Tables of estimated abundances of taxa present in metagenomic samples (including human) using Kraken (Wood & Salzberg, Genome Biology, 2013), based on k-mer identity with a reference database extracted from a large set of complete genomesThis reference database included all available RefSeq genomes as of September 19th 2017 for bacteria (94,803), archaea (676), viruses (7,497), protozoa (79), fungi (238) and plasmids (10,842). We added the GRCh38, HuRef and YanHuang human genome reference sequences (International Human Genome Sequencing Consortium, 2004; Levy et al., 2007; Wang et al., 2008)Kraken assigns reads to all taxonomic levels in a cumulative manner, and relative abundance of taxa can be computed using the ratio of read counts at one specific level over the total. Read counts were computed 1) with a conservative filter on read confidence scores, i.e. keeping only reads with more than 20% k-mers assigned to congruent taxa (using kraken-filter executable with option “--thresh 0.20”); and 2) in a sensitive mode, i.e. without confidence score filtering. Relative abundances were computed at the species and genus level. Distribution of relative abundances per sample (from sensitive mode) showed significant bias relative to sequencing depth for values under 10-12, with low-depth samples being depleted in rare species (Fig. S1), so the species relative abundance dataset was truncated to species with values above 10-12, decreasing the number of represented species from 8,226 to 5,323. We used linear discriminant analysis (LDA) effect size (LEfSe) (Segata et al., 2011) to detect taxa that significantly differentiate groups of samples based on their subsistence strategy (accounting for the underlying grouping by population). We then used a simple LDA, as implemented in the ade4 R package (Dufour & Dray, 2007), to identify the species that specifically differentiate microbiomes along the human lifestyle gradient opposing HGs to Western controls (WCs); significance was assessed with pairwise t-tests, Wilcoxon rank-sum tests (using Benjamini-Hochberg false discovery rate [FDR] correction procedure for multiple testing) and ANCOM test (with low stringency multiple testing correction, option ‘multcorr=2’).Figures : Taxa discriminating between subsistence strategies under conservative and sensitive settings, respectively.WGS-based estimates of taxonomic abundance (Kraken classification from reads with assignment confidence over 20% or unfiltered reads, respectively) were used to find (A) the best discriminant taxa based on a three-way comparison of the HG, TF and WC groups with the LEfSe algorithm (score over 3), and (B) the best discriminant species between HG and WC groups based on a simple LDA. Species are ranked (left to right and top to bottom) by decreasing absolute LDA score. Abundances significantly different under a Wilcoxon rank sum test with FDR-corrected p-values < 0.05 are indicated with an asterisk. WC: Western Controls; TF: Traditional Farmers; HG: Hunter-Gatherers.Scripts used to analyse these results can be found on GitHub: https://github.com/flass/microbiomes/tree/master/scripts/krakenThis work was published in the journal Molecular Ecology doi: 10.1111/mec.1443

Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of OMG-ETH pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

kraken database for MetaMeta pipeline version 1. The database was generated by the kraken-build script and it is based on the NCBI RefSeq Complete Genome sequences of Archaea and Bacteria dating from 2015-06-02

Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of ETH-USD pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

Comprehensive financial and analytical metrics for Kraken, including key performance indicators, market data, and ecosystem analytics.

Kraken/Braken databases for UHGG genomes.

HUMAN_3006.tar.gz: Kraken/Bracken database for 3006 high quality species clusters of the UHGG (Beresford-Jones et al., 2022). Database was built from the single highest quality genome for each species cluster (n=3006). Uses the original GTDB v1.3 taxonomy.

UHGG_5987_KRAKEN.tar.gz: Kraken/Bracken database for 3006 high quality species clusters of the UHGG (Beresford-Jones et al., 2022). Species clusters are represented by a variable number of high quality genomes (n=5987 in total), selected to maximise represented taxonomic diversity. Uses a custom taxonomy modified from GTDB v2.1 with each species cluster being represented by a species level taxonomic annotation.

Methods:

Databases built using Kraken v2.1.2 and Bracken v2.6.2. Commands used to build the databases are included below.

kraken2-build --build --db Kraken --threads 12

bracken-build -d Kraken -k 35 -l 150 -t 12

OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information within each time frame (such as one minute, five minute, hourly, daily, etc.):

Open: the first traded price High: the highest traded price Low: the lowest traded price Close: the final traded price Volume: the total volume traded by all trades Trades: the number of individual trades

Each ZIP file contains the relevant CSV files for 1, 5, 15, 30, 60, 240, 720 and 1440 minute intervals, which can be viewed in a text editor, used in code, converted into other formats (such as JSON, XML, etc.) or imported into a graphical charting application.

