 | 0.0 | 0.16597112157576788 | 0.061828808052803476 | 0.03542774507624584 |
BRANCHED-CHAIN-AA-SYN-PWY | 0.809119460940484 | 0.48742970351634946 | 0.31026460726705557 | 0.45112014745075385 | 0.533223246144144 |
CALVIN-PWY | 0.7471856063348943 | 0.43539068809626824 | 0.5017490980464553 | 0.558853576717294 | 0.7335935875854149 |
CENTBENZCOA-PWY | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
CENTFERM-PWY | 0.10084227280343115 | 0.004444222095217799 | 0.0 | 0.08962097946255058 | 0.00441333658115254 |
COA-PWY | 0.5453051217028345 | 0.3518796414366713 | 0.344076152890069 | 0.37632569091459495 | 0.602617761047426 |
COBALSYN-PWY | 0.5667093955412954 | 0.33121562231953955 | 0.13833285548273205 | 0.2358862633207529 | 0.5792234415938627 |
CODH-PWY | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
COLANSYN-PWY | 0.03020029891826877 | 0.023168873943814977 | 0.22240290933212184 | 0.008753927046590228 | 0.06327963037493521 |
COMPLETE-ARO-PWY | 0.7980034079041006 | 0.48753676656174344 | 0.39119291357316593 | 0.48629642816901375 | 0.7028157460472372 |
DAPLYSINESYN-PWY | 0.6703393472166221 | 0.4299659400849499 | 0.3272614253100503 | 0.3726560584902267 | 0.5231532428654286 |
DENITRIFICATION-PWY | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
DENOVOPURINE2-PWY | 0.13661965229461256 | 0.093778418536116 | 0.42490701397830993 | 0.35011587756452256 | 0.4261284606944567 |
DTDPRHAMSYN-PWY | 0.7336082448891426 | 0.43600840206699604 | 0.44384054089679187 | 0.5529230588790547 | 0.740065661700592 |
ECASYN-PWY | 0.030186334566619684 | 0.0 | 0.130730569634781 | 0.05191429272823931 | 0.0 |
ENTBACSYN-PWY | 0.06457087428537162 | 0.0 | 0.23592197493758077 | 0.10957497549137835 | 0.0 |
FAO-PWY | 0.0571322203586654 | 4.791657928562685e-07 | 0.21694134380892882 | 0.07621951797554785 | 4.791660644959697e-07 |
FASYN-ELONG-PWY | 0.2681395105494251 | 0.08166754471846616 | 0.3899945097217771 | 0.20262857699489337 | 0.3711544908857412 |
In this output there are zeros, but they are values that concern the expressions of the pathways and not the abundances of the bacteria. So, based on these values, is it right to use the model applied with metagenomeSeq? Or is it recommended to use another statistical model?
Thank again,
Matteo
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