Nyaa Torrents (named for the Japanese onomatopoeia for a cat's meow) is a BitTorrent website focused on East Asian (Japanese, Chinese, and Korean) media. It is one of the largest public anime-dedicated torrent indexes.[1][2]
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On 1 May 2017, their .se, .eu, and .org domain names were deactivated, with the site's moderators later confirming that the owner took it down voluntarily.[5][6][7] In the following weeks, several forks, partially based on Nyaa code and database of torrents, were started, each using "nyaa" in its name.[8]
In 2020 the site was blocked in India, along with other pirate streaming and torrent websites, after a decision by the Delhi High Court in favour of the plaintiff, Disney India. The court order provided for "dynamic" blocking meaning that Disney could ask for further bans on websites violating copyrights other than the ones in the order.[12]
In the context of the GC-rich genome of B. pertussis, most platforms gave similar uniformity of sequence coverage, with the Ion Torrent data giving slightly more uneven coverage. In the S. aureus genome the PGM performed better. The PGM gave very biased coverage when sequencing the extremely AT-rich P. falciparum genome (Figure 1). This affect was also evident when we plotted coverage depth against GC content (Additional file 2: Figure S4). Whilst the PacBio platform gave a sequence dataset with quite even coverage on GC and extremely AT-rich contexts, it did demonstrate slight but noticeable unevenness of coverage and bias towards GC-rich sequences with the S. aureus genome. With the GC-neutral S. Pullorum genome all platforms gave equal coverage with unbiased GC representation (data not shown).
In a recent study to investigate the optimal enzyme for next generation library preparation [5], we found that the enzyme used for fragment amplification during next generation library preparation can have a significant influence on bias. We found the enzyme Kapa HiFi amplifies fragments with the least bias, giving even coverage, close to that obtained without amplification. Since the PGM has two amplification steps, one during library preparation and the other emulsion PCR (emPCR) for template amplification, we reasoned that this might be the cause of the observed bias. Substituting the supplied Platinum Taq enzyme with Kapa HiFi for the nick translation and amplification step during library preparation profoundly reduced the observed bias (Figure 3). We were unable to further improve this by use of Kapa HiFi for the emPCR (results not shown).
The effect of substituting Platinum HiFi PCR supermix with Kapa HiFi in the PGM library prep amplification step. A) The percentage of the P. falciparum genome covered at different read depths. The blue line shows the data obtained with the recommended Platinum enzyme and the green line with Kapa HiFi. The red line depicts ideal coverage behavior. B) The number of bases covered at different depths. C) Sequence representation vs. GC-content plots.
Illustration of platform-specific errors. The panels show Artemis BAM views with reads (horizontal bars) mapping to defined regions of chromosome 11 of P. falciparum from PacBio (P; top), Ion Torrent (I; middle) and MiSeq (M; bottom). Red vertical dashes are 1 base differences to the reference and white points are indels. A) Illustration of errors in Illumina data after a long homopolymer tract. Ion torrent data has a drop of coverage and multiple indels are visible in PacBio data. B) Example of errors associated with short homopolymer tracts. Multiple insertions are visible in the PacBio Data, deletions are observed in the PGM data and the MiSeq sequences read generally correct through the homopolymer tract. C) Example of strand specific deletions (red circles) observed in Ion Torrent data.
Also evident in the MiSeq data, were strand errors due to the GGC motif [11]. Following the finding that the motif GGC generates strand-specific errors, we analyzed this phenomenon in the MiSeq data for P. falciparum (Additional file 4: Table S5). We observed that the error is mostly generated by GC-rich motifs, principally GGCGGG. We found no evidence for an error if the triplet after the GGC is AT-rich. Other MiSeq datasets also showed this artifact (data not shown). In addition to this being a strand-specific issue, it appears that this is a read-specific phenomenon. Whilst there is a quality drop in the first read following these GC-rich motifs, there is a striking loss of quality in read 2, where the reads have nearly half the mean quality value compared to the read 1 reads for GC-rich triplets that follow the GGC motif. We could observe this low quality in read 2 in all our analysed Illumina lanes. For AT-rich motifs the ratio is nearly 1 (1.03).