Note that the OHLCVT data only includes entries for intervals when trades happened, so any missing candlesticks indicate that no trades occurred during those intervals. Charting software often provides an option to display/hide empty intervals, which could be used to replace the missing candlesticks if needed.

Taxonomic binning of the gold standard pooled assembly
Software: Kraken
SoftwareVersion: 2.0.8 beta
DataURL: https://data.cami-challenge.org/participate
SoftwareURL: https://ccb.jhu.edu/software/kraken2/
ReferenceDatabase: built 2019-05-22
Taxonomy: NCBI 2019-05-22
ShortReadsUsed: False
LongReadsUsed: False
CommandUsed: kraken2-build --standard --db kraken2db_std --use-ftp
kraken2 --db kraken2db_std --threads 16 --output 19122017_mousegut_scaffolds.kraken --report 19122017_mousegut_scaffolds.kreport anonymous_gsa_pooled.fasta
cat 19122017_mousegut_scaffolds | awk '{print $2 "\t" $3}' > 19122017_mousegut_scaffolds.cami

Kraken reports for each tick sample as well as combined table

hbxartdev/kraken dataset hosted on Hugging Face and contributed by the HF Datasets community

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Having issues with your Kraken wallet? Whether you’re locked out, facing delays, or concerned about security, getting the right support matters. One number circulating online is +1-888-416-9087—but it’s important to note this isn’t officially listed on Kraken.com.

When to Contact Kraken Support:

2FA login issues

Funds missing or delayed

ID verification problems

Suspicious activity on your account

Official Kraken Support Methods:

Live Chat: Available at support.kraken.com

Email: support@kraken.com

In-App: Use Help Center inside the Kraken app

Social Media: Tweet @krakenfx

Phone (Unverified): +1-888-416-9087 (use caution)

Calling the Unofficial Number – What to Do:

Double-check number via Kraken’s Help Center

Be cautious when dialing

Provide only necessary info (never passwords or seed phrases)

Ask for a support ticket or case number

Follow up via Kraken’s official email

Stay Safe: Kraken urges users to rely on in-app or web support channels. If you try the phone route, protect your account info and always confirm legitimacy.

Intro If your Kraken Wallet hits a snag, there’s no need to panic. Whether you’re locked out or dealing with device glitches, the dedicated support line at +1-888-416-9087 can help you sort it out fast. Kraken Wallet Highlights This hardware wallet offers: • Cold storage for private keys • Multi-currency support • Secure PIN and passphrase features • Simple firmware upgrades Why People Kraken It Being offline means it’s highly resistant to hacks, making Kraken perfect for anyone who values security. When Things Go Wrong You might run into: • Computer connection failures • Problems updating firmware • Forgotten PINs or phrases • Damaged or lost devices Why Kraken Support is Essential The support team: • Guides you through urgent issues • Keeps your crypto safe • Helps you get back up and running Before Calling Try the Help Center, or email: support@Krakenwallet.com. Social channels may also provide quick tips. Dialing +1-888-416-9087 This number connects you with professionals trained to: • Handle wallet malfunctions • Assist with security concerns • Help with urgent recoveries Call Flow – What to Expect • Share basic device/OS info • Follow troubleshooting steps • Never reveal your recovery seed Before You Call 1. Note your model and serial number 2. Call during U.S. business hours 3. Follow prompts carefully 4. Stay calm and take notes Call Tips • Stay polite • Speak clearly • Don’t disclose your seed phrase Support Alternatives • Chatbot on the website • Email for complex cases • User communities for shared experiences Avoiding Scams • Stick to: https://Krakenwallet.com • Ignore unsolicited contact • Never share your recovery phrase What Support Will Ask For • Device details • Operating system info • Description of the issue After the Call • Check email for case ID • Complete follow-up steps • Monitor wallet activity Security Standards Support calls are encrypted, and Kraken never stores or asks for seed data. Final Note When problems arise, Kraken support is your go-to. Dial +1-888-416-9087 and get back on track securely.

Kraken users facing issues like account lockouts or verification delays may seek help through a variety of channels. You might encounter the number +1-888-416-9087 online—but this isn’t listed on Kraken’s official site.

