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/r/bioinformatics

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1

Advice/suggestions on data collection for a publication.

Hi all,

I have differentially expressed genes from two biological replicates. The project was on aging and hence done a few basic experiments to further strengthen my hypothesis. I know that I can not publish the data from only 2 biological replicates and I can not do any more experiments since I'm out of the lab.

Bioinformatically, is there any way I can add in more data/data analysis (like meta-analysis from datasets from Gene Expression Omnibus etc) along with the data from 2 biological replicates to publish?

If yes, what are the tools and/or software that can be used for this approach?

(Cell biologist here and pretty new to the bioinformatics field)

Thank you.

0 Comments
2024/05/20
14:41 UTC

1

what to do with unknown sequences in dna alignment?

Good day! I’m currently working on a project for my Systematics class. We were given DNA sequences, which we aligned through Clustal and concatenated to create a tree using Maximum Parsimony and Bayesian Inference. However, in the trnTF, we discovered a long chain of “N” in one of the taxa, causing an increase in the number of characters. What should be the correct decision, delete the unknown sequences or retain them? What would be the consequences say we delete the said unknown sequences?

0 Comments
2024/05/20
14:39 UTC

3

CreateSeuratObject taking very long

I have my data with 33694 obs of 63690 variables, and it has been an hour since I ran the below command and it still isn't complete

seu_obj<-CreateSeuratObject(count=raw_data)

Is there any way to speed this up?

2 Comments
2024/05/20
13:43 UTC

4

Better to be specialize in one specific language or know a bit of multiple?

Hey all, I

I am just curious about the opinions of some people more senior to the bioinformatics field. I've only been in the work force for a year (academic lab as a tech), but through undergrad, my masters, and now this past year, I've gotten pretty good in R. I still learn new tricks everyday, but I feel very familiar with the syntax and it's like second nature. In grad school, I took a python course for genomics that taught the basics. However, since nothing I do on a day-to-day basic really requires python, and/or could be done in R, I don't really use it at all. As with anything...if you don't use it, you lose it...

Would you say it is better to be really proficient in one language or be half way decent at 2 or 3? In this case, R and Python, and maybe some third? (maybe something like nextflow?)

If you're only interested in doing analysis and not necessarily building tools or algorithms, is it even worth learning higher level languages like C++ or Rust?

4 Comments
2024/05/20
13:33 UTC

2

Assistant research exp vs ms program

Im currently a cs student with a bio minor. I’m 29 and returned to school to 1. Switch careers 2. Not be locked out of progressing because of my lack of education.

I plan on getting a PhD but my undergrad program is no name, online, and has no research opportunities. I know I need something else before doing a PhD. My question is would spending a few years working as a research assistant in the genomics field be equal/better/worse than getting an ms?

I live in nyc and see a decent amount of openings for roles requiring only a bs.

1 Comment
2024/05/20
12:23 UTC

0

Any bioinformatics career guider please look at my queries.

I am a bsc 3rd year student. Currently confused about my career. When I stop thinking about government jobs. I think about career in reasearch.i will be giving exams like iitjam tifr gs....etc but i couldn't found any better career options. Then i found bioinformatics. Internet says it's in demand . Should I pursue my career in this field. Should I be doing a diploma or MSc . I am literally highly confused.

8 Comments
2024/05/20
10:37 UTC

3

“Plant Genome Annotation: Are My BlastX Parameters Correct?”

Currently, I am performing the gene annotation of a plant genome. The transcriptome data of this species is available but the RNA was isolated from a different tissue (whose ploidy is supposedly different); also transcriptome data of closely related genera are available.

While performing BlastX I queried 10 sequences at a time, kept the "nr" protein database, and specified the TaxonomyID of ~6 related genera and that of the family my species belongs to. The e-value was set to 10^-05 and set to 10 top hits. Now, for 100 batches (each containing 10 sequences) of Blastx, I got hits only for 15. Now, I've just slowed down and started thinking if the parameters have been set correctly. I plan to download the hits in XML format and feed them into Blast2Go for annotation. I am a bit confused if I am getting it right, or if I do have to make changes in the settings. Can someone share some input?