Overall the rate of SNP calling was slightly higher for the Ion Torrent data than for Illumina data (chi square p value 3.15E-08), with approximately 82% of SNPs being correctly called for the PGM and 68-76% of the SNPs being detected from the Illumina data (Figure 5A). Conversely, the rate of false SNP calls was higher with Ion Torrent data than for Illumina data (Figure 5B). SNP calling from PacBio data proved more problematic, as existing tools are optimized for short-read data and not for high error-rate long-read data. We were reliant on SNPs called by the SMRT portal pipeline for this analysis. Our results showed that SNP detection from PacBio data was not as accurate as that from the other platforms, with overall only 71% of SNPs being detected and 2876 SNPs being falsely called (Additional file 5: Table S6).
Whilst one would normally use higher coverage than used here for confident SNP detection (i.e., 30-40x depth), we were limited to 15x depth due to the yield of some of the platforms. Nonetheless, at least for the haploid genome, S. aureus, 15x coverage should be a reasonable quantity for SNP detection and even in the human genome, 15x coverage has been shown to be sufficient to accurately call heterozygous SNPs [3].
Additional file 2: Figure S1: Comparison of the outcome of sequencing using libraries prepared using enzymatic shearing (green line) and physical shearing (blue line) on the Ion Torrent PGM. A) The percentage of the P. falciparum genome covered at different read depths; B) The number of bases covered at different depths; C) Sequence representation versus GC content. Figure S2. Genome coverage uniformity plots for 15x depth randomly normalized sequence coverage from sequencing libraries prepared using standard and Nextera Library preparation methods. A) The percentage of the B. pertussis genome covered at different read depths; B) The number of bases covered at different depths for B. pertussis; C) The percentage of the S. aureus genome covered at different read depths; D) The number of bases covered at different depths for S. aureus; E) The percentage of the P. falciparum genome covered at different read depths; and F) The number of bases covered at different depths for P. falciparum. Figure S3. Sequence representation versus GC content for 15x depth randomly normalized sequence coverage from sequencing libraries prepared using standard and Nextera Library preparation methods. Genome coverage uniformity plots for 15x depth randomly normalized sequence coverage from sequencing libraries prepared using the Illumina Nextera Library preparation kit (blue line) compared to those prepared using a standard Illumina library preparation with Kapa HiFi for library amplification (green line), on: A) B. pertussis; B) S. aureus and C) P. falciparum genomes. Figure S4. Sequence representation versus GC content for 15x depth randomly normalized sequence coverage from the sequencing platforms tested, on: A) B. pertussis; B) and C) P. falciparum genomes. (PPT 962 KB)
The search engine is now prominently displaying several torrent sites at the top of search results, despite its longstanding cooperation with the entertainment industry to demote links to copyright-infringing content.
A carousel with more than a dozen torrent sites, including the Pirate Bay and Torrent Project, now appears when you search for terms like "torrent sites" or "best torrent sites." Clicking on one of the sites shown in the carousel surfaces search results related to the site.
First spotted by Torrent Freak(Opens in a new tab), we don't know how long Google has been displaying the torrent results. Torrent Freak also found that Google displays links to streaming sites known to host pirated content, like Putlocker and Alluc, alongside links to legitimate services, like Hulu and Crackle.
Each torrent gets assigned a health status showing its status using colors. The health reflects the connection status of that torrent. Typically, all your torrents will have the same status after a while, but that may depend on the swarm size etc. The important part is that the "best" status you reach tells you most about the correctness of your network settings. The goal is to reach green health .
The "smiley" icon can be seen e.g. in Library, in My torrents, in torrent details etc. If you do not have the smiley visible by default, you can add the Health column to the table by using Column setup.
Note: Some small torrents will never attain green status, simply because there are no remote connections to connect to. For example, if there is only one active peer in addition to you, and you manage to connect to him first, then there is nobody to contact you, and the status will remain yellow.
One of the most typical errors you may receive is that of "Invalid passkey" or "Unauthorized torrent". You may receive them, if you try to use such .torrent files, which use a private tracker. If you have not received the .torrent file directly from the private tracker web site, it is possible that the private tracker will reject your connection attempt as it is not your personalised copy of that torrent. (The torrent has been created for somebody else, who has then shared it with you either directly or by uploading it to an index site where you have then found it.) 2ff7e9595c
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