Reasons People Contact Kraken:

Locked accounts due to 2FA issues

Trouble verifying identity

Stuck transactions

Suspected hacks or phishing

Lost access to wallet

Kraken’s Trusted Support Options:

Live chat via Kraken’s website

Email: support@kraken.com

In-app help tools

Twitter/X: @krakenfx

Unofficial number: +1-888-416-9087 (with caution)

If You Call +1-888-416-9087:

Confirm if the number is still in use

Ask to speak to a representative

Provide only minimal verification details

Write down any support ticket or case ID

Follow up with official channels

Never share your recovery keys or passwords

Warning: Phone support is not Kraken’s standard method. Stick to official tools for a safer experience.

Stuck with a Kraken wallet issue? Support is available—but be cautious about numbers like +1-888-416-9087, which is not found on Kraken’s official website.

Top Reasons to Reach Out:

Can’t log in due to 2FA failure

Delayed withdrawals or deposits

KYC verification problems

Possible unauthorized activity

Trouble recovering your account

How to Reach Kraken Securely:

Live Chat: Via their site (24/7 help)

App Support: Log in and use the Help feature

Email: support@kraken.com

Social Media: Use @krakenfx for updates

Phone: +1-888-416-9087 (proceed carefully—it’s unverified)

Tips for Calling an Unverified Number:

Confirm on Kraken’s site before dialing

Don’t give sensitive info

Ask for case ID and next steps

Follow up with an official email

Watch for strange activity on your account afterward

Always trust Kraken’s official channels first. Phone support can be tricky, so stay alert and secure.

Wood et al simulated dataset used to evaluate the accuracy of Kraken v1 (and other classifiers) in the original Kraken publication; contains three FASTA files and instructions for obtaining the source taxonomic IDs for each sequence. These simulated metagenomic samples (each 10,000 reads) were also used to evaluate the speed of the non-Kraken classifiers.

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Context

Real and up to date stock market exchange of cryptocurrencies can be quite expensive and are hard to get. However, historical financial data are the starting point to develop algorithm(s) to analyze market trend and why not beat the market by predicting market movement.

Content

Data provided in this dataset are historical data from the beginning of NANO-USD pair market on Kraken exchange up to the present (2021 December). This data comes frome real trades on one of the most popular cryptocurrencies exchange.

Trading history

Historical market data, also known as trading history, time and sales or tick data, provides a detailed record of every trade that happens on Kraken exchange, and includes the following information: - Timestamp - The exact date and time of each trade. - Price - The price at which each trade occurred. - Volume - The amount of volume that was traded.

OHLCVT

In addition, OHLCVT data are provided for the most common period interval: 1 min, 5 min, 15 min, 1 hour, 12 hours and 1 day. OHLCVT stands for Open, High, Low, Close, Volume and Trades and represents the following trading information for each time period: - Open - The first traded price - High - The highest traded price - Low - The lowest traded price - Close - The final traded price - Volume - The total volume traded by all trades - Trades - The number of individual trades

Don't hesitate to tell me if you need other period interval 😉 ...

Update

This dataset will be updated every quarter to add new and up to date market trend. Let me know if you need an update more frequently.

Inspiration

Can you beat the market? Let see what you can do with these data!

A kraken2 database built from the genome assemblies used by the Human Pangenome Reference Consortium (https://projects.ensembl.org/hprc/). This archive contains the three files required by kraken2, hash.k2d, opts.k2d, and taxo.k2d, along with inspect.txt, which is obtained by running kraken2-inspect on the database, ktaxonomy.tsv, which contains the taxonomy information of the database (obtained by running https://github.com/jenniferlu717/KrakenTools#make_ktaxonomypy).

The genomes for this database were downloaded using the assembly summary text file included in this dataset and genome_updater.sh (v0.6.3; https://github.com/pirovc/genome_updater)

genome_updater.sh -m -a -f "genomic.fna.gz" -t 8 -e "hprc_assembly_summary.txt" -o HPRC_genomes/

The python script prepare_kraken_fasta.py was then used to prepare the assemblies for use in kraken with the following command

python prepare_kraken_fasta.py -r -T 9606 -o HPRC.fna HPRC_genomes/

The database was then built with kraken2 using the following commands

kraken2-build --download-taxonomy --db db/
kraken2-build --add-to-library HPRC.fna --db db/
kraken2-build --build --db db/ --threads 16

This statistic shows the advertising spending of the rum brand Kraken in the United States from 2013 to 2015. The brand invested approximately **** million U.S. dollars in advertising in 2013.