4 Comments
2024/05/20
08:27 UTC

13

Cool upcoming talk about protein engineering (May 29)

It streams on YouTube Live on May 29, at 9am JST: https://www.youtube.com/watch?v=SQiQBD8a0U0

The speaker is Sam Gelman, who is a recent PhD grad.

"Just as words combine to form sentences that convey meaning in human languages, the specific arrangement of amino acids in proteins can be viewed as an information-rich language describing molecular structure and behavior.

Protein language models harness advances in natural language processing to decode intricate patterns and relationships within protein sequences. These models learn meaningful, low-dimensional representations that capture the semantic organization of protein space and have broad utility in protein engineering. However, while protein language models are powerful, they do not take advantage of the extensive knowledge of protein biophysics and molecular mechanisms acquired over the last century. Thus, they are largely unaware of the underlying physical principles governing protein function.

We introduce Mutational Effect Transfer Learning (METL), a specialized protein language model that bridges the gap between traditional biophysics-based and machine learning approaches by incorporating synthetic data from molecular simulations. We pretrain a transformer on millions of molecular simulations to capture the relationship between protein sequence, structure, energetics, and stability. We then finetune the neural network to harness these fundamental biophysical signals and apply them when predicting protein functional scores from experimental assays. METL excels in protein engineering tasks like generalizing from small training sets and extrapolating to new sequence positions. We demonstrate METL's ability to design functional green fluorescent protein variants when trained on only 64 experimental examples."

0 Comments
2024/05/20
07:17 UTC

10

Is this code plagiarism - going towards publication?

I am working on a pipeline that my lab wants to publish, and from which the original creators of the pipeline have moved on.

Unfortunately it had no documentation which is now what much of my work entails.

I have discovered that much of the code has been copied and pasted from open source code, and code from similar projects at other labs. There is no differentiation between the external code and code implemented by my lab. Much of the copy & pasted code even has no reference to its external source either.

As a recent CS grad, I was taught that this would be considered plagiarism...am I wrong?

EDIT

Thanks for the info on the licensing! HOWEVER, my question is not about whether or not it was OK to use the code (with this I think we are all good), it is about how it is not cited in the codebase or any documentation. As I understand, credit should be given for original works where used, no?

3 Comments
2024/05/19
21:19 UTC

39

Best way to bridge the gap between CS and bioinformatics?

I currently work as a machine learning engineer, and have a BS in computer science and math from UCSC, and an MS in statistics from Texas A&M university. My goal is to move more into biotech, and to work on things that I feel are actually helping people.

I currently live in Santa Cruz, and have considered reaching out to some professors in the labs up at UCSC to volunteer my time to get in on some of the fun research they’re doing there. I’m not sure yet if my end goal is a PhD, but I definitely miss research from my time during my MS.

Given that I have very little bio knowledge, is there a good way to bridge the gap between my CS/statistics knowledge and what I should have under my belt delving into bioinformatics?

40 Comments
2024/05/19
18:02 UTC

5

Metagenomics database

I am trying to get a a very large variety of DNA-based genomes. Is there a assembled metagenomics database where I can do this.

My goal is to generate a large, highly diverse protein library from DNA viruses, eukaryotes and prokaryotes of many different origins. I thought metagenome samples would be highly useful for this task.

I dont want reveal, but there is a reason i cannot use uniprot.

4 Comments
2024/05/19
17:29 UTC

1

Mailing list/diffusion network for postdoc in statistical genetics?

Hey all,

I'm trying to recruit a postdoc for a project of developing a new statistical method in the field of evolutionary genetics. We're having difficulty attracting profiles with strong skills in statistics and method development on the "evolutionary genetics" side of our networks, and I know a few networks for bioinformatics, but not all.

Do you guys know about some kind of international mailing list/diffusion network where academic people skilled in statistics and genetics would go to look out for postdocs?

Thanks for your suggestions!

11 Comments
2024/05/19
08:37 UTC

1

In AutoDock Vina, what values of --center_x/y/z represent the center of the grid box?

I would like to run protein-ligand blind docking simulations with the PSMA protein as the receptor. As far as I can tell, just doing measurements in PyMol, the protein is less than 100 Å across in all dimensions, so I think I could use a 100x100x100 grid box to cover all possible docking sites, as in:

./vina --receptor=PSMA.pdbqt --ligand=foo.pdbqt --size_x=100 --size_y=100 --size_z=100 ...

and I intend to run commands like this with a range of --center_x/y/z coordinates, scanning the grid box.

