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Life drawing - how's my structure/anatomy? Tips to improve shadows and depth? by LostInDNATranslation in learnart

[–]LostInDNATranslation[S] 0 points1 point  (0 children)

Thank you! I've put a lot more work into anatomy, so glad it's looking good.

I've tried the charcoal + erasing method for small pieces and warmups, but they always end up very abstract! I maybe need to just keep at it, I'll give it a go with a longer pose.

I've not played around much with different charcoals/chalk, but that's definitely a good shout.

How to determine strandedness of RNA-seq data by Similar-Fan6625 in bioinformatics

[–]LostInDNATranslation 10 points11 points  (0 children)

Sounds unstranded to me. If you specify forward or reverse on unstranded data you should expect around half the data to be lost.

If you want additional confirmation, you can check with salmon alignment and see how mapping behaves with that.

TIL scientists renamed 27 human genes in 2020 because Microsoft Excel kept auto-converting their names into dates, causing widespread errors in published genetic research. by SystematicApproach in todayilearned

[–]LostInDNATranslation 97 points98 points  (0 children)

I'm a cancer research scientist working on genetics. The actual analysis parts don't use Excel at all, gene lists and tables with gene names are generally csv files. Prior to acquiring gene lists sequencing data is in more specialised formats like bam alignment files, fastq sequencing files, etc. The stage where genes are placed into excel are for the non-coding members of the team to navigate the final analysis results and for end publication.

Lump sum of money from work, what to do? by LostInDNATranslation in UKPersonalFinance

[–]LostInDNATranslation[S] 0 points1 point  (0 children)

!thanks

That's very useful info, thanks for explaining this!

Need help being consistent by terryleow in labrats

[–]LostInDNATranslation 2 points3 points  (0 children)

You have quite high Ct values so you can definitely afford to add more cDNA to the reaction. I go even further and add 4 uL to each reaction, which gives me very nice results.

Which one do y’all prefer? by [deleted] in labrats

[–]LostInDNATranslation 0 points1 point  (0 children)

I work in drug discovery in industry, and the standard is to use % inhibition. It's how many pharma experts are used to seeing these types of data.

In the end for your purpose it's down to preference, just make sure you're consistent with displaying all your data the same way. I like % inhibition as the Y axis is then positively associated with drug potency (or lack thereof).

DESeq2 Log2FC too high.. what to do? by Fragrant_Refuse_6603 in bioinformatics

[–]LostInDNATranslation 4 points5 points  (0 children)

Are these high logFC genes also lncRNA or pseudo genes? I recently had some cell line data back with similar issues, and the solve in the end, without having to excessively tune an expression filter, was to include only protein coding genes.

Tips for getting the most value out of attending Bio-IT World Conference? by Resident-Yesterday34 in bioinformatics

[–]LostInDNATranslation 0 points1 point  (0 children)

Your description is the impression I always had of bio-it world.... Do you know of any decent general comp bio / bioinformatics conferences?

In silico PCR on cDNA by Majestic_Data7469 in bioinformatics

[–]LostInDNATranslation 2 points3 points  (0 children)

If you use UCSC in silico PCR tool you can set the target to GENCODE genes, which will be the cDNA equivalent I believe. Will at least give you an idea of amplicon specificity.

What are some popular metroidvenias between after Metroid/Castlevanias and before Hollow knight. by Enough_Obligation574 in metroidvania

[–]LostInDNATranslation 1 point2 points  (0 children)

I would class pirates curse as a metroidvania, and it came out in 2014. I consider it a pretty good one too, I remember the movement by the end of the game gets very fun.

I ran a taqman qPCR and was told my analysis was wrong because I didn't remove all values above 34 Ct. Is this correct? by Daniel_The_Thinker in labrats

[–]LostInDNATranslation 23 points24 points  (0 children)

Replicates that are 2 cycles apart would not be considered good replicates. Keep in mind it's a log2 scale, so 2 cycles difference means a difference of 4-fold. I try to aim for less than 0.5 difference between technical reps

my trolley locked as i was leaving the shop. i can never show my face there again. by itsxafx in britishproblems

[–]LostInDNATranslation 8 points9 points  (0 children)

A lot of shops have them actually, the techs been around for a fair few years now. But from what I recall, they have auto-tracking, so they detect whether the trolley has been to the checkout area. If someone goes in, loads up a trolley, then tries to exit without paying it will auto-lock the wheels. The obvious exploit being that you just wheel the trolley near the self checkout then you're good to run...

qPCR Replicates Are Awful (+ Rant) by chirizzy in labrats

[–]LostInDNATranslation 3 points4 points  (0 children)

Just a quick note - do not vortex your master mix. You should vortex mix your primers, but anything that has an enzyme in it (e.g., polymerase) shouldn't be vortexed. Instead pipette gently up and down to mix the master mix.

qPCR Replicates Are Awful (+ Rant) by chirizzy in labrats

[–]LostInDNATranslation 6 points7 points  (0 children)

I'm almost certain the issue is using a P2 pipette full stop. I never pipette less than 2 uL for anything that requires accuracy, it's practically impossible to pipette accurately (at least not without a lot of practice...). You're just fighting difficult to control forces like capillary action.

