How to remove low abundance and less prevalent data from my dataset?

Hi friends!!!
I have a relative abundance table where samples are in column and rows contain the features (pathways). Something like this (reproducible example):

   # Pathway    ERR300139_Abundance-RELAB   ERR267324_Abundance-RELAB   ERR341905_Abundance-RELAB   ERR092237_Abundance-RELAB
1CMET2-PWY: N10-formyl-tetrahydrofolate biosynthesis    0.00826631  0.00946472  0.00962571  0.00411153
3-HYDROXYPHENYLACETATE-DEGRADATION-PWY: 4-hydroxyphenylacetate degradation  0   0   0   0.000695608
7ALPHADEHYDROX-PWY: cholate degradation (bacteria, anaerobic)   0   0   0   0
AEROBACTINSYN-PWY: aerobactin biosynthesis  0   0   0   0
ALLANTOINDEG-PWY: superpathway of allantoin degradation in yeast    3.32E-05    0   3.35E-05    0
ANAEROFRUCAT-PWY: homolactic fermentation   0.00682776  0.00681683  0.00675732  0.00495716
ANAGLYCOLYSIS-PWY: glycolysis III (from glucose)    0.00866693  0.0100437   0.00829714  0.00524566
ARG+POLYAMINE-SYN: superpathway of arginine and polyamine biosynthesis  0.00106395  0.000544088 0.000774645 0.00370237
ARGDEG-PWY: superpathway of L-arginine, putrescine, and 4-aminobutanoate degradation    0   0   0   0.00164625
ARGININE-SYN4-PWY: L-ornithine de novo  biosynthesis    0.00166327  0.00383993  0.000105528 0.00230283
ARGORNPROST-PWY: arginine, ornithine and proline interconversion    0.000132331 0.000244069 7.96E-05    0.000479006
ARGSYN-PWY: L-arginine biosynthesis I (via L-ornithine) 0.0124159   0.00955758  0.0118644   0.00533077

Now, I want to keep features (i.e. pathways) which are present with abundance >0.0001 and present in at least 10% of samples. Can you please tell me how can I do that?

Thanks,
dpc