But I can't seem to find an explanation of the coordinate system. Is the center of a 100x100x100 box at (0, 0, 0), so that a scan should run from (-50, -50, -50) to (+50, +50, +50) or is the center at (50, 50, 50) so that a scan should run from (0, 0, 0) to (100, 100, 100), or something else?

Or maybe I am completely confused about what these parameters control. Thanks in advance!

4 Comments
2024/05/19
06:32 UTC

1

Discrepancy between the variant database and reference sequence

I'm encountering an annoying issue while working on my graduation project and could use some insights.

I'm using a variant database to annotate genetic variants in the MEFV gene. The database reports a variant at position c.1730C>G using the transcript reference sequence NM_000243.2. According to the database, the reference nucleotide at this position should be "C".

However, when I check the same position using the NCBI database, UCSC Genome Browser, and Entrez API (all using NM_000243.2), the reference nucleotide is "T", not "C".

Has anyone encountered similar issues? Is it possible that there is an error in the variant database (LOVD), or am I missing something in terms of coordinate systems or annotations? Note that I experience the same issue on other databases and for other genes as well - so it is not an isolated case. Any guidance on how to resolve this discrepancy would be greatly appreciated.

Thanks in advance for your help!

7 Comments
2024/05/18
21:50 UTC

16

Difference between KEGG vs GO

Hi all. I am working on my first RNAseq analysis. I have completed GSEA for both GO and KEGG terms but I am not really sure what the difference between them are and if I should focus on one more than the other. When I try to search on google the results aren’t the most helpful and usually are something along the lines of “GO annotates and classifies gene sets through BP, CC, and MF while KEGG looks at pathways related to DEGs”. Maybe I am just too new to this, but that does not really tell me much.

Any help is appreciated!

8 Comments
2024/05/18
19:48 UTC

4

Resources to learn metabolomics

Hey everyone,

I am a 4th-semester pursuing my bachelor of engineering in biotechnology student who will be completing my semester soon and will be beginning my summer break. I have two months and I plan on doing internships, mostly in bioinformatics. I have received an offer to do a research internship in systems biology at my own university, but along with that I want to do another. I have contacted a bioinfo company I have known personally for quite some time, and they said they could offer me a position, with a stipend provided that I am well-versed in molecular dynamics and metabolomics but I may have to pay a training fee if I am not familiar with concepts so that they can train me. It's not very affordable, so I plan on starting in July instead of June so that I can focus on my university internship and upskill myself in programming and metabolomics.

I am currently completing a certification on molecular dynamics from Udemy. I plan on doing another from Coursera on computational genomics. I have found some resources on YouTube on metabolomics, but it doesn't have a lot of practical hands-on analysis modules. Could anyone recommend some free resources where I can learn things to use things like MetaboAnalyst, XCMS, MetFrag, LipidMaps, etc?

Also, can someone guide me on the skills and tools one would need for metabolomic analysis?

Cheers

6 Comments
2024/05/18
15:45 UTC

2

[Molecular Docking] Active Site Inside a Protein?

I'm doing a virtual screening of potential active compounds from banana that can bind to 14-alpha Sterol Demethylase. Based on previous studies, the active site of the receptor seems to be inside the protein rather than on the surface (I've also checked this using COACH server). I haven't done any docking simulations where the active site is inside the receptor. Is it even possible? All of my docking experience involved active sites on the surface of proteins so I'm unaware. I'm planning to use Autodock vina but if anyone has other suggestions, that would certainly help.

0 Comments
2024/05/18
15:09 UTC

2

How do I find the sequence identity in clustal omega or clustalw?

Sorry for the silly questuon, I’m still a beginner

I have input 10 sequences into clustal omega and clustalw

In clustalw I have found how similar different pairs of sequences are but I struggle to find how much do my 10 sequences match as a whole

Any help is much appreciated

0 Comments
2024/05/18
14:09 UTC

3

Data frame and matrix formation on R

Hi all,

I’m honestly about to pull my hair out. I’ve uploaded an excel sheet of metadata. Rows as ‘ID1, ID2’ and so on. I have various columns - ie ‘MLST, CC’ etc. I’ve plotted my treefile and have labeled tips.

When I write df<-as.data.frame(matrix(ncol=2,nrow=length(tree$tip.label),data=0)) Rownames(df)<-tree$tip.label

I get the error: error in rownames(df) <-tree$tip.label : could not find function “rownames<-“

What am I doing wrong?! I’m going crazy!

15 Comments
2024/05/18
11:44 UTC

1

Realignment tools

Hello,

I am new to bioinformatics. I am working with some samples i found online and do what they did in the paper but again since i am not a pro i will do it using standard tools instead. So, I am working with WGS illumina reads- 131bp of MRSA and i have to look for other ST of MRSA that resulted in the outbreak so my ref genome is also an MRSA ST which is not responsible for outbreak (as stated in that paper). Keeping that in mind, I have designed a workflow trimmomatic-> bowtie2 -> realignment ( i need a tool that works well for bacterial genome realignment, also which works on 4GB RAM) -> BCFTOOLS (for variant calling with realigned reads) -> phylogenetic tree analysis.

I need a tool for realignment. I am still trying to understand variant calling part.

I have read about ScanIndel, Pilon and BLAT and it's not something that a lot of people have used previously.

Edit: The paper i am following uses Pindel but it's computationally expensive. I am looking for soft clipping realignment tool since bowtie2 works that way on local mode

2 Comments
2024/05/18
08:37 UTC

5

Multiple Warnings trying to filter .vcf from Simons Genome Diversity Project

Hi, I am throwing myself at this problem for an online course and even the given video example doesn't work when I try it with .vcf files I've downloaded from the Simons project.

I'm trying to use vcftools to filter DP and GQ but it always returns the same number of sites no matter what threshold I set.

Here is an example of one I have tried:

$ vcftools --gzvcf LP6005441-DNA_B04.annotated.nh2.variants.vcf.gz --out chr22 --recode --chr 22 --minGQ 98

VCFtools - 0.1.16
(C) Adam Auton and Anthony Marcketta 2009

Parameters as interpreted:
        --gzvcf LP6005441-DNA_B04.annotated.nh2.variants.vcf.gz
        --chr 22
        --minGQ 98
        --out chr22
        --recode

Using zlib version: 1.2.11
Warning: Expected at least 2 parts in FORMAT entry: ID=PL,Number=G,Type=Integer,Description="Normalized, Phred-scaled likelihoods for genotypes as defined in the VCF specification">
Warning: Expected at least 2 parts in FORMAT entry: ID=FL,Number=1,Type=Character,Description="filter level in range 0-9 or no value (non-integer: N,?) with zero being least reliable; to threshold at FL=n, use all levels n-9">
Warning: Expected at least 2 parts in INFO entry: ID=AC,Number=A,Type=Integer,Description="Allele count in genotypes, for each ALT allele, in the same order as listed">
Warning: Expected at least 2 parts in INFO entry: ID=AC,Number=A,Type=Integer,Description="Allele count in genotypes, for each ALT allele, in the same order as listed">
Warning: Expected at least 2 parts in INFO entry: ID=AF,Number=A,Type=Float,Description="Allele Frequency, for each ALT allele, in the same order as listed">
Warning: Expected at least 2 parts in INFO entry: ID=AF,Number=A,Type=Float,Description="Allele Frequency, for each ALT allele, in the same order as listed">
Warning: Expected at least 2 parts in INFO entry: ID=MLEAC,Number=A,Type=Integer,Description="Maximum likelihood expectation (MLE) for the allele counts (not necessarily the same as the AC), for each ALT allele, in the same order as listed">
Warning: Expected at least 2 parts in INFO entry: ID=MLEAC,Number=A,Type=Integer,Description="Maximum likelihood expectation (MLE) for the allele counts (not necessarily the same as the AC), for each ALT allele, in the same order as listed">
Warning: Expected at least 2 parts in INFO entry: ID=MLEAF,Number=A,Type=Float,Description="Maximum likelihood expectation (MLE) for the allele frequency (not necessarily the same as the AF), for each ALT allele, in the same order as listed">
Warning: Expected at least 2 parts in INFO entry: ID=MLEAF,Number=A,Type=Float,Description="Maximum likelihood expectation (MLE) for the allele frequency (not necessarily the same as the AF), for each ALT allele, in the same order as listed">
Warning: Expected at least 2 parts in INFO entry: ID=RPA,Number=.,Type=Integer,Description="Number of times tandem repeat unit is repeated, for each allele (including reference)">
After filtering, kept 1 out of 1 Individuals
Outputting VCF file...
After filtering, kept 51247 out of a possible 3917661 Sites
Run Time = 10.00 seconds

No matter what threshold I set for any filter I've tried, I always get the warnings and no filtering.

