# Tag Info

9

The first column contains Ensembl gene identifiers, and the suffix is a version number that can be used to track changes to the gene annotations over time. From the Ensembl Stable IDs documentation: Ensembl annotation uses a system of stable IDs that have prefixes based on the species scientific name plus the feature type, followed by a series of digits ...

6

If you don't mind hitting it 50k times and are OK with python3... from urllib import request import json def getPathways(proteinID): baseURL = 'http://reactome.org/ContentService/data/query' PathwayIDs = set() try: response = request.urlopen('{}/{}'.format(baseURL, proteinID)).read().decode() data = json.loads(response) ...

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At Ensembl, we categorise synonyms as anything that a gene might also be known as. This includes older names for them, since those names will be in the literature, including where a gene has been split in two.

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You are looking at the supplementary data of a paper. That seems to have given you a list of features, and some information about those features. Specifically, you seem to have a list of two types of element: "peg". Based on the information there, I assume "peg" stands for "protein encoding gene". Note that all peg lines have a ...

5

The gi is an abbreviation for "Genbank identifier". This is a pretty standard convention used by data stored in NCBI databases. There used to be a pretty comprehensive description of the conventions used at NCBI (I wouldn't say it was a standard or specification, just convention) here, but this page is no longer available it seems. The AY848686 label is an ...

5

This is possibly a wild goose chase, but a lot of searching led me to this sample: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM2536852 Which appears to exhibit accessions of the right format. This in turn leads to the platform: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GPL22166 Which is a custom spotted cDNA array, which the metadata ...

4

Reposting my answer from the related ticket in the Biology section: I think there is an issue with the terminology. The "primary" accession number, is the first accession number in cases where an entry has more than one accession number, as described in http://www.uniprot.org/help/accession_numbers: Entries can have more than one accession number. This ...

3

On Reactome website they have at the download page mapping files (uniprot, ensembl, etc.), but unfortunately not for the protein IDs you are using (stable identifiers). I had contact with their helpdesk, and they sent me a file containing all protein IDs to the pathways. Exactly what you need. I have asked them if they wanted to put it on their download ...

3

Consider the circumstances in which entries will have more than one accession (taken from the same page you linked in the original post). Entries will have more than one accession number if they have been merged or split. For example, when two entries are merged into one, the accession numbers from both entries are stored in the AC line(s). If an existing ...

3

You can link them with the kgXref table, since kgXref.refseq == refGene.name and kgXref.kgID == knownCanonical.transcript. Since it seems that knownCanonical.transcript is what you want anyway, you don't even need to join on it: mysql --user=genomep --password=password --host=genome-mysql.cse.ucsc.edu \ -A -D hg38 -e 'select concat(t.name, ".", i.version) ...

3

CATH The CATH database classifies protein by fold: https://www.cathdb.info/ So the value from that is probably the most useful for you. Crystallographic conditions pH Salinity Dissolved Sugars Reducing Agent Concentration Your crystallising conditions do not mean much. They are a solution that is close to precipitating your protein but slowly enough for it ...

2

You can use Entrez Direct for this as follows: efetch -db protein -id YP_805528.1 -format gpc -mode xml | xtract -insd Protein EC_number YP_805528.1 6.3.2.13

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What tool did you use to replace the read names? Can you modify that to split up the reads into separate files or encode the cell barcode in the read description instead of the read name? Typically is it assumed by many tools that the FASTQ read names are unique. you could have issues with BWA and split alignments but I don't know if that pertains to your ...

2

There are various attempts to guess putative horizontal gene transfer using sequence composition (kmer-frequencies or GC content), you do not have to implement a new method by your own. I co-authored one of them called SigHunt. It's kind of working, but the code is really messy and there are now bit more precise methods out there. The advantage is SigHunt ...

2

The tricky bit here is that you need a list of sequence records sorted in the same order as the CG values. You can accomplish this by making tuples of the seq records and GC values, then sorting the tuples specifying the GC values as the sorting key: gc_w_records = sorted(((GC(rec.seq), rec) for rec in SeqIO.parse("ls_orchid.fasta", "fasta")), key=lambda ...

2

I'm not sure I understand the question, but XP_019970915.1 is an 'NCBI Reference Sequence' ID for 'erythrocyte binding antigen-181' (https://www.ncbi.nlm.nih.gov/protein/XP_019970915.1/). If you look that protein up in UniProt you can find other identifiers/info and GO annotations etc (https://www.uniprot.org/uniprot/A0A151LVZ9). Does that answer your ...

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The Retrieve/ID mapping tool from Uniprot allows you to convert from Uniprot to entrez ID and vice-versa. It is available here. Just select the appropriate values in the 2.Selection options panel.

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Answer from @devon-ryan, converted from comment: Both, that's why NAT5 is no longer a human gene symbol. NAT5 does not equal NAA20, it's an out-dated name for it. Names change over time as people realize that there are more genes for something than originally thought.

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The ID history converter is available as a Perl script. This script accesses these MySQL tables, so you could query these tables directly. Note that the mapping session is only one release at a time, so you would need to run 25 queries to go from release 75 to 100.

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You can put you fasta file in a single line per sequence: perl -pe 'if(/\>/){s/\n/\t/; s/>//; s/\n//}' file.fasta > file.tsv This line will create the next output: U1019.1010.2020_20384 0000-AHDJ-38347_223 GAAATACCGAGAGAGAAATACCGAGAGAGAAATACCGAGAGAGAAATACCGAGAGAGAAATACCGAGAGAGAAATACCGAGAGA U1928.1898.2020_20343 0000-AHDJ-24247_242 ...

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You can do it with bash quiet easy. First create a backup of your fasta file with cp otu.fasta otu_backup.fasta Then you can run: while IFS=" " read -r otu fastaId rest; do sed -E -i "s/>$fastaId .+/>$otu/" otu.fasta; done < ids.txt; done < OTU_ID.txt What does the code? With IFS=" " you declare a whitespace as ...

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gi looks like a Genbank Identifier. You can search for the 10 digit number following gi| at the Genbank website.

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I think that a very nice example of what you are talking about saying the word bigger, is probably a microarray transciptional analysis of RNA extracted from a biological sample. Simplifying, in these analyis, each observation is analised on, up to 10000 genes expression levels of different mRNA coding genes. Thus, from these type of molecular biology ...

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That is a GenBank gene ID and it (apparently) stands for "GenInfo Identifier". The full GenBank ID is gi|61393989. Yes, this is the standard format for sequences provided by NCBI. However, you can have all sorts of extra details appended to that. They (NCBI) generally use | as a field separator, so you could try to write code that parse that, but ...

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