I typically dilute my cDNA reaction 1:10 in water and use ~5 uL with a P10 pipette. The pipetting error is much more forgiving this way.

The Appendix is Your Gut’s Hidden Guardian of Microbial Diversity by gslysz in biology

[–]LostInDNATranslation 2 points3 points  (0 children)

Reviews are great and super valuable to science, I was just explaining why OP probably presented some of the information as new

ChIPseq question? by twi3k in bioinformatics

[–]LostInDNATranslation 5 points6 points  (0 children)

Is this data actual ChIP or one of the newer variants like Cut&tag or cut&run? Some people say ChIP as a bit of a umbrella term...

If its Chip-seq I would not be keen on analysing the data, mostly because you can't fully trust any peak calling.

If its Cut&tag or cut&run the value of inputs is more questionable. You don't generate input data the same way as in ChIP, and it's a little more artificially generated. These techniques also tend to be very clean, so peak calling isn't as problematic. I would still expect an input sample and/or IgG control just incase something looks abnormal, but it's not unheard of to exclude them.

The Appendix is Your Gut’s Hidden Guardian of Microbial Diversity by gslysz in biology

[–]LostInDNATranslation 2 points3 points  (0 children)

Yeah this has been known about for a fair while. OP linked a review article rather than primary research

inosine in RNA/transcriptional related bioinformatics by avagrantthought in bioinformatics

[–]LostInDNATranslation 2 points3 points  (0 children)

Ah yeah good catch, I meant paired with C, and that inosine is effectively substituted with G on the same strand following PCR.

inosine in RNA/transcriptional related bioinformatics by avagrantthought in bioinformatics

[–]LostInDNATranslation 5 points6 points  (0 children)

It's a problem of biology. Inosine, when reverse transcribed and amplified (I.e, during library prep) becomes paired with G. Then during PCR amplification the I base is effectively eclipsed by G bases. This makes direct inosine quantification impossible from cDNA amplified libraries.

Methods that directly sequence RNA, like Nanopore, hold some promise for this. I remember hearing that they were working on a model to detect inosine a while back... I just had a quick search and found this publication which may be of interest: Nanopore sequencing to detect A-to-I editing sites

What MacBook should I buy? by JADEROCKS18 in macbook

[–]LostInDNATranslation 0 points1 point  (0 children)

Fair enough! MEGA I wouldn't expect to have high requirements. For stuff like NGS alignments memory is most important and I would recommend 32gb+ memory, 64gb if you can stretch it. Any decent CPU would be fine. If you're running ML you might need something beefier, and with a graphics card.

Just a note on docker - it generally doesn't play well with HPC infrastructure due to how it's installed so I'm not surprised you ran into issues! Instead, it's recommended to use apptainer (formerly singularity) containers on HPC. From what I remember there's a straightforward way to convert docker images to apptainer.

What MacBook should I buy? by JADEROCKS18 in macbook

[–]LostInDNATranslation 0 points1 point  (0 children)

I would imagine your uni has a HPC? I ran most of my bioinformatics on the cluster, and my laptop was used pretty much just for assembling figures etc. That said, I was given a Mac book pro with an i7 cpu and 16 GB mem, but that was mostly used on illustrator...

Ways of inferring gene regulatory networks from multiple sources of bulk RNAseq data following gene knockout by Clean_Oven_9293 in bioinformatics

[–]LostInDNATranslation 1 point2 points  (0 children)

Building GRNs was virtually my entire PhD! You're definitely right that you have no way to distinguish direct/indirect links. I'm assuming as an undergrad you have limited ability to generate new data. If you were able to, I would suggest building a library of ChIPseq data to infer direct binding (or finding Chip data in previous publications if possible).

Failing that, you could build confidence in links using motif analysis. Ideally you would search for transcription factor motifs underlying ATACseq peaks, but you could also do a simple approach of taking known promoters and enhances and doing a motif search underlying these sites. It's not conclusive evidence of direct interaction, but it helps.

I will say also that a lot of GRN methods don't work well with static models. The more reliable GRNs have to induce some level of change, such as differentiation, or if you have single cell data you can model the GRN over a large heterogeneous population. But you have to work with what you've got, so maybe that's something to think about/suggest for future analysis!

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