I've tried searching BioInfo forums but i keep running into dead ends about the warnings --and I don't even know if they are preventing the filtering. Can anyone offer a hint as to what I'm doing wrong please?

6 Comments
2024/05/18
06:06 UTC

2

Question regarding Bioinformatics software HumanN on an HPC

Hello, has anyone here used HumanN on an HPC system before? Do you know If its 'multi-node' enabled, i.e can It use MPI for executing work on multiple cores across multiple nodes?

Similarly, is it even multi-core enabled? Can it submit work to multiple cores?

Thank you in advance

3 Comments
2024/05/18
03:27 UTC

2

My BLASTn results were not what I was expecting

I'm trying to identify miRNAs from a WGS dataset as part of a pipeline I want to build.

I downloaded one bam file (>63GB) of a WGS tongue cancer dataset (already aligned) on my local computer (M1 pro, 16GB RAM, 1TB Storage) because my stupid dept has zero facilities for the research they want us to do. Anyway, converted the bam file to fasta. This is what a few lines of the fasta looks like;

>E00582:249:HY2WVCCXY:7:1101:10003:10029/1
GAGGGGACACTTTAGGATGCTACAAAATAAAATACAACAACAACAACGATAACAGCAGCAGCAACAACAACAACAGCAACAAAAGGGGAAGAAACAAATCTGGCCACTGCACATTCCTCCTTGCCAACAAAAAGCCGTGGATGCAAAAAG
>E00582:249:HY2WVCCXY:7:1101:10003:10029/2
GTGATCCGCCCACCTCGGGCTCCCAAAGTGCTGGGATTCCAGGAGTGAGCCACCGCGCCCGGCCGTCCACTTTGCTTCTTGCAGAGGCTGATGGTTTGAGTAATTTCCGAGATTCATAGCTCGAGCGCGCCCTGTTCTGTCTATGCAGTG
>E00582:249:HY2WVCCXY:7:1101:10003:10134/1
CTCCCTACCACTTAAGTGCCAGTTCTCCCACGAGGTCCTGTTCCTGACCCTGAGACCAGAAACAAACTTGGAAGGCCCAAGGATGGTGGGAAGGGGAGGGGAACGTGATGACGCAGCTCAGTGTTTGCACTTGAAGCTGAGGACACCAAA
>E00582:249:HY2WVCCXY:7:1101:10003:10134/2
AAAGGATGGGGAGAGAGTGGGCACAGAAACACTGGGGTCTGCACTCTGGAAAGCTGAATTGAAGGGCTCTCAGGAAGCTACCAAGAGGCTGTTTGCATGGAAGGTTATTTTTGGAGATAGCCTGCCTGGTTTGGTGTCCTCAGCTTCAAG

I also ran a blastn via command line (took 4+hrs) using the WGS dataset as query and a curated custom database with about >3,500 miRNA sequences to detect sequences similar to the known miRNAs.

Now the problem is, the output .txt file from the BLAST is ~53GB. My computer can't open it with TextEdit (keeps saying "System has run out of application memory") anytime I try and the only thing I haven't quit yet is my Chrome (taking 940MB) and my terminal.

I tried reading a few lines with head and this is a sample of a few lines of what I can see

Query= E00582:249:HY2WVCCXY:7:1101:10003:10029/1
Length=150
***** No hits found *****
Lambda      K        H
    1.33    0.621     1.12 
Gapped
Lambda      K        H
    1.28    0.460    0.850 
Effective search space used: 4990410

Query= E00582:249:HY2WVCCXY:7:1101:10003:10029/2
Length=150
***** No hits found *****
Lambda      K        H
    1.33    0.621     1.12 
Gapped
Lambda      K        H
    1.28    0.460    0.850 
Effective search space used: 4990410

This is my first time doing blast but from the stuff I saw online and what my colleagues who've done it before said, the output from a blast is usually in columns (sequence, score (bits), e-value). So this is definitely not what I was expecting. But also I can't even open the txt file and see the entire thing. Now (correct me if I'm wrong), I'm assuming that if there are queries that read (*****no hits found*****), there *may be sections that read ****hits found****. Is that a possibility? If so, how do I either go about seeing if there are actual hits found or possibly opening the txt file. Or at the very possible worst, is there an alternative way to achieve what I'm trying to do?

