Anybody has a reference of any good source to work on NGS ion torrent platform?

We want to conduct exploratory analyses on the influence of personality (Big Five) on health trajectories in humanitarian aid workers. The health trajectories are unevenly distributed with a vast majority of staff being in the healthy trajectory. The internal consistency of the Big Five Inventory is fine and most personality traits correlate significantly with our health outcomes. Yet, the distributions of the personality traits are skewed and have a rather low standard deviation (e.g., agreeableness mean 4.15 out of 5 and SD 0.52). We were wondering if it statistically makes sense to enter these skewed and rather homogeneous data as a covariate in the growth mixture model. I cannot find any information on statistical requirements of covariates for GMMs. Does anyone have information on this or an advice? Thanks!

I want to combine WoS and Scopus bibtext files and to delete dublicates. However, I can't add the files to RStudio. I watched many videos on Youtube about that. They give some codes but these codes doesn't work. For example;

web_data<-convert2df("wos.bib") scopus_data<-convert2df("scopus.bib",dbsource="scopus",format="bibtex")

I need URGENT help.

Hi guys,

I have an mRNA sample that should be incubated in 37C for half of an hour before using. I am now wondering this short time of incubation in high degree might degrade mRNA ?

Thank you

Dear all,

I encountered a weird situation in my research. I have 3 groups, they are all non-parametric and no equal variance as well. I ran a Kruskal-wallis test to compare the difference and my results are significant, p<0.001 However, when I ran post hoc to compare each group, different Post hoc test is giving me completely opposite results. In SPSS, Mann-whitney U with Bonferroni correction, showing me, say, Group 1 > Group 3;

In Jamovi, only DSCF (Dwass-Steel-Critchlow-Fligner test) showed me Group 1<group 3. Reflected in a negative W value MY question is, why is this happening, why Mann-Whitney U and Dunn's are showing one results; and DSCF test show completely opposite? And with Non-Normal, heteroscedastic data, is DSCF test more robust?

Thank you very much for your time

Hi all,

I have recently been attempting to add a C-terminal 6xhis tag to my gene of interest. My reverse primer for this consisted of ~20bp homology to the end of the ORF, omitting the STOP codon - 6Xhis tag - XhoI site - Leader sequence. I successfully amplified the gene and subcloned into pJET 1.2. I have screened the clones by PCR and by restriction digest which indicated the gene of interest was successfully cloned. When sequencing, the end of the gene is correct, however, the tag has not been incoorporated and the STOP codon has remained. My assumption is that during the initial PCR, the gene has amplified correctly but the polymerase has not read through to the 6his tag etc. Since tagging primers are so large the Tm's for the whole primer are very high, thus I calculated by Tm based on the 20bp of homology to the target gene. Any help/advice would be much appreciated. Please ask if any other information would be helpful!

Good day, I need advice.

My nucleotide sequence dataset (n=163; invertebrate mitochondrial DNA; 658 bp) was aligned by Muscle, manually adjusted to remove any stop codons and translates into a protein. I have been able to successfully create Neighbour-Joining trees with the dataset to date.

Now, I am attempting to produce a ML tree with the same dataset, using the bootstrap test method (1000 replicates), with the Kimura 2-parameter substitution model and the Nearest-Neighbour-Interchange (NNI) as the ML heuristic method. On more than one attempt, I started the process and it became "stuck" on a bootstrap replicate number for several hours before I stopped the process and started again. Please advise on how to avoid this and successfully create an ML tree by bootstrapping. Thank you.

Regards,

Tamiko

i have question about NGS sequencing

If the read aligns with mismatches but still the reported position is still much more probable than any other

so In what cases low alignment score but high mapping score??

Hi all.

I am conducting a mediation analysis (model 4) in SPSS using the PROCESS macro by Hayes. I have cross-sectional survey data and want to test the following relation:

Trait perfectionism (X) -> Emotion Dysregulation (M) -> Sound sensitivity (Y) I want to add one covariate in the analysis: a diagnosis of OCPD. My rationale behind this is that both OCPD and perfectionism are strongly related and therefore, as a covariate, such a diagnosis might have an effect on Y.

When adding it to the model, however, it has no statistical significance and the effect is negligible. Therefore, does it make sense to retain it as a covariate if ONLY 12 participants (out of 145) have reported a diagnosis of OCPD?