I'd appreciate the help.

22 Comments
2024/05/17
19:45 UTC

6

RNAseq mixed effect modeling

I need to incorporate a random effect into my model for microarray differential expression. I usually use dream from variance partition, but to my knowledge that is for bulk. Limma -voom also has a block flag I could use, again for bulk.

I could use lme4..

Are there any other alternatives to incorporate random effects for microarray? Not sure if the assumptions of RMA normalized microarray would satisfy the assumptions of these bulk based models.

4 Comments
2024/05/17
18:54 UTC

7

Resources for learning perl in bioinformatics?

We spent a few months using biopython for a protein related project, but our professor changed and now we have to program on perl(which I'm kind of unfamiliar with). While I found some of the basics, I was wondering if someone has any recommendations of videos and educational material of perl in bioinformatics specifically?

18 Comments
2024/05/17
16:18 UTC

7

Phylogenetic tree visualization in Python?

Hey everyone,

just joint Reddit since I noticed I can ask here research related stuff!! I'm working on my Master's thesis which is a phylogenetic study. So far, I visualized phylogenetic trees with FigTree, exported the visualization as image file and then edited the picture by hand with Gimp which is a real pain im the ass, especially when you change something in your tree and have to rearrange everything.

I'm looking for a tool where I can create beautiful visualizations of my tree, where I can highlight certain clades, branches and evtl. annotate whole clades.

I know there is a tool like that in R (ggtree), but personally I just HATE R and would love to avoid it lol I even made all my statistics in Python. Is there a comparable tool im Python? I found ETE Toolkit but from the docs it looks so ugly and outdated, I want beautiful and fancy graphics!

In the end of the day, when there is no alternative of course I'll just use ggtree, but maybe anyone has a good alternative - preferably something in Python but I'm open to anything else. Oh, and I want my graphics to be vector graphics of course.

Thankssssss!

21 Comments
2024/05/17
14:03 UTC

3

Any resources that I can read/watch to find out if bioinformatics is for me?

Hi, I want to see if bioinformatics would be a good career option for me. Without thinking much about it I typed "bioinformatics cancer" in google scholar, found an article on anti-cancer drug development and for the love of God I cannot understand a single paragraph of this. I have no idea what the fuck they're talking about.

I'd like to read something that I can understand but also would be a good insight into what you can do as a bioinformatician as I understand that it is a very diverse field.

4 Comments
2024/05/17
10:13 UTC

0

Do plants or bacteria have p53 homologue

his is a practice question in my entrance to bioinformatics course, I’m struggling to find a consistent results in between databases, can anyone please help me find an answer to this question?

7 Comments
2024/05/17
08:04 UTC

30

A custom GPT for DNA cloning

Recently, I have created a custom GPT called “DNA Cloning GPT” to assist with the DNA cloning process in silico. If you provide the DNA materials you want to assemble as GenBank format files and a narrative of the cloning process, this GPT will simulate the process according to your instructions and generate the corresponding GenBank output and sequence map. The GenBank input used in the attached example is available here.

This GPT is a pilot version, so its capabilities as an AI agent for molecular cloning are not enough. However, I would be grad if you are interested in trying it out. If you wan to know the back-end tool used in this GPT, please see here.

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1 Comment
2024/05/17
05:19 UTC

2

Looking for advice on a TF annotation tool

So my data goes like this. I have TF X and its location is Chr16: 1019600, 1019608. I found a tool called 'atlas enhancer' but their cell data base is so limited. My data is for differentiated neuron and glia cells. Does anyone know of any other tool where I can annotate TFs based on genomic locations for especially glia/neurons? Any help is appreciated. Thanks in advance.

1 Comment
2024/05/16
22:39